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Library and information science: practice, theory, and philosophical basis

2000, Information processing & management

Related Papers

WA A Weerasooriya

Bijan Kumar Roy

Luciano Floridi

This paper analyses the relations between philosophy of information (PI), library and information science (LIS) and social epistemology (SE). In the 􏰜rst section, it is argued that there is a natural relation between philosophy and LIS but that SE cannot provide a satisfactory foundation for LIS. SE should rather be seen as sharing with LIS a common ground, represented by the study of information, to be investigated by a new discipline, PI. In the second section, the nature of PI is outlined as the philosophical area that studies the conceptual nature of information, its dynamics and problems. In the third section, LIS is de􏰜ned as a form of applied PI. The hypothesis supported is that PI should replace SE as the philosophical discipline that can best provide the conceptual foundation for LIS. In the conclusion, it is suggested that the ‘identity’ crisis undergone by LIS has been the natural outcome of a justi􏰜ed but precocious search for a philosophical counterpart that has emerged only recently: namely, PI. The development of LIS should not rely on some borrowed, pre-packaged theory. As applied PI, LIS can fruitfully contribute to the growth of basic theoretical research in PI itself and thus provide its own foundation.

InSITE Conference

gholamreza fadaie

Prakash Jadhav

One can define research as a scientific and systematic search for pertinent information on a specific topic. Research leads to progress in a profession. This paper is based on a survey of Ph.D. research in Library and Information Science in India. The study also deals with historical and developmental changes in the field of library and information science. It also focuses on the recent research trends due to emergence and use of Information and Communication Technology in the library as well as allied fields. The present study shows the scope for new research in various fields in LIS.

International Review of Humanities Studies

Taufik Asmiyanto

This article reviews the shift in the theoretical foundations of library and information science (LIS) on social epistemology to the philosophy of information. This shift bids have been submitted more than a decade ago where Luciano Floridi sees that the LIS has close relations with the philosophy of information. Paul Ricoeur's Hermeneutics Phenomenology used to understand and interpret Jesse Shera and Luciano Floridi's texts and to reveal the implicit and hidden meanings in the text. This reading indicates that the LIS is a discipline that not only deals with knowledge alone but rather takes care of the content that we understand as meaningful data. With that also, we understand the information not only as a matter of semantic and regarded as an epistemic prerequisite for the establishment of knowledge. However, beyond that, the information is placed as the ontological. Meaning of information, then, becomes important for LIS to place in the appropriate position. The foundation on the philosophy of information can break the chain of LIS dependence on another field theory and develop his theory. Therefore, this foundation does not only contribute praxis to produce solutions to technical problems that are commonly done regarding the improvement and development of library services. Although, this foundation can provide a 'new' space for scientists in this field to expand its epistemic motion.

Michael Bemis

This unique annotated bibliography is a complete, up-to-date guide to sources of information on library science, covering recent books, monographs, periodicals and websites, and selected works of historical importance. Far from just compiling a simple list of sources, Bemis digs deeper, examining the strengths and weaknesses of key works. A boon to researchers and practitioners alike, this bibliography *as a profession, the ethics of information science, cataloging, reference work, and library architecture *Encompasses encyclopedias, dictionaries, directories, photographic surveys, statistical publications, and numerous electronic sources, all categorized by subject *Offers appendixes detailing leading professional organizations and publishers of library and information science literature This coimprehensive bibliography of English-language resources on librarianship, the only one of its kind, will prove invaluable to scholars, students, and anyone working in the field.

Australian Academic and Research Libraries

Concepcion Wilson

Australian Academic & Research Libraries

Library information science (LIS) should develop its foundation in terms of a philosophy of information (PI).

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Research Methods in Library and Information Science

Submitted: 28 October 2016 Reviewed: 23 March 2017 Published: 28 June 2017

DOI: 10.5772/intechopen.68749

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Library and information science (LIS) is a very broad discipline, which uses a wide rangeof constantly evolving research strategies and techniques. The aim of this chapter is to provide an updated view of research issues in library and information science. A stratified random sample of 440 articles published in five prominent journals was analyzed and classified to identify (i) research approach, (ii) research methodology, and (iii) method of data analysis. For each variable, a coding scheme was developed, and the articles were coded accordingly. A total of 78% of the articles reported empirical research. The rest 22% were classified as non‐empirical research papers. The five most popular topics were “information retrieval,” “information behaviour,” “information literacy,” “library services,” and “organization and management.” An overwhelming majority of the empirical research articles employed a quantitative approach. Although the survey emerged as the most frequently used research strategy, there is evidence that the number and variety of research methodologies have been increased. There is also evidence that qualitative approaches are gaining increasing importance and have a role to play in LIS, while mixed methods have not yet gained enough recognition in LIS research.

library and information science
research methods
research strategies
data analysis techniques
research articles

Author Information

Aspasia togia *.

Department of Library Science & Information Systems, Technological Educational Institute (TEI) of Thessaloniki, Greece

Afrodite Malliari

DataScouting, Thessaloniki, Greece

*Address all correspondence to: [email protected]

1. Introduction

Library and information science (LIS), as its name indicates, is a merging of librarianship and information science that took place in the 1960s [ 1 , 2 ]. LIS is a field of both professional practice and scientific inquiry. As a field of practice, it includes the profession of librarianship as well as a number of other information professions, all of which assume the interplay of the following:

information content,

the people who interact with the content, and

the technology used to facilitate the creation, communication, storage, or transformation of the content [ 3 ].

The disciplinary foundation of LIS, which began in the 1920s, aimed at providing a theoretical foundation for the library profession. LIS has evolved in close relationship with other fields of research, especially computer science, communication studies, and cognitive sciences [ 4 ].

The connection of LIS with professional practice, on one hand, and other research fields on the other has influenced its research orientation and the development of methodological tools and theoretical perspectives [ 5 ]. Research problems are diverse, depending on the research direction, local trends, etc. Most of them relate to the professional practice although there are theoretical research statements as well. LIS research strives to address important information issues, such as these of “ information retrieval, information quality and authenticity, policy for access and preservation, the health and security applications of data mining ”(p. 3) [ 6 ]. The research is multidisciplinary in nature, and it has been heavily influenced by research designs developed in the social, behavioral, and management sciences and to a lesser extent by the theoretical inquiry adopted in the humanities [ 7 ]. Methods used in information retrieval research have been adapted from computer science. The emergence of evidence‐based librarianship in the late 1990s brought a positivist approach to LIS research, since it incorporated many of the research designs and methods used in clinical medicine [ 7 , 8 ]. In addition, LIS has developed its own methodological approaches, a prominent example of which is bibliometrics. Bibliometrics, which can be defined as “ the use of mathematical and statistical methods to study documents and patterns of publication ” (p. 38) [ 9 ], is a native research methodology, which has been extensively used outside the field, especially in science studies [ 10 ].

Library and information science research has been often criticized as being fragmentary, narrowly focused, and oriented to practical problems [ 11 ]. Many authors have noticed limited use of theory in published research and have advocated greater use of theory as a conceptual basis in LIS research [ 4 , 11 – 14 ]. Feehan et al. [ 13 ] claimed that LIS literature has not evolved enough to support a rigid body of its own theoretical basis. Jarvelin and Vakkari [ 15 ] argued that LIS theories are usually vague and conceptually unclear, and that research in LIS has been dominated by a paradigm which “ has made little use of such traditional scientific approaches as foundations and conceptual analysis, or of scientific explanation and theory formulation ” (p. 415). This lack of theoretical contributions may be associated with the fact that LIS emanated from professional practice and is therefore closely linked to practical problems such as the processing and organization of library materials, documentation, and information retrieval [ 15 , 16 ].

In this chapter, after briefly discussing the role of theory in LIS research, we provide an updated view of research issues in the field that will help scholars and students stay informed about topics related to research strategies and methods. To accomplish this, we describe and analyze patterns of LIS research activity as reflected in prominent library journals. The analysis of the articles highlights trends and recurring themes in LIS research regarding the use of multiple methods, the adoption of qualitative approaches, and the employment of advanced techniques for data analysis and interpretation [ 17 ].

2. The role of theory in LIS research

The presence of theory is an indication of research eminence and respectability [ 18 ], as well as a feature of discipline’s maturity [ 19 , 20 ]. Theory has been defined in many ways. “ Any of the following have been used as the meaning of theory: a law, a hypothesis, group of hypotheses, proposition, supposition, explanation, model, assumption, conjecture, construct, edifice, structure, opinion, speculation, belief, principle, rule, point of view, generalization, scheme, or idea ” (p. 309) [ 21 ]. A theory can be described as “ a set of interrelated concepts, definitions, and propositions that explains or predicts events or situations by specifying relations among variables ” [ 22 ]. According to Babbie [ 23 ], research is “ a systematic explanation for the observed facts and laws that related to a particular aspect of life ” (p. 49). It is “ a multiple‐level component of the research process, comprising a range of generalizations that move beyond a descriptive level to a more explanatory level ” [ 24 ] (p. 319). The role of theory in social sciences is, among other things, to explain and predict behavior, be usable in practical applications, and guide research [ 25 ]. According to Smiraglia [ 26 ], theory does not exist in a vacuum but in a system that explains the domains of human actions, the phenomena found in these domains, and the ways in which they are affected. He maintains that theory is developed by systematically observing phenomena, either in the positivist empirical research paradigm or in the qualitative hermeneutic paradigm. Theory is used to formulate hypotheses in quantitative research and confirms observations in qualitative research.

Glazier and Grover [ 24 ] proposed a model for theory‐building in LIS called “circuits of theory.” The model includes taxonomy of theory, developed earlier by the authors [ 11 ], and the critical social and psychological factors that influence research. The purpose of the taxonomy was to demonstrate the relationships among the concepts of research, theory, paradigms, and phenomena. Phenomena are described as “ events experienced in the empirical world ” (p. 230) [ 11 ]. Researchers assign symbols (digital or iconic representations, usually words or pictures) to phenomena, and meaning to symbols, and then they conceptualize the relationships among phenomena and formulate hypotheses and research questions. “ In the taxonomy, empirical research begins with the formation of research questions to be answered about the concepts or hypotheses for testing the concepts within a narrow set of predetermined parameters ” (p. 323) [ 24 ]. Various levels of theories, with implications for research in library and information Science, are described. The first theory level, called substantive theory , is defined as “ a set of propositions which furnish an explanation for an applied area of inquiry ” (p. 233) [ 11 ]. In fact, it may not be viewed as a theory but rather be considered as a research hypothesis that has been tested or even a research finding [ 16 ]. The next level of theory, called formal theory , is defined as “ a set of propositions which furnish an explanation for a formal or conceptual area of inquiry, that is, a discipline ” (p. 234) [ 11 ]. Substantive and formal theories together are usually considered as “middle range” theory in the social sciences. Their difference lies in the ability to structure generalizations and the potential for explanation and prediction. The final level, grand theory , is “ a set of theories or generalizations that transcend the borders of disciplines to explain relationships among phenomena ” (p. 321) [ 24 ]. According to the authors, most research generates substantive level theory, or, alternatively, researchers borrow theory from the appropriate discipline, apply it to the problem under investigation, and reconstruct the theory at the substantive level. Next in the hierarchy of theoretical categories is the paradigm , which is described as “ a framework of basic assumptions with which perceptions are evaluated and relationships are delineated and applied to a discipline or profession ” (p. 234) [ 11 ]. Finally, the most significant theoretical category is the world view , which is defined as “ an individual’s accepted knowledge, including values and assumptions, which provide a ‘filter’ for perception of all phenomena ” (p. 235) [ 11 ]. All the previous categories contribute to shaping the individual’s worldview. In the revised model, which places more emphasis on the impact of social environment on the research process, research and theory building is surrounded by a system of three basic contextual modules: the self, society, and knowledge, both discovered and undiscovered. The interactions and dialectical relationships of these three modules affect the research process and create a dynamic environment that fosters theory creation and development. The authors argue that their model will help researchers build theories that enable generalizations beyond the conclusions drawn from empirical data [ 24 ].

In an effort to propose a framework for a unified theory of librarianship, McGrath [ 27 ] reviewed research articles in the areas of publishing, acquisitions, classification and knowledge organization, storage, preservation and collection management, library collections, and circulations. In his study, he included articles that employed explanatory and predictive statistical methods to explore relationships between variables within and between the above subfields of LIS. For each paper reviewed, he identified the dependent variable, significant independent variables, and the units of analysis. The review displayed explanatory studies “ in nearly every level, with the possible exception of classification, while studies in circulation and use of the library were clearly dominant. A recapitulation showed that a variable at one level may be a unit of analysis at another, a property of explanatory research crucial to the development of theory, which has been either ignored or unrecognized in LIS literature ” (p. 368) [ 27 ]. The author concluded that “explanatory and predictive relationships do exist and that they can be useful in constructing a comprehensive unified theory of librarianship” (p. 368) [ 27 ].

Recent LIS literature provides several analyses of theory development and use in the field. In a longitudinal analysis of information needs and uses of literature, Julien and Duggan [ 28 ] investigated, among other things, to what extent LIS literature was grounded in theory. Articles “ based on a coherent and explicit framework of assumptions, definitions, and propositions that, taken together, have some explanatory power ” (p. 294) were classified as theoretical articles. Results showed that only 18.3% of the research studies identified in the sample of articles examined were theoretically grounded.

Pettigrew and McKechnie [ 29 ] analyzed 1160 journal articles published between 1993 and 1998 to determine the level of theory use in information science research. In the absence of a singular definition of theory that would cover all the different uses of the term in the sample of articles, they operationalized “theory” according to authors’ use of the term. They found that 34.1% of the articles incorporated theory, with the largest percentage of theories drawn from the social sciences. Information science itself was the second most important source of theories. The authors argued that this significant increase in theory use in comparison to earlier studies could be explained by the research‐oriented journals they selected for examination, the sample time, and the broad way in which they defined “theory.” With regard to this last point, that is, their approach of identifying theories only if the author(s) describe them as such in the article, Pettigrew and McKechnie [ 29 ] observed significant differences in how information science researchers perceive theory:

Although it is possible that conceptual differences regarding the nature of theory may be due to the different disciplinary backgrounds of researchers in IS, other themes emerged from our data that suggest a general confusion exists about theory even within subfields. Numerous examples came to light during our analysis in which an author would simultaneously refer to something as a theory and a method, or as a theory and a model, or as a theory and a reported finding. In other words, it seems as though authors, themselves, are sometimes unsure about what constitutes theory. Questions even arose regarding whether the author to whom a theory was credited would him or herself consider his or her work as theory (p. 68).

Kim and Jeong [ 16 ] examined the state and characteristics of theoretical research in LIS journals between 1984 and 2003. They focused on the “theory incident,” which is described as “an event in which the author contributes to the development or the use of theory in his/her paper.” Their study adopted Glazier and Grover’s [ 24 ] model of “circuits of theory.” Substantive level theory was operationalized to a tested hypothesis or an observed relationship, while both formal and grand level theories were identified when they were named as “theory,” “model,” or “law” by authors other than those who had developed them. Results demonstrated that the application of theory was present in 41.4% of the articles examined, signifying a significant increase in the proportion of theoretical articles as compared to previous studies. Moreover, it was evident that both theory development and theory use had increased by the year. Information seeking and use, and information retrieval, were identified as the subfields with the most significant contribution to the development of the theoretical framework.

In a more in‐depth analysis of theory use in Kumasi et al. [ 30 ] qualitatively analyzed the extent to which theory is meaningfully used in scholarly literature. For this purpose, they developed a theory talk coding scheme, which included six analytical categories, describing how theory is discussed in a study. The intensity of theory talk in the articles was described across a continuum from minimal (e.g., theory is discussed in literature review and not mentioned later) through moderate (e.g., multiple theories are introduced but without discussing their relevance to the study) to major (e.g., theory is employed throughout the study). Their findings seem to support the opinion that “ LIS discipline has been focused on the application of specific theoretical frameworks rather than the generation of new theories ” (p. 179) [ 30 ]. Another point the authors made was about the multiple terms used in the articles to describe theory. Words such as “framework,” “model,” or “theory” were used interchangeably by scholars.

It is evident from the above discussion that the treatment of theory in LIS research covers a spectrum of intensity, from marginal mentions to theory revising, expanding, or building. Recent analyses of the published scholarship indicate that the field has not been very successful in contributing to existing theory or producing new theory. In spite of this, one may still assert that LIS research employs theory, and, in fact, there are many theories that have been used or generated by LIS scholars. However, “ calls for additional and novel theory development work in LIS continue, particularly for theories that might help to address the research practice gap ” (p. 12) [ 31 ].

3. Research strategies in LIS

3.1. surveys of research methods.

LIS is a very broad discipline, which uses a wide range of constantly evolving research strategies and techniques [ 32 ]. Various classification schemes have been developed to analyze methods employed in LIS research (e.g., [ 13 , 15 , 17 , 33 – 35 , 38 ]). Back in 1996, in the “research record” column of the Journal of Education for Library and Information Science, Kim [ 36 ] synthesized previous categories and definitions and introduced a list of research strategies, including data collection and analysis methods. The listing included four general research strategies: (i) theoretical/philosophical inquiry (development of conceptual models or frameworks), (ii) bibliographic research (descriptive studies of books and their properties as well as bibliographies of various kinds), (iii) R&D (development of storage and retrieval systems, software, interface, etc.), and (iv) action research, it aims at solving problems and bringing about change in organizations. Strategies are then divided into quantitative and qualitative driven. In the first category are included descriptive studies, predictive/explanatory studies, bibliometric studies, content analysis, and operation research studies. Qualitative‐driven strategies are considered the following: case study, biographical method, historical method, grounded theory, ethnography, phenomenology, symbolic interactionism/semiotics, sociolinguistics/discourse analysis/ethnographic semantics/ethnography of communication, and hermeneutics/interpretive interactionism (p. 378–380) [ 36 ].

Systematic studies of research methods in LIS started in the 1980s and several reviews of the literature have been conducted over the past years to analyze the topics, methodologies, and quality of research. One of the earliest studies was done by Peritz [ 37 ] who carried out a bibliometric analysis of the articles published in 39 core LIS journals between 1950 and 1975. She examined the methodologies used, the type of library or organization investigated, the type of activity investigated, and the institutional affiliation of the authors. The most important findings were a clear orientation toward library and information service activities, a widespread use of the survey methodology, a considerable increase of research articles after 1960, and a significant increase in theoretical studies after 1965.

Nour [ 38 ] followed up on Peritz’s [ 37 ] work and studied research articles published in 41 selected journals during the year 1980. She found that survey and theoretical/analytic methodologies were the most popular, followed by bibliometrics. Comparing these findings to those made by Peritz [ 37 ], Nour [ 38 ] found that the amount of research continued to increase, but the proportion of research articles to all articles had been decreasing since 1975.

Feehan et al. [ 13 ] described how LIS research published during 1984 was distributed over various topics and what methods had been used to study these topics. Their analysis revealed a predominance of survey and historical methods and a notable percentage of articles using more than one research method. Following a different approach, Enger et al. (1989) focused on the statistical methods used by LIS researchers in articles published during 1985 [ 39 ]. They found that only one out of three of the articles reported any use of statistics. Of those, 21% used descriptive statistics and 11% inferential statistics. In addition, the authors found that researchers from disciplines other than LIS made the highest use of statistics and LIS faculty showed the highest use of inferential statistics.

An influential work, against which later studies have been compared, is that of Jarvelin and Vakkari [ 15 ] who studied LIS articles published in 1985 in order to determine how research was distributed over various subjects, what approaches had been taken by the authors, and what research strategies had been used. The authors replicated their study later to include older research published between 1965 and 1985 [ 40 ]. The main finding of these studies was that the trends and characteristics of LIS research remained more or less the same over the aforementioned period of 20 years. The most common topics were information service activities and information storage and retrieval. Empirical research strategies were predominant, and of them, the most frequent was the survey. Kumpulainen [ 41 ], in an effort to provide a continuum with Jarvelin and Vakkeri’s [ 15 ] study, analyzed 632 articles sampled from 30 core LIS journals with respect to various characteristics, including topics, aspect of activity, research method, data selection method, and data analysis techniques. She used the same classification scheme, and she selected the journals based on a slightly modified version of Jarvelin and Vakkari’s [ 15 ] list. Library services and information storage and retrieval emerged again as the most common subjects approached by the authors and survey was the most frequently used method.

More recent studies of this nature include those conducted by Koufogiannakis et al. [ 42 ], Hildreth and Aytac [ 43 ], Hider and Pymm [ 32 ], and Chu [ 17 ]. Koufogiannakis et al. [ 42 ] examined research articles published in 2001 and they found that the majority of them were questionnaire‐based descriptive studies. Comparative, bibliometrics, content analysis, and program evaluation studies were also popular. Information storage and retrieval emerged as the predominant subject area, followed by library collections and management. Hildreth and Aytac [ 43 ] presented a review of the 2003–2005 published library research with special focus on methodology issues and the quality of published articles of both practitioners and academic scholars. They found that most research was descriptive and the most frequent method for data collection was the questionnaire, followed by content analysis and interviews. With regard to data analysis, more researchers used quantitative methods, considerably less used qualitative‐only methods, whereas 61 out of 206 studies included some kind of qualitative analysis, raising the total percentage of qualitative methods to nearly 50%. With regard to the quality of published research, the authors argued that “ the majority of the reports are detailed, comprehensive, and well‐organized ” (p. 254) [ 43 ]. Still, they noticed that the majority of reports did not mention the critical issues of research validity and reliability and neither did they indicate study limitations or future research recommendations. Hider and Pymm [ 32 ] described content analysis of LIS literature “ which aimed to identify the most common strategies and techniques employed by LIS researchers carrying out high‐profile empirical research ” (p. 109). Their results suggested that while researchers employed a wide variety of strategies, they mostly used surveys and experiments. They also observed that although quantitative research accounted for more than 50% of the articles, there was an increase in the use of most sophisticated qualitative methods. Chu [ 17 ] analyzed the research articles published between 2001 and 2010 in three major journals and reported the following most frequent research methods: theoretical approach (e.g., conceptual analysis), content analysis, questionnaire, interview, experiment, and bibliometrics. Her study showed an increase in both the number and variety of research methods but lack of growth in the use of qualitative research or in the adoption of multiple research methods.

In summary, the literature shows a continued interest in the analysis of published LIS research. Approaches include focusing on particular publication years, geographic areas, journal titles, aspects of LIS, and specific characteristics, such as subjects, authorship, and research methods. Despite the abundance of content analyses of LIS literature, the findings are not easily comparable due to differences in the number and titles of journals examined, in the types of the papers selected for analysis, in the periods covered, and in classification schemes developed by the authors to categorize article topics and research strategies. Despite the differences, some findings are consistent among all studies:

Information seeking, information retrieval, and library and information service activities are among the most common subjects studied,

Descriptive research methodologies based on surveys and questionnaires predominate,

Over the years, there has been a considerable increase in the array of research approaches used to explore library issues, and

Data analysis is usually limited to descriptive statistics, including frequencies, means, and standard deviations.

3.2. Data collection and analysis

Articles published between 2011 and 2016 were obtained from the following journals: Library and Information Science Research, College & Research Libraries, Journal of Documentation, Information Processing & Management, and Journal of Academic Librarianship ( Table 1 ). These five titles were selected as data sources because they have the highest 5‐year impact factor of the journals classified in Ulrich’s Serials Directory under the “Library and Information Sciences” subject heading. From the journals selected, only full‐length articles were collected. Editorials, book reviews, letters, interviews, commentaries, and news items were excluded from the analysis. This selection process yielded 1643 articles. A stratified random sample of 440 articles was chosen for in‐depth analysis ( Table 2 ). For the purpose of this study, five strata, corresponding to the five journals, were used. The sample size was determined using a margin of error, 4%, and confidence interval, 95%.

Table 1.

Profile of the journals.

Table 2.

Journal titles.

Each article was classified as either research or theoretical. Articles that employed specific research methodology and presented specific findings of original studies performed by the author(s) were considered research articles. The kind of study may vary (e.g., it could be an experiment, a survey, etc.), but in all cases, raw data had been collected and analyzed, and conclusions were drawn from the results of that analysis. Articles reporting research in system design or evaluation in the information systems field were also regarded as research articles . On the other hand, works that reviewed theories, theoretical concepts, or principles discussed topics of interest to researchers and professionals, or described research methodologies were regarded as theoretical articles [ 44 ] and were classified in the no‐empirical‐research category. In this category, were also included literature reviews and articles describing a project, a situation, a process, etc.

Each article was classified into a topical category according to its main subject. The articles classified as research were then further explored and analyzed to identify (i) research approach, (ii) research methodology, and (iii) method of data analysis. For each variable, a coding scheme was developed, and the articles were coded accordingly. The final list of the analysis codes was extracted inductively from the data itself, using as reference the taxonomies utilized in previous studies [ 15 , 32 , 43 , 45 ]. Research approaches “ are plans and procedures for research ” (p. 3) [ 46 ]. Research approaches can generally be grouped as qualitative, quantitative, and mixed methods studies. Quantitative studies aim at the systematic empirical investigation of quantitative properties or phenomena and their relationships. Qualitative research can be broadly defined as “ any kind of research that produces findings not arrived at by means of statistical procedures or other means of quantification ” (p. 17) [ 47 ]. It is a way to gain insights through discovering meanings and explaining phenomena based on the attributes of the data. In mixed model research, quantitative and qualitative approaches are combined within or across the stages of the research process. It was beyond the scope of this study to identify in which stages of a study—data collection, data analysis, and data interpretation—the mixing was applied or to reveal the types of mixing. Therefore, studies using both quantitative and qualitative methods, irrespective of whether they describe if and how the methods were integrated, were coded as mixed methods studies.

Research methodologies , or strategies of inquiry, are types of research models “ that provide specific direction for procedures in a research design ” (p. 11) [ 46 ] and inform the decisions concerning data collection and analysis. A coding schema of research methodologies was developed by the authors based on the analysis of all research articles included in the sample. The methodology classification included 12 categories ( Table 3 ). Each article was classified into one category for the variable research methodology . If more than one research strategy was mentioned (e.g., experiment and survey), the article was classified according to the main strategy.

Table 3.

Coding schema for research methodologies.

Methods of data analysis refer to the techniques used by the researchers to explore the original data and answer their research problems or questions. Data analysis for quantitative researches involves statistical analysis and interpretation of figures and numbers. In qualitative studies, on the other hand, data analysis involves identifying common patterns within the data and making interpretations of the meanings of the data. The array of data analysis methods included the following categories:

Descriptive statistics,

Inferential statistics,

Qualitative data analysis,

Experimental evaluation, and

Other methods,

Descriptive statistics are used to describe the basic features of the data in a study. Inferential statistics investigate questions, models, and hypotheses. Mathematical analysis refers to mathematic functions, etc. used mainly in bibliometric studies to answer research questions associated with citation data. Qualitative data analysis is the range of processes and procedures used for the exploration of qualitative data, from coding and descriptive analysis to identification of patterns and themes and the testing of emergent findings and hypotheses. It was used in this study as an overarching term encompassing various types of analysis, such as thematic analysis, discourse analysis, or grounded theory analysis. The class experimental evaluation was used for system and software analysis and design studies which assesses the newly developed algorithm, tool, method, etc. by performing experiments on selected datasets. In these cases, “experiments” differ from the experimental designs in social sciences. Methods that did not fall into one of these categories (e.g., mathematical analysis, visualization, or benchmarking) were classified as other methods . If both descriptive and inferential statistics were used in an article, only the inferential were recorded. In mixed methods studies, each method was recorded in the order in which it was reported in the article.

Ten percent of the articles were randomly selected and used to establish inter‐rater reliability and provide basic validation of the coding schema. Cohen’s kappa was calculated for each coded variable. The average Cohen’s kappa value was κ = 0.60, p < 0.000 (the highest was 0.63 and lowest was 0.59). This indicates a substantial agreement [ 48 ]. The coding disparities across raters were discussed, and the final codes were determined via consensus.

3.3. Results

3.3.1. topic.

Table 4 presents the distribution of articles over the various topics, for each of which a detailed description is provided. The five most popular topics of the papers in the total sample of 440 articles were “information retrieval,” “information behavior,” “information literacy,” “library services,” and “organization and management.” These areas cover over 60% of all topics studied in the papers. The least‐studied topics (covered in less than eight papers) fall into the categories of “information and knowledge management,” “library information systems,” “LIS theory,” and “infometrics.”

Table 4.

Article topics.

Figure 1 shows how the top five topics are distributed across journals. As expected, the topic “information retrieval” has higher publication frequencies in Information Processing & Management, a journal focusing on system design and issues related to the tools and techniques used in storage and retrieval of information. “Information literacy,” “information behavior,” “library services,” and “organization and management” appear to be distributed almost proportionately in College & Research Libraries. “Information literacy” seems to be a more preferred topic in the Journal of Academic Librarianship, while “information behavior” is more popular in the Journal of Documentation and Library & Information Science Research.

research paper in library and information science pdf

Figure 1.

Distribution of topics across journals.

3.3.2. Research approach and methodology

Of all articles examined, 343 articles, which represent the 78% of the sample, reported empirical research. The rest 22% (N = 97) were classified as non‐empirical research papers. Research articles were coded as quantitative, qualitative, or mixed methods studies. An overwhelming majority (70%) of the empirical research articles employed a quantitative research approach. Qualitative and mixed methods research was reported in 21.6 and 8.5% of the articles, respectively ( Figure 2 ).

Figure 2.

Research approach.

Table 5 presents the distribution of research approaches over the five most famous topics. The quantitative approach clearly prevails in all topics, especially in information retrieval research. However, qualitative designs seem to gain acceptance in all topics (except information retrieval), while in information behavior research, quantitative and qualitative approaches are almost evenly distributed. Mixed methods were quite frequent in information literacy and information behavior studies and less popular in the other topics.

Table 5.

Topics across research approach.

The most frequently used research strategy was survey, accounting for almost 37% of all research articles, followed by system and software analysis and design, a strategy used in this study specifically for research in information systems (Jarvelin & Vakkari, 1990). This result is influenced by the fact that Information Processing & Management addresses issues at the intersection between LIS and computer science, and the majority of its articles present the development of new tools, algorithms, methods and systems, and their experimental evaluation. The third‐ and fourth‐ranking strategies were content analysis and bibliometrics. Case study, experiment, and secondary data analysis were represented by 15 articles each, while the rest of the techniques were underrepresented with considerably fewer articles ( Table 6 ).

Table 6.

Research methodologies.

3.3.3. Methods of data analysis

Table 7 displays the frequencies for each type of data analysis.

Table 7.

Method of data analysis.

Almost half of the empirical research papers examined reported any use of statistics. Descriptive statistics, such as frequencies, means, or standard deviations, were more frequently used compared to inferential statistics, such as ANOVA, regression, or factor analysis. Nearly one‐third of the articles employed some type of qualitative data analysis either as the only method or—in mixed methods studies—in combination with quantitative techniques.

3.4. Discussions and conclusions

The patterns of LIS research activity as reflected in the articles published between 2011 and 2016 in five well‐established, peer‐reviewed journals were described and analyzed. LIS literature addresses many and diverse topics. Information retrieval, information behavior, and library services continue to attract the interest of researchers as they are core areas in library science. Information retrieval has been rated as one of the most famous areas of interest in research articles published between 1965 and 1985 [ 40 ]. According to Dimitroff [ 49 ], information retrieval was the second most popular topic in the articles published in the Bulletin of the Medical Library Association, while Cano [ 50 ] argued that LIS research produced in Spain from 1977 to 1994 was mostly centered on information retrieval and library and information services. In addition, Koufogiannakis et al. [ 42 ] found that information access and retrieval were the domain with the most research, and in Hildreth and Aytac’s [ 43 ] study, most articles were dealing with issues related to users (needs, behavior, information seeking, etc.), services, and collections. The present study provides evidence that the amount of research in information literacy is increasing, presumably due to the growing importance of information literacy instruction in libraries. In recent years, there is an ongoing educational role for librarians, who are more and more actively engaging in the teaching and learning processes, a trend that is reflected in the research output.

With regard to research methodologies, the present study seems to confirm the well‐documented predominance of survey in LIS research. According to Dimitroff [ 49 ], the percentage related to use of survey research methods reported in various studies varied between 20.3 and 41.5%. Powell [ 51 ], in a review of the research methods appearing in LIS literature, pointed out that survey had consistently been the most common type of study in both dissertations and journal articles. Survey reported the most widely used research design by Jarvelin and Vakkari [ 40 ], Crawford [ 52 ], Hildreth and Aytac [ 43 ], and Hider and Pymm [ 32 ]. The majority of articles examined by Koufogiannakis et al. [ 42 ] were descriptive studies using questionnaires/surveys. In addition, survey methods represented the largest proportion of methods used in information behavior articles analyzed by Julien et al. [ 53 ]. There is no doubt that survey has been used more than any other method in LIS research. As Jarvelin and Vakkari [ 15 ] put it, “it appears that the field is so survey‐oriented that almost all problems are seen through a survey viewpoint” (p. 416). Much of survey’s popularity can be ascribed to its being a well‐known, understood, easily conducted, and inexpensive method, which is easy to analyze results [ 41 , 42 ]. However, our findings suggest that while the survey ranks high, a variety of other methods have been also used in the research articles. Content analysis emerged as the third‐most frequent strategy, a finding similar to those of previous studies [ 17 , 32 ]. Although content analysis was not regarded by LIS researchers as a favored research method until recently, its popularity seems to be growing [ 17 ].

Quantitative approaches, which dominate, tend to rely on frequency counts, percentages, and descriptive statistics used to describe the basic features of the data in a study. Fewer studies used advanced statistical analysis techniques, such as t‐tests, correlation, and regressions, while there were some examples of more sophisticated methods, such as factor analysis, ANOVA, MANOVA, and structural equation modeling. Researchers engaging in quantitative research designs should take into consideration the use of inferential statistics, which enables the generalization from the sample being studied to the population of interest and, if used appropriately, are very useful for hypothesis testing. In addition, multivariate statistics are suitable for examining the relationships among variables, revealing patterns and understanding complex phenomena.

The findings also suggest that qualitative approaches are gaining increasing importance and have a role to play in LIS studies. These results are comparable to the findings of Hider and Pymm [ 32 ], who observed significant increases for qualitative research strategies in contemporary LIS literature. Qualitative analysis description varied widely, reflecting the diverse perspectives, analysis methods, and levels of depth of analysis. Commonly used terms in the articles included coding, content analysis, thematic analysis, thematic analytical approach, theme, or pattern identification. One could argue that the efforts made to encourage and promote qualitative methods in LIS research [ 54 , 55 ] have made some impact. However, qualitative research methods do not seem to be adequately utilized by library researchers and practitioners, despite their potential to offer far more illuminating ways to study library‐related issues [ 56 ]. LIS research has much to gain from the interpretive paradigm underpinning qualitative methods. This paradigm assumes that social reality is

the product of processes by which social actors together negotiate the meanings for actions and situations; it is a complex of socially constructed meanings. Human experience involves a process of interpretation rather than sensory, material apprehension of the external physical world and human behavior depends on how individuals interpret the conditions in which they find themselves. Social reality is not some ‘thing’ that may be interpreted in different ways, it is those interpretations (p. 96) [ 57 ].

As stated in the introduction of this chapter, library and information science focuses on the interaction between individuals and information. In every area of LIS research, the connection of factors that lead to and influence this interaction is increasingly complex. Qualitative research searches for “ all aspects of that complexity on the grounds that they are essential to understanding the behavior of which they are a part ” (p. 241) [ 59 ]. Qualitative research designs can offer a more in‐depth analysis of library users, their needs, attitudes, and behaviors.

The use of mixed methods designs was found to be rather rare. While Hildreth and Aytac [ 43 ] found higher percentages of studies using combined methods in data analysis, our results are analogous to those shown by Fidel [ 60 ]. In fact, as in her study, only few of the articles analyzed referred to mixed methods research by name, a finding indicating that “ the concept has not yet gained recognition in LIS research ” (p. 268). Mixed methods research has become an established research approach in the social sciences as it minimizes the weaknesses of quantitative and qualitative research alone and allows researchers to investigate the phenomena more completely [ 58 ].

In conclusion, there is evidence that LIS researchers employ a large number and wide variety of research methodologies. Each research approach, strategy, and method has its advantages and limitations. If the aim of the study is to confirm hypotheses about phenomena or measure and analyze the causal relationships between variables, then quantitative methods might be used. If the research seeks to explore, understand, and explain phenomena then qualitative methods might be used. Researchers can consider the full range of possibilities and make their selection based on the philosophical assumptions they bring to the study, the research problem being addressed, their personal experiences, and the intended audience for the study [ 46 ].

Taking into consideration the increasing use of qualitative methods in LIS studies, an in‐depth analysis of papers using qualitative methods would be interesting. A future study in which the different research strategies and types of analysis used in qualitative methods will be presented and analyzed could help LIS practitioners understand the benefits of qualitative analysis.

Mixed methods used in LIS research papers could be analyzed in future studies in order to identify in which stages of a study, data collection, data analysis, and data interpretation, the mixing was applied and to reveal the types of mixing.

As far as it concerns the quantitative research methods, which predominate in LIS research, it would be interesting to identify systematic relations between more than two variables such as authors’ affiliation, topic, research strategies, etc. and to create homogeneous groups using multivariate data analysis techniques.

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Home > FACULTIES > Information & Media Studies (FIMS) > LIS-ETD

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Forecasting the future of library and information science and its sub-fields

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Published: 17 December 2020
Volume 126 , pages 1527–1551, ( 2021 )

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Forecasting is one of the methods applied in many studies in the library and information science (LIS) field for numerous purposes, from making predictions of the next Nobel laureates to potential technological developments. This study sought to draw a picture for the future of the LIS field and its sub-fields by analysing 97 years of publication and citation patterns. The core Web of Science indexes were used as the data source, and 123,742 articles were examined in-depth for time series analysis. The social network analysis method was used for sub-field classification. The field was divided into four sub-fields: (1) librarianship and law librarianship, (2) health information in LIS, (3) scientometrics and information retrieval and (4) management and information systems. The results of the study show that the LIS sub-fields are completely different from each other in terms of their publication and citation patterns, and all the sub-fields have different dynamics. Furthermore, the number of publications, references and citations will increase significantly in the future. It is expected that more scholars will work together. The future subjects of the LIS field show astonishing diversity from fake news to predatory journals, open government, e-learning and electronic health records. However, the findings prove that publish or perish culture will shape the field. Therefore, it is important to go beyond numbers. It can only be achieved by understanding publication and citation patterns of the field and developing research policies accordingly.

How to design bibliometric research: an overview and a framework proposal

The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis

The journal coverage of web of science and scopus: a comparative analysis.

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Introduction

Price ( 1963 p. 19, 1974 , p. 166), predicted more than half a century ago that if the exponential growth of big science continued, we could have two scientists for each person and dog in the population in the future, and we could have one million academic journals by the 2000s. Today, an average of 2.3% of worldwide gross national product is devoted to research and development activities (World Bank 2018 ), and 8.5 out of every 1000 workers is employed as a researcher (Organisation for Economic Co-operation and Development 2020 ). The current total number of active journals published worldwide is 380,299 ( ULRICHSWEB Global Serials Directory 2020 ), and at least the 73,299,923 articles have been published since Price published Little Science, Big Science in 1963. Footnote 1 One of Price’s biggest concerns was that if the growth of big science continued in this way, there would be no scientist who would be able to read every paper ( 1974 , p. 165). Even though we have not reached the number of journals estimated by Price, scientific outputs have still been increasing rapidly, and science is more difficult to follow than ever. In fact, the 90% of the research papers are never cited, and 50% of published research papers are never read by anyone else than the authors, reviewers and editors (Tripathy and Tripathy 2017 , p. 198).

One of the most important problems caused by big science is the inequality of scientific practices in various fields. Big science requires large budgets, diverse research groups with numerous staff members and big laboratories. The high costs of big science create a continuous interplay between the status system, which depends on honour and esteem, and class (Merton 1968 , p. 57). According to Allison and Stewart ( 1974 , p. 599), several publications and citations are affected by this inequality. One of the problems that creates this inequality is disciplinary differences: authors’ productivity depends on their work discipline, popularity and experience (Allison 1980 ; Merton 1968 ). Even today, big science provides a cumulative advantage for some scientists and disciplines. This cumulative advantage, in turn, affects the distribution of science funds (Bol et al. 2018 ) and other scientific career decisions (Petersen and Penner 2014 ). Scientific rewards are much more unequally distributed than other well-being outcomes (Xie 2014 , p. 810). For these reasons, the general characteristics of each discipline should be understood, and decisions should be made according to these characteristics to be able to make the right decisions in research evaluations.

Through the examination of the development of the LIS field, the same inequality can be seen. Over the years, studies have revealed that although the field is relatively small in the social sciences, it has several sub-fields, and the characteristics of these sub-fields are different from each other in terms of publication and citation patterns, authorship structures, production frequencies, etc. (Åström 2010 ; Moya-Anegón et al. 2006 ; White and McCain 1998 ). Besides, the development of sub-fields is directly affected by time and trends. For example, the number of articles written using terms such as ‘information technology’, ‘social network analysis’ or ‘citations’ has increased in recent years, but traditional librarianship topics such as librarianship, archiving or cataloguing have shown a decreasing trend (Larivière et al. 2012 , pp. 1006–1009). While this can be advantageous for some sub-fields, it negatively affects the visibility of more traditional fields and causes an unequal distribution of funds and resources.

The main aim of this study is to determine the sub-fields of the LIS field, reveal the potentials of these fields and make predictions of each sub-field. This will highlight the different scientific practices within the same discipline, which must then be taken into consideration when making decisions. The research questions are as follows:

What is the current structure of the LIS field and its sub-fields? Is there a significant difference between the sub-fields and publication/citation patterns?

Based on a 10-year forecast using the publication information produced in the LIS field, what size increase might be expected in the number of future publications?

Is it possible to predict the number of future citations? What are the citation potentials of the sub-fields?

How will the number of references cited in LIS papers change in the future?

Will the co-authorship patterns in the LIS field change in the future?

Are the quantitative predictions consistent, and do they provide valid insights for the future?

What are the emerging topics of the LIS field? Is it possible to predict future topics of LIS?

Literature review

The literature review is organized into two main parts. The first part presents the subject distribution of papers published in the LIS field which use time series analyses. In the second part, various studies using time series analysis in scholarly communication and research evaluation fields are summarized. The explanation about the use of time series analysis is given in the Methodology section.

Time series analysis studies in LIS

Time series analysis has been applied in the LIS literature to provide forecasts on four different sub-topics: Bibliometrics, health sciences, management and social media. To define main application areas of time series analysis in the field of LIS, 452 papers published in LIS and indexed in Web of Science were evaluated. Footnote 2 (see Fig. 1 ).

Most used keywords of the time series analysis studies in LIS (The sunburst graph was created by using Flourish Studio ( https://app.flourish.studio/ ). Keyword occurrences were calculated by using VOSviewer. Before the calculation, the keyword standardization process was conducted.)

An article by Bates et al. ( 1999 ) is the most cited paper with its 768 citations in the dataset, which includes publications indexed in Web of Science’s Information Science and Library Science category. The article evaluated the impact of computerised physician order entries to reduce the number of medication errors. The authors used prospective time series analysis to calculate the effectiveness of computerised systems for medications. As a result, it is found that computerised systems resulted in a large decrease in medication errors. The second-most cited paper (372 citations) evaluated time series data for online product reviews to understand the effects of word of mouth on online shopping (Li and Hitt 2008 ). The third-most cited article (283 citations) was written by the founder of CiteSpace and his colleagues (Chen et al. 2010 ). The authors used time series analysis to introduce a new multi-perspective co-citation analysis method for information science literature. The most-cited articles from three different sub-topics prove the subject diversity of publications which used time series analysis methods and techniques.

The bibliometric studies using time series analysis are focused on research evaluations, bibliometric indicators and scientometric visualisations. These studies have sought to reveal the relation between early citations and cumulative advantage (Adams 2005 ), evaluate the effectiveness of monetary support systems (Tonta 2018 ), understand the citation trajectories of Nobel prize winners in economics (Bjork et al. 2014 ), visualise or discover the intellectual structure of disciplines (Ma 2012 ) or events (Clausen and Wormell 2001 ), analyse the evolution of research topics (Wu et al. 2014 ), predict citation counts (Abrishami and Aliakbary 2019 ), observe the effects of science policy changes on the number of publications (Baskurt 2011 ), forecast research activities (Bildosola et al. 2017 ), detect emerging/leading papers (Iwami et al. 2014 ) and evaluate research metrics (Liu and Rousseau 2008 ; Ye and Rousseau 2008 ). The time series analysis techniques have been used in bibliometric studies since the early 1990s, and it is still one of the preferred methods in the literature. The main reason for this choice might be explained by the policymaking mission of research evaluations. Following the impact of research policy changes or detecting number of future citations provide important findings to the policymakers to enhance evaluation processes.

Time series analyses have also been used in the papers on health information. In recent years, the studies in health information have focused on evaluating electronic health records, predicting health risks (Perrote et al. 2015 ), optimising drug-drug interaction alert rules using electronic health records (Simpao et al. 2015 ), understanding information-seeking behaviours on health subjects (Huerta et al. 2016 ) and monitoring mental health discussions on Twitter (McClellan et al. 2017 ). The whole world has witnessed how long- and short-term predictions on health issues important during COVID-19 times. It is expected to see a publication explosion in this field in the future. Studies that make predictions on various issues related to the COVID-19 have started to be published in the literature (e.g. Jiang et al. 2020 ; Salgotra et al. 2020 ). Although there are many “unknown unknowns” exists about the virus, time series analysis is likely to be more popular among policymakers by providing a range of scenarios (Grogan 2020 ).

Economics and management sub-subjects of LIS field are also conducted research by using time series analysis. The papers have focused on telecommunication infrastructure and its relations to economic growth/activity (Cronin et al. 1991 ; Dutta 2001 ), disseminating economic census data (Zeisset 1998 ) and early detection of an economic bubble (Dmitriev et al. 2017 ). The last subject category, social media, can be accepted as a part of management subject. During the social media age, the predictions on big data (Niu et al. 2017 ; Saboo et al. 2016 ), social media analyses (Luo and Zhang 2013 ; Zhang et al. 2019 ), word of mouth (Li Hitt 2008 ) and election analyses on Twitter (Conway et al. 2015 ) are some of the important research topics.

The thematic diversity of LIS studies that have used time series analyses demonstrates that this is an essential method for scholars working in this field and is not limited to forecasting. In this study, the main aim of using a time series analysis was to make predictions about research outputs for the LIS field.

Prediction types in the field of scholarly communication and bibliometrics

Forecasting the future is one of the most frequently discussed subjects in bibliometrics and research evaluation studies. Predictions are often made to estimate Nobel Prize Laureates by considering publication and citation patterns. The Web of Science group has provided this well-known prediction mechanism for Nobelists since 2002 (Bourke-Waite 2019 ). Since 1970, millions of indexed publications and citations to these papers have been evaluated and estimations made. Until 2019, 50 Nobel prize winners who were on the list of citation laureates won the Nobel Prize. Of these, 29 researchers received the prize within 2 years of being nominated. Besides the Web of Science Group, there have been other numerous papers published in the literature to predict Nobel Prize winners (e.g., Ashton and Oppenheim 1978 ; Claes and De Ceuster 2013 ; Siegel 2019 ); however, Gingras and Wallace ( 2010 ) warned against the limits of bibliometric tools for predicting Nobel Prize winners due to the rapid growth of disciplines and the halo effect.

Another important area of predictive research is estimating the future number of publications and citations using different tools, techniques and perspectives. Leydesdorff ( 1990 ) sought to estimate the national performance of EEC (European Economic Community) countries and the US using time series analysis models. He found that it is possible to predict the following year’s publication statistics. In Rousseau ( 1994 ) proposed a double exponential model for first citation processes. He aimed to find a model for first citations, and he suggested two models to predict the total number of articles in a fixed group that would ever be cited. In Burrell ( 2003 ) developed the theory of stochastic models to predict the future citation patterns of individual papers. He found that expected citation count was a linear function of the current number, thus proving the idiom ‘success breeds success’.

Chen ( 2012 ) proposed a theoretical and computational model to predict future citations using three metrics: modularity change rate, cluster linkage and centrality divergence. The results indicate that the model could successfully predict future citations. Also, authors’ collaboration statistics and the number of references were found to be good predictors of global citations.

From the citation perspective, Abbasi et al. ( 2011 ) created a model to identify the effects of co-authorship networks on scholars’ performance. As a result, they recommended using researchers’ networks to predict scholars’ future performance. Tahamtan et al. ( 2016 ) reviewed the literature and presented 28 factors affecting the number of citations, these factors were then sorted into three main categories: paper-related factors (such as quality of papers, document type, etc.), journal-related factors (such as the impact factor or journal’s language) and author-related factors. The authors indicated that it is possible to predict the frequency of citations by considering these factors. Similarly, Chakraborty et al. ( 2014 ) developed a two-stage prediction model that produced better results for highly cited papers, and the authors suggested using this model to predict seminal papers in the scientific fields. The authors indicated that although the publication’s authors and venue are crucial for gathering citations, the features related to the papers’ content are more effective for long-term citation predictions. Another study on estimating the factors affecting the number of citations received by articles published in 12 crime psychology journals showed that author impact might be a more powerful predictor of how many times an article is cited than the venue (journal) of publication (Walters 2006 ).

Brody et al. ( 2006 ) examined the relationship between the number of early downloads and the number of citations received for the publications on Arxiv. The study showed that there was a correlation between early downloads and citation impact. Besides, the longer the period for which downloads were counted, the higher the correlation between downloads and citation impact. The authors concluded that the 2 year citation impact should be estimated using 6 months of download statistics.

One of the most recent studies on citation data and forecasting investigated whether the number of volumes that the journals published affected the impact factors of the journals (Zhang 2020 ). The results showed that if the increase of volumes is consistent and significant, a decrease of impact factors is unlikely.

Unlike the other studies mentioned above, some of the studies in the literature did not aim to estimate the number of citations using different statistical data but rather to predict future technologies using citation data. Small ( 2006 ) proposed using clustering, mapping and string formation to track and predict growth areas in science. Érdi et al. ( 2013 ) developed a new model to detect new technological hot spots by clustering patent citation data. Similarly, the Bass and ARIMA models, which are time series analysis models, were utilised to forecast development trends based on patent data (You et al. 2017 ). Kwon and Geum ( 2020 ) indicated that promising inventions can be identified by considering the number of backward citations as the link with previous knowledge. All these studies demonstrate that time series analysis can not only be used to predict the number of outputs in the literature but also to forecast technological developments.

Considering the number of forecasting studies in the literature, predictions provide important findings for scholars, policymakers and managers working in LIS and its sub-fields. Through these findings, it is possible to develop policies, identify the problematic practices and measure the effects of policy changes.

Methodology

Data structure.

To achieve the aims of the study, an advanced search of the Web of Science core indexes (SCI, SSCI and A&HCI) was conducted on 12 December 2019 using the search string WC = ( “Information science and Library Science” ) AND LA = ( English ) AND PY = (1921–2018) AND DT = ( article ). Although the Information Science and Library Science category is only indexed in SSCI, up to 5000 articles were indexed in SCI and A&HCI but not SSCI. Therefore, all three core indexes were included in the study to cover all studies in the field.

The oldest paper within the author’s subscription limits was from 1921, so that year became the starting point. Since the research was carried out before the end of 2019, the year 2019 was excluded from the scope of the research to avoid manipulation of the data and findings. However, the publication and citation data for 2019 were used to validate the success of the predictions made in this study. Also, only articles written in the English language were considered to avoid manipulation due to document type or language differences.

A total of 123,742 articles were analysed and evaluated within the context of this study. The metadata of all articles was downloaded as tab-delimited text using the Web of Science exporting features. A total of 248 different .txt files were downloaded because of the download limits of Web of Science (500 records per download). Then, all the .txt files were combined using the command prompt. Footnote 3 After creating one data file, a deep data cleaning and unification process was conducted. The main characteristics of the dataset are shown in Fig. 2 .

The main characteristics of the dataset.

The articles in the dataset were published in 174 different journals. To answer the research questions, the dataset was divided into four different sub-fields using social network analysis and clustering methods.

Clustering and determination of LIS sub-fields

Two different networks were created for subject clustering. One was a co-cited journal network and the other was a co-occurrence of keywords network. The creation phases of the networks were:

Co-cited journals The VOSviewer visualisation tool was used to create a co-citation network. Before creating the network, the names of the cited journals were standardised. During the standardisation process, different variations of journal names (e.g., Libr Trends, Lib Trends and Library Trends) and title changes (e.g., American Documentation, JASIS and JASIS&T) were considered. All journal names were unified. As a result, 537,227 sources were listed in our dataset. The limit for the minimum number of citations for a source was set at 20; 11,253 sources met this threshold. The co-citation network shown in Fig. 1 presents the top 1000 co-cited journals in the network.

Co-occurrence network The same standardisation process was used to unify the terms that appeared in the title, abstract and keyword fields. The standardisation process included unification of singular/plural words, abbreviations, noun phrases and synonyms. All keywords and the full counting method were selected to create the co-occurrence network. A total of 71,389 keywords were determined, and 8123 of these appeared at least five times in the etwork. The first 1000 terms are shown in Fig. 3 .

Clustering for journals in the dataset (networks of co-cited journals and keyword co-occurrence)

The main reason for creating two different network maps was to cross-validate the subject distribution of the dataset. Based on the clustering results, five clusters were determined for each network map. The clusters determined by most-occurred keywords were parallel with the co-cited journal network. It provided the opportunity to verify the accuracy of the classification. For both networks, the purple clusters were considered to be part of the green cluster. Therefore, the main subjects were classified into four main clusters for our study: librarianship and law librarianship (traditional library studies), health information in LIS , scientometrics and information retrieval and management and information systems .

Although some authors have argued that the journal citation reports (JCR) subject classification is problematic because it covers management information system (MIS) journals, which are different from other sub-fields (Larivière et al. 2012 , p. 999; Ni and Sugimoto 2011 ), our classification results for this field align with previous studies in the literature (e.g., Moya-Anegón et al. 2006 ; Ni and Sugimoto 2011 ; Tseng and Tsay 2013 ) that the field is generally divided into four sub-fields: information science (including information retrieval and information seeking), library science (practical and research-oriented), MIS and scientometrics. In this study, we also added health information to these classifications.

The main limitation of the classification used in this study was the journal-based approach. Some problems were determined for the journals which publish papers on two or more different topics. For example, the journal Health Information and Libraries was classified into the librarianship and law librarianship cluster by co-cited journal analysis, however, the main subject field of the journal is health libraries (Overview - Health Information and Libraries Journal 2020 ). To avoid that kind of problems, an expert control mechanism was conducted and content information from the articles published in that journal was used to decide the journal’s main focus. Additionally, if a journal was not listed in the network map, the same process was applied. For example, African Journal of Library Archives and Information Science was classified into the librarianship and law librarianship cluster using this method. The distribution of the articles into classes is shown in Fig. 4 .

Distribution of journals into subject clusters

Each of the subject fields has different features even though they are all in the same subject category—LIS. Therefore, it is important to understand the structures of these sub-fields and their potentials. Although the librarianship and law librarianship category contains up to 50% of the articles, it is the field with the lowest citation rate. Furthermore, collaboration is more common for health information in the LIS literature. To understand the differences between the sub-fields, the Kruskal-Wallis test was conducted. The test showed that:

The sub-categories of the articles significantly affect the number of publications that the articles cite ( H [3] = 17951.379, p < 0.001),

The sub-categories of the articles significantly affect the number of times an article is cited ( H [3] = 19807.543, p < 0.001) and

The sub-categories of the articles significantly affect the number of authors per paper ( H [3] = 20557.826, p < 0.001).

The test results demonstrate that even if the study focused on a specific category, the sub-fields of that category could have different structures, and thus, evaluations must consider these differences.

Time series analysis and time series forecasting

Many systems that we use today produce time-based data, which can be used to make various inferences. By using the data produced as a result of observations or experiments, problems with the system can be revealed, and predictions can be made about the future. The systematic approach to answering mathematical and statistical questions posed by time correlations is called time series analysis (Shumway and Stoffer 2006 , p. 1). This method of analysis has been used in various fields, from economics to geographical sciences, and it has a wide range of applications. The literature review section summarized different variations of time series analyses in the LIS literature to achieve different aims.

Forecasting is one method of time series analysis and is used to provide the t + 1 value of future time by evaluating the t number of available observations (Box et al. 2008 , p. 2). The forecasting process includes seven phases: (1) problem definition, (2) data collection, (3) data analysis, (4) model selection and fitting, (5) model validation, (6) forecasting and model deployment and (7) monitoring forecasting model performance (Montgomery et al. 2008 , p. 12). SPSS Statistics 23 (IBM) was used to conduct the model selection, fitting, validation, deployment and monitoring phases of this study.

There are different types of time series data, and this must be considered when choosing the analysis method. The well-known data types in time series analyses are trend data, seasonal data and cyclical variations. As seen in Fig. 2 , our dataset shows a linear trend, and thus the analyses were conducted to predict the future of this trend. The only exception for our data was the citations. Any publication requires a certain period to gather citations, and this period varies from discipline to discipline. The decrease in the number of citations over the last 8 years (Fig. 2 ) indicates that the half-life of citations in the LIS field is 8.3 (Incites Journal Citation Reports 2018 ). To prevent this decline from adversely affecting the results of the forecasting, only citation data up to 2010 were used. Thus, time series forecasting was applied using the period from 1921 to 2010.

Unusual events, disturbances or errors that might affect time series data are known as outliers (Box et al. 2008 , p. 536). There are different methods to remove outliers from the data or to normalise the data to provide strong predictions. Removing or normalising citation data was vital for this study because there were too many extreme values, and without processing the data to remove outliers, it would have been impossible to provide a powerful forecast for research outputs in the LIS field. To achieve this aim, median scores of the number of references and the number of citations per year were used to normalise the data. Additionally, autocorrelation and partial autocorrelation plots were created ( Appendix ).

The results of the forecasting analyses are presented in this section according to the number of publications, number of citations, number of references and number of authors per title.

Number of publications

As shown in Fig. 5 , it is predicted that the number of publications in the LIS field will increase in the future. The average number of English language articles published per year in these 97 years was 1262; however, 50% of these articles were published in the last 20 years. Footnote 4 Thus, an increasing publication pattern can be easily seen in Graph 1 in Fig. 5 (all LIS fields). Forecasting the number of publications for the whole LIS literature produced significant results [ Ljung Box Q (18) = 30.286, df = 18, p = 0.035, ARIMA (0, 1, 0) = 0.539, SE = 0.162, p = 0.001], and according to the results, 3974 publications were predicted for 2019 and 4632 for 2027.

Forecasting for number of publications

Because the expected number of articles for 2019 was estimated at 3974, and most of the articles published in 2019 are indexed in the Web of Science, it was possible to compare the forecast to the actual number of publications in 2019. A total of 4412 English language articles were published in 2019 and indexed before October 2020. Footnote 5 This shows that the number of publications will likely increase beyond the prediction, as that many articles are not expected until 2024 in the time series analysis. However, this number is still within the limits of the upper confidence level. If we follow the upper confidence level of the forecast to estimate the near future, there may be 6069 published articles in 2028. This means that if the upper confidence levels are actualised, a total of 52,807 articles could be published between 2019 and 2028.

Although the forecasting tests for sub-fields produced meaningful results, the data were not sufficient to make predictions. It is possible to follow the data from the trend lines and Ljung-box scores. Results of the analysis suggest that increases are expected in the number of publications that will be produced in all sub-fields. This is evidenced by the fact that the forecasts and the actual numbers are quite similar (see Table 1 ), indicating that estimating the number of publications in the LIS field and its sub-fields is possible using time series analysis.

Number of citations

Approximately 17% of the articles published in the LIS field have received 80% (1,209,824) of the citations for the whole literature. These statistics are important in terms of showing the existence of core articles in the LIS field. It is important to note that some publications receive numerous citations while others do not. Fig. 6 shows the distribution of citations received by sub-fields.

Distribution of citations according to sub-fields

Analysis of the dataset shows that two articles received 10,000 citations. These articles were classified into the sub-fields of management and information systems and health information in LIS. The citation potentials are different for each category. For example, papers published in the sub-field of management and information systems are more likely to be cited than those published in the sub-field of librarianship and law librarianship. One of the main features of citation data is their skewness (Bornmann and Leydesdorff 2017 ), and my dataset was no exception. This skewness makes it difficult to produce accurate forecasts for the number of citations in the future.

In addition to the skewness of citation data, other problems are literature obsolescence and citation half-lives. Since the cited half-life of the LIS field is 8 years, it is not possible to make an accurate prediction using data from the last 8 years. For this reason, forecasting only covered the years 1921–2010, and the last 8 years were excluded.

Fig. 7 presents the forecasting results which show that the most consistent prediction could be obtained by analysing the entire discipline. However, for the field-based analyses, the predictions did not produce meaningful results. The results indicate that half of the publications could be cited 20 or more times per year in the future. Considering that the median number of citations currently is 10 per year, this prediction of a major increase in citation counts is possible. However, it is estimated that the number of citations received in the LIS field might exceed 100,000. If we assume the same upper confidence level as we did for the number of publications, the upper confidence for the total number of citations is estimated to be 141,000. Since the distribution of median values does not offer a linear trend for sub-fields, it is difficult to predict which sub-fields will receive more citations. Furthermore, the half-life may be different for each sub-field. This is one of the factors that makes forecasting difficult. Considering all these factors, future analyses might produce more meaningful results.

Forecasting for citations

Number of references per paper

While the number of references that could be cited in publications was more limited in the past, with the increase in the number of publications, there has also been a significant increase in the number of references made in studies. It is possible to monitor this increase from the trendlines in Fig. 8 . The forecast predicts that a total of 300,000 references will be listed in the LIS literature in 2028. Half of the publications are expected to cite at least 63 sources. In 2018, this number was 47. The tests for forecasting produced significant results, and upper and lower confidence level scores were very close, indicating the accuracy/consistency of the future prediction.

Forecasting of the number of references

Despite the success in forecasting the future number of references, it is difficult to make a similar forecast for the sub-fields because of the differences between the fields and the skewness of the reference/citation data. Although they are in the same main subject category, the citation patterns are different for each sub-field. The average number of references per article is 15 (median = 21) in the field of librarianship and law librarianship, 26 (median = 21) in scientometrics and information retrieval, 30 (median = 26) in health information in LIS and 42 (median = 37) in the management and information systems fields.

Forecasting author collaborations

The average number of authors per paper in the LIS literature is two, and the median is one. Thus, scholars in the LIS field generally prefer to work alone. However, health information in LIS is the most collaborative sub-field of LIS literature. The article entitled ‘Academic domains as political battlegrounds: A global enquiry by 99 academics in the fields of education and technology’ Footnote 6 . is the most collaborative paper with 99 authors. The article is classified as part of the librarianship and law librarianship sub-field in our dataset. The main statistics for authorship patterns are shown in Table 2 .

The forecast results show that the average number of authors per paper is three. In the next 10 years, this number is expected to increase to 3.6. Considering the trendline over the past 97 years, this expected result is reasonable. Fig. 9 presents the forecasts for collaboration patterns in the LIS literature.

Forecasting of collaboration patterns

Possibility of consistent forecasting in the publish or perish world

The analyses above demonstrate the difficulty of predicting research outputs. Every year, the number of publications increases. Since no regular trend can be seen in this increase in the number of publications, any predictions we make today are minimum values for the future. Table 1 presents one example of this. All three graphs in Fig. 10 show the estimated increase per year in comparison with the previous period. The periods are determined by considering the years that had increases in the number of publications.

Forecasts by different periods

Figure 10 demonstrates that the number of publications does not have a regular trend. Thus, there is the possibility that no prediction will accurately forecast the number of future publications. If the trend until 1950 had continued to today, the number of publications in the LIS literature today would be 37,049 (30% of today’s actual number). If the data from 1970 were used, the number would be 76,612 (61% of today’s actual number), and if the data from 2000 were used, the number would be 117,336 (94% of today’s actual number). While it is possible to say that forecasts in recent years have been more accurate, that is, the publication trends have been similar in recent years, the unpredictability should be expected to continue regardless of any changes in research performance evaluation systems. Besides, it should be kept in mind that the number of publications may be indirectly affected by unexpected emerging issues such as COVID-19 that significantly affect the publishing patterns of the authors.

It is difficult to estimate the total number of citations using the data up to 1970 because of the cumulative nature of citations. However, predictions using data up to 2000 produced forecasts that are close to reality. Using data up to 1970, it was estimated that the average number of references per paper would be 67 in 2018. However, the data after 1970 changed the situation. Using the data until 2000, the estimated average number of references per paper in 2018 was 22, while the actual average number of references in 2018 was 51. Thus, the number of references in publications have increased far beyond the predictions made using more recent data.

Forecasting the research subjects

The findings confirm that the entire LIS field will face many more publications in the future with the spread of publish or perish culture. Therefore, the key to following the developments in LIS is to go beyond numbers. Although it is difficult to forecast the potential future of LIS subjects by using just numbers, making inferences by looking at the emerging subjects in recent years is possible. Figure 11 shows the most-used keywords of the papers published in the last two years in the LIS field. Footnote 7

Emerging subjects of the LIS field (Flourish Studio was used to create the radial tree)

Figure 11 shows a network of keywords that includes five clusters. The four clusters are parallel with the classification of this study. However, a new cluster named “COVID-19” has been added to the LIS literature as expected. The emerging subjects of each sub-field are:

COVID-19 All the countries have been fighting with COVID-19 since December 2019. According to WHO’s COVID-19 Global Research Database ( Global Research on Coronavirus Disease ( COVID- 19) 2020 ) a total of 123,959 publications were published from the day of the outbreak to November 7, 2020. The subject is also popular in the LIS field. Social media, fact-checking, governmental responsibilities during the pandemic such as political communication, transparency and participation, digital journalism and fake news are the important subjects of LIS field recently. The cluster proves the importance of LIS research focusing on open and correct information all over the world during the pandemic.

Bibliometrics and information retrieval The keywords of this cluster show that bibliometrics and information retrieval issues converge to each other with the developments of computational techniques. Machine learning, text mining, topic modelling and sentiment analyses are used for bibliometric studies such as content-based citation analyses and digital humanities. Also, scholarly communication subjects like peer-review, societal impact, incentives, predatory journals, language (multilingualism) and rankings are important keywords of this cluster. As indicated in the literature review part, predictions are still important for this sub-field.

Librarianship and law librarianship The effects of COVID-19 is also observed in this cluster (e.g. e-learning, e-resources). Information literacy plays a vital role among researchers, students and the public during COVID-19 times. Therefore, traditional librarianship subjects will be important to solve information problems of individuals in the future. Besides, digitization and preservation of archival materials are the other popular subjects of the cluster.

Health information in LIS Many studies in this sub-field focus on disadvantaged groups in recent years. Studies on inequality, refugees and genders can be evaluated in this content. Also, public access to health information, health communication and electronic health records are popular subjects and related to COVID-19 pandemic.

Discussion and conclusion

The study suggested a forecasting mechanism for research outputs in the LIS field. The main aim of the study was to inform scholars and policymakers about the future of research in this field. Nowadays, articles are often only read by a few people (Eveleth 2014 ; Simkin and Roychowdhury 2015 ; Tripathy and Tripathy 2017 ), and the main purpose of publishing is to achieve a numerical advantage rather than further the development of science. Although many researchers have emphasised that the current system should change, there have not yet been any concrete changes.

First, we revealed that publishing, citation and collaboration patterns differ between the sub-fields in the LIS literature. It is a well-known fact that apples and oranges are incomparable in research evaluations (Johnes and Johnes 1992 ); however, this study shows that it is also difficult to compare apples to each other because there are different types of apples (e.g., red, granny smith, honeycrisp, etc.). According to the results of the study more articles are published in traditional librarianship journals, and these journals tend to be cited less than others in the field. Articles published in the management dimension of the LIS field have greater citation potential than other sub-fields. This explains why management journals tend to have the highest impact factor in JCR among the LIS journals. This study shows the sub-field differences in LIS, and any evaluations based on categories should consider the sub-fields and their different characteristics.

The findings of this study indicate the number of publications and citations will continue to increase each year unless there is a change in research evaluation systems. This could lead to an uncontrollable mass of publications in the LIS field. The upper confidence levels estimated by the forecasting model produced in this study were already realised in 2019, demonstrating that this increase will be huge. However, it is difficult to forecast the future of sub-fields because the publication trends in sub-fields differ greatly from the general framework. If the existing systems continue, the inequality between LIS sub-fields will continue to grow. The meaning of following the current research evaluation systems is that the production of papers will continue to increase, and some of the sub-fields will not be able to benefit from future opportunities due to their disadvantages. For this reason, decision-makers and managers must consider field- and time-based differences in their research evaluation tasks.

One of the important results revealed in this study is the predicted increase in the number of publications, citations and references. Given that evaluations are made using citation data, the growing amount of data will make future evaluations more difficult. For this reason, supporting programmes such as the Initiative for Open Citations, which aims to promote the unrestricted availability of scholarly citation data, may also be useful for managing data in the future.

The results show that a lot of papers which have long reference lists will be produced, they will cite each other, more authors will work together to write papers. However, their contents and levels will be different from each other. Many of the studies have predicted that publishing will change in the future as a consequence of these differences. For example, Priem ( 2013 ) claimed that publishing forms, reward systems, measurement tools and peer-review systems will soon change. Similarly, Waldrop ( 2008 ) and Kendall ( 2015 ) stated that open science will be the new norm and that we will experience many changes to authorship and research evaluation systems in the next years. The predictions for the future of the publishing system is also the subject of the LIS field. This study proves the astonishing diversity of research subjects of the LIS field and tries to show the importance of looking beyond numbers.

The search was conducted on 7 July 2020 using the term PY = (1963–2020) in Web of Science’s core indexes: social sciences citation index (SCI), social sciences citation index (SSCI), Arts and humanities citation index (A&HCI), Emerging sources citation index (ESCI), Conference proceedings citation index (CPCI) and Book citation index (BKCI).

To access papers on/using time series analyses, the search string TS=(“time series” OR “forecasting analys*s” OR ARIMA OR “Exponential smoothing”) AND WC=(“Information science & library science”) was used. The search was conducted on 15 May 2020 using the Web of Science core indexes.

The text files were combined into a single file using the following steps: (1) open command prompt, (2) enter the folder, (3) use the code >> copy *.txt join.txt .

Although half of the articles were published in the last 20 years, using the entire past provides advantages for time series analyses using linear data (Jones 1964 , p. 47). The rate of increase in the number of publications over the years is one of the important factors for the success of the forecast. To provide accuracy on forecasts, the entire 97-year period was used for prediction.

A total of 137 articles were identified as early access. These articles might be covered by volumes/issues published in 2020. The total number of articles excluding early access articles was 4275.

https://journals.sagepub.com/doi/full/10.1177/0266666916646415 .

An advanced search was conducted on 5 November 2020 using the search string WC= ( “Information Science and Library Science” ) AND PY = (2019–2020) to gather the publication data for the last two years. All Web of Science indexes including ESCI, CPCI and BKCI were included to be able to cover more papers. Articles, reviews and proceedings were considered. A total of 13,856 papers were evaluated to analyze the emerging subjects of the field.

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Acknowledgements

This research was supported by a research grant from the Polish National Agency for Scientific Exchange, NAWA Poland (PPN/ULM/2019/1/00062). I would like to thank Emanuel Kulczycki, Güleda Doğan, Ola Swatek and the anonymous peer-reviewers for their meticulous reading of the paper and their invaluable suggestions.

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Taşkın, Z. Forecasting the future of library and information science and its sub-fields. Scientometrics 126 , 1527–1551 (2021). https://doi.org/10.1007/s11192-020-03800-2

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Global Knowledge, Memory and Communication

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Article publication date: 14 June 2022

Issue publication date: 9 January 2024

The study aims to present an insight into the research landscape of Library and Information Science (LIS) by India using a bibliometric visualization tool. The study analyses the research growth and trends, highly cited articles, productive publication titles, institutional and country collaboration.

Design/methodology/approach

The data were downloaded from the Web of Science Core Collection for a period of 20 years and analysed through VOSviewer, a data visualization software.

The results indicate that the overall annual contributions are increasing, although with uneven and slow growth from 2001 to 2014. However, the highest contributions and impact is witnessed over the past few years. All the top 10 cited papers are related to the area of information processing and management. The visualization technique made it clear that the area of research has made a transition from traditional concepts of library and information to novel ones involving big data, machine learning, altmetrics, etc. Also, the Indian Institute of Technology System, the Council of Scientific and Industrial Research and the Indian Institute of Management System have made the highest contributions. Furthermore, India shares maximum collaborations with the USA, followed by England and China.

Research limitations/implications

The findings of this study would help readers to gain understanding about the contribution of India for the development of the LIS. It would also help researchers to identify the hotspots and left out areas of research in the Indian context that require further investigation, thus would help in policy decisions and future research. Furthermore, researchers will be sensitized about the network visualizations that can also help them to get connected with the peers. The study can also help the journals to recognize the trending topics, which will provide the researchers with the opportunities to work on the same. Funding agencies can also be benefitted by the findings of the current study as they will be informed about the research areas which need to be funded.

Originality/value

There are not many research studies that highlight the research trends in the area of LIS from India and visualize the collaboration among institutions and countries. The study tries to showcase the research trends and collaborative frameworks in the field of LIS in terms of network visualization.

Bibliometrics
Data visualization
Research output-India
Library and Information Science research
Network visualization
Scientometrics
Research trends

Acknowledgements

Conflict of interest: There is no potential conflict of interest in the research.

Gupta, S. and Gul, S. (2024), "Tracking the research trends in the library and information science: a case study of India", Global Knowledge, Memory and Communication , Vol. 73 No. 1/2, pp. 202-218. https://doi.org/10.1108/GKMC-11-2021-0184

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Introduction to Library and Information Science

(2 reviews)

Reed Hepler, College of Southern Idaho

David Horalek, College of Southern Idaho

Publisher: College of Southern Idaho Pressbooks Network (CSI)

Language: English

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Reviewed by Kathy Evans, Reference & Archive Librarian, Shenandoah University on 11/10/23

Comprehensiveness rating: 5 see less

This textbook is logically organized, with distinctive chapters covering essential practices of librarianship. Hepler and Horalek do not offer an index in this introductory text. The authors define key concepts within the text, and those words are conveniently bolded and offer a "pop-out" definition. Unfortunately, these concepts are not in a glossary of terms or a helpful index. However, the text is searchable as an eBook.

Content Accuracy rating: 3

The text reads accurately in regards to librarianship. Some wording in the texts indicates bias. For example, the authors describe OCLC as a monopoly. Which is arguably true, but is it necessary to state that? The authors mention "publisher's whims." Whims? Another word may be more appropriate. Curiously, there is no mention of the ancient Library of Alexandria in Chapter 2 – History of Libraries.

Relevance/Longevity rating: 5

Overall, the text is straightforward and relevant to the subject. Updates should be relatively easy, given the organization and format of the information.

Clarity rating: 4

Current terms may help clarify the different aspects of librarianship and library services. Some sections are wordy and lack confidence in the subject discussed, while others seem almost rushed.

Consistency rating: 4

The text is consistent in terms of terminology and framework. As mentioned under clarity, more current descriptions of library services could be added to the text to clarify the terminology used.

Modularity rating: 5

The authors do a good job organizing the sections into readable chunks of information.

Organization/Structure/Flow rating: 5

The authors organized the textbook logically.

Interface rating: 5

The interface is easy to navigate. The self-check modules at the end of each section are helpful, albeit clunky, to use.

Grammatical Errors rating: 3

The text is wordy in the delivery of the material covered. Some language seems too familiar when presenting the information. Several punctuation errors are apparent.

Cultural Relevance rating: 5

The authors address the importance of diversity, inclusion, and equity in library collections.

Introduction to Library and Information Science could be a helpful textbook with some added proofreading and revisions.

Reviewed by Taylor Tharpe, Research & Digital Services Librarian, Longwood University on 7/18/23

Comprehensiveness rating: 4 see less

In Part I of the textbook, the author offers consistent definitions of certain terms, such as data, knowledge, and information. The author does a great job of providing helpful resources and information to go hand-in-hand with each chapter/section. However, some of the material that is questioned in the interactive quizzes are not mentioned in that particular section.

Content Accuracy rating: 5

I noticed no bias while reading this textbook. All information is presented in an accurate and unbiased manner.

The majority of the content was relevant and up to date.

Clarity rating: 5

This textbook is written in accessible prose and provides a disclaimer and instructions for the interactive features that accompany each section/chapter.

Consistency rating: 5

The textbook is consistent in terms of terminology and framework.

Textbook is broken into three different parts, that can be separated to support different units of a course or class.

The topics presented are organized in an understandable manner. They flow together nicely.

Interface rating: 4

Pictures and graphs could use some formatting work as the some of the captions aren't directly under the image, but I think this just depends on how you are viewing the textbook. The online version of the textbook is much more user-friendly than the PDF version.

Grammatical Errors rating: 2

This textbook makes many grammatical errors. This includes capitalization, sentence structure, spelling, misusing, etc. I counted numerous errors throughout the entire text.

The author touches on the subject of demographics and knowing how to serve patrons regardless of ethnic group, race, gender, sexual orientation, etc. The textbook also has a section on DEI and how important it is for libraries to acquire materials and hold events that meet the DEI initiative.

The author focuses more on the application of skills associated with working within the library field, rather than just lecturing about library theory. However, the author also mentions using ChatGPT, which doesn't seem very reliable to me.

Data, Information, and Knowledge
History of Libraries
Library Services
Acquisitions
Collection Development
Classficiation and Cataloging
Facilities and Funding
Circulation
Reference Librarianship
Preservation
Intellectual Freedom
Digitial Initiatives and Library 2.0
Representation in the Library
Patron Services
Reader's Advisory
The Modern Library Experience

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About the book.

This book explores the history, present, and future of library science, both in theory and in practice. It examines the place of the librarian as arbiter of information access in a constantly-changing and modernizing global community.

About the Contributors

Reed Hepler , College of Southern Idaho

David Horalek , College of Southern Idaho

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Baldwin, J., & Pinfield, S. (2018). The UK Scholarly Communication Licence: Attempting to Cut through the Gordian Knot of the Complexities of Funder Mandates, Publisher Embargoes and Researcher Caution in Achieving Open Access. Publications, 6(3), Article 3. https://doi.org/10.3390/publications6030031

Butler, L.-A., Matthias, L., Simard, M.-A., Mongeon, P., & Haustein, S. (2023). The oligopoly’s shift to open access: How the big five academic publishers profit from article processing charges. Quantitative Science Studies, 4(4), 778–799. https://doi.org/10.1162/qss_a_00272

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Fontúrbel, F. E., & Vizentin-Bugoni, J. (2021). A Paywall Coming Down, Another Being Erected: Open Access Article Processing Charges (APC) may Prevent Some Researchers from Publishing in Leading Journals. The Bulletin of the Ecological Society of America, 102(1), e01791. https://doi.org/10.1002/bes2.1791

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Published: 14 May 2024

2023 summer warmth unparalleled over the past 2,000 years

Jan Esper ORCID: orcid.org/0000-0003-3919-014X 1 , 2 ,
Max Torbenson ORCID: orcid.org/0000-0003-2720-2238 1 &
Ulf Büntgen 2 , 3 , 4

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Climate change
Palaeoclimate

Including an exceptionally warm Northern Hemisphere (NH) summer 1 ,2 , 2023 has been reported as the hottest year on record 3-5 . Contextualizing recent anthropogenic warming against past natural variability is nontrivial, however, because the sparse 19 th century meteorological records tend to be too warm 6 . Here, we combine observed and reconstructed June-August (JJA) surface air temperatures to show that 2023 was the warmest NH extra-tropical summer over the past 2000 years exceeding the 95% confidence range of natural climate variability by more than half a degree Celsius. Comparison of the 2023 JJA warming against the coldest reconstructed summer in 536 CE reveals a maximum range of pre-Anthropocene-to-2023 temperatures of 3.93°C. Although 2023 is consistent with a greenhouse gases-induced warming trend 7 that is amplified by an unfolding El Niño event 8 , this extreme emphasizes the urgency to implement international agreements for carbon emission reduction.

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Department of Geography, Johannes Gutenberg University, Mainz, Germany

Jan Esper & Max Torbenson

Global Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic

Jan Esper & Ulf Büntgen

Department of Geography, University of Cambridge, Cambridge, United Kingdom

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Esper, J., Torbenson, M. & Büntgen, U. 2023 summer warmth unparalleled over the past 2,000 years. Nature (2024). https://doi.org/10.1038/s41586-024-07512-y

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Cultural Relativity and Acceptance of Embryonic Stem Cell Research

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There is a debate about the ethical implications of using human embryos in stem cell research, which can be influenced by cultural, moral, and social values. This paper argues for an adaptable framework to accommodate diverse cultural and religious perspectives. By using an adaptive ethics model, research protections can reflect various populations and foster growth in stem cell research possibilities.

INTRODUCTION

Stem cell research combines biology, medicine, and technology, promising to alter health care and the understanding of human development. Yet, ethical contention exists because of individuals’ perceptions of using human embryos based on their various cultural, moral, and social values. While these disagreements concerning policy, use, and general acceptance have prompted the development of an international ethics policy, such a uniform approach can overlook the nuanced ethical landscapes between cultures. With diverse viewpoints in public health, a single global policy, especially one reflecting Western ethics or the ethics prevalent in high-income countries, is impractical. This paper argues for a culturally sensitive, adaptable framework for the use of embryonic stem cells. Stem cell policy should accommodate varying ethical viewpoints and promote an effective global dialogue. With an extension of an ethics model that can adapt to various cultures, we recommend localized guidelines that reflect the moral views of the people those guidelines serve.

Stem cells, characterized by their unique ability to differentiate into various cell types, enable the repair or replacement of damaged tissues. Two primary types of stem cells are somatic stem cells (adult stem cells) and embryonic stem cells. Adult stem cells exist in developed tissues and maintain the body’s repair processes. [1] Embryonic stem cells (ESC) are remarkably pluripotent or versatile, making them valuable in research. [2] However, the use of ESCs has sparked ethics debates. Considering the potential of embryonic stem cells, research guidelines are essential. The International Society for Stem Cell Research (ISSCR) provides international stem cell research guidelines. They call for “public conversations touching on the scientific significance as well as the societal and ethical issues raised by ESC research.” [3] The ISSCR also publishes updates about culturing human embryos 14 days post fertilization, suggesting local policies and regulations should continue to evolve as ESC research develops. [4] Like the ISSCR, which calls for local law and policy to adapt to developing stem cell research given cultural acceptance, this paper highlights the importance of local social factors such as religion and culture.

I. Global Cultural Perspective of Embryonic Stem Cells

Views on ESCs vary throughout the world. Some countries readily embrace stem cell research and therapies, while others have stricter regulations due to ethical concerns surrounding embryonic stem cells and when an embryo becomes entitled to moral consideration. The philosophical issue of when the “someone” begins to be a human after fertilization, in the morally relevant sense, [5] impacts when an embryo becomes not just worthy of protection but morally entitled to it. The process of creating embryonic stem cell lines involves the destruction of the embryos for research. [6] Consequently, global engagement in ESC research depends on social-cultural acceptability.

a. US and Rights-Based Cultures

In the United States, attitudes toward stem cell therapies are diverse. The ethics and social approaches, which value individualism, [7] trigger debates regarding the destruction of human embryos, creating a complex regulatory environment. For example, the 1996 Dickey-Wicker Amendment prohibited federal funding for the creation of embryos for research and the destruction of embryos for “more than allowed for research on fetuses in utero.” [8] Following suit, in 2001, the Bush Administration heavily restricted stem cell lines for research. However, the Stem Cell Research Enhancement Act of 2005 was proposed to help develop ESC research but was ultimately vetoed. [9] Under the Obama administration, in 2009, an executive order lifted restrictions allowing for more development in this field. [10] The flux of research capacity and funding parallels the different cultural perceptions of human dignity of the embryo and how it is socially presented within the country’s research culture. [11]

b. Ubuntu and Collective Cultures

African bioethics differs from Western individualism because of the different traditions and values. African traditions, as described by individuals from South Africa and supported by some studies in other African countries, including Ghana and Kenya, follow the African moral philosophies of Ubuntu or Botho and Ukama , which “advocates for a form of wholeness that comes through one’s relationship and connectedness with other people in the society,” [12] making autonomy a socially collective concept. In this context, for the community to act autonomously, individuals would come together to decide what is best for the collective. Thus, stem cell research would require examining the value of the research to society as a whole and the use of the embryos as a collective societal resource. If society views the source as part of the collective whole, and opposes using stem cells, compromising the cultural values to pursue research may cause social detachment and stunt research growth. [13] Based on local culture and moral philosophy, the permissibility of stem cell research depends on how embryo, stem cell, and cell line therapies relate to the community as a whole . Ubuntu is the expression of humanness, with the person’s identity drawn from the “’I am because we are’” value. [14] The decision in a collectivistic culture becomes one born of cultural context, and individual decisions give deference to others in the society.

Consent differs in cultures where thought and moral philosophy are based on a collective paradigm. So, applying Western bioethical concepts is unrealistic. For one, Africa is a diverse continent with many countries with different belief systems, access to health care, and reliance on traditional or Western medicines. Where traditional medicine is the primary treatment, the “’restrictive focus on biomedically-related bioethics’” [is] problematic in African contexts because it neglects bioethical issues raised by traditional systems.” [15] No single approach applies in all areas or contexts. Rather than evaluating the permissibility of ESC research according to Western concepts such as the four principles approach, different ethics approaches should prevail.

Another consideration is the socio-economic standing of countries. In parts of South Africa, researchers have not focused heavily on contributing to the stem cell discourse, either because it is not considered health care or a health science priority or because resources are unavailable. [16] Each country’s priorities differ given different social, political, and economic factors. In South Africa, for instance, areas such as maternal mortality, non-communicable diseases, telemedicine, and the strength of health systems need improvement and require more focus. [17] Stem cell research could benefit the population, but it also could divert resources from basic medical care. Researchers in South Africa adhere to the National Health Act and Medicines Control Act in South Africa and international guidelines; however, the Act is not strictly enforced, and there is no clear legislation for research conduct or ethical guidelines. [18]

Some parts of Africa condemn stem cell research. For example, 98.2 percent of the Tunisian population is Muslim. [19] Tunisia does not permit stem cell research because of moral conflict with a Fatwa. Religion heavily saturates the regulation and direction of research. [20] Stem cell use became permissible for reproductive purposes only recently, with tight restrictions preventing cells from being used in any research other than procedures concerning ART/IVF. Their use is conditioned on consent, and available only to married couples. [21] The community's receptiveness to stem cell research depends on including communitarian African ethics.

c. Asia

Some Asian countries also have a collective model of ethics and decision making. [22] In China, the ethics model promotes a sincere respect for life or human dignity, [23] based on protective medicine. This model, influenced by Traditional Chinese Medicine (TCM), [24] recognizes Qi as the vital energy delivered via the meridians of the body; it connects illness to body systems, the body’s entire constitution, and the universe for a holistic bond of nature, health, and quality of life. [25] Following a protective ethics model, and traditional customs of wholeness, investment in stem cell research is heavily desired for its applications in regenerative therapies, disease modeling, and protective medicines. In a survey of medical students and healthcare practitioners, 30.8 percent considered stem cell research morally unacceptable while 63.5 percent accepted medical research using human embryonic stem cells. Of these individuals, 89.9 percent supported increased funding for stem cell research. [26] The scientific community might not reflect the overall population. From 1997 to 2019, China spent a total of $576 million (USD) on stem cell research at 8,050 stem cell programs, increased published presence from 0.6 percent to 14.01 percent of total global stem cell publications as of 2014, and made significant strides in cell-based therapies for various medical conditions. [27] However, while China has made substantial investments in stem cell research and achieved notable progress in clinical applications, concerns linger regarding ethical oversight and transparency. [28] For example, the China Biosecurity Law, promoted by the National Health Commission and China Hospital Association, attempted to mitigate risks by introducing an institutional review board (IRB) in the regulatory bodies. 5800 IRBs registered with the Chinese Clinical Trial Registry since 2021. [29] However, issues still need to be addressed in implementing effective IRB review and approval procedures.

The substantial government funding and focus on scientific advancement have sometimes overshadowed considerations of regional cultures, ethnic minorities, and individual perspectives, particularly evident during the one-child policy era. As government policy adapts to promote public stability, such as the change from the one-child to the two-child policy, [30] research ethics should also adapt to ensure respect for the values of its represented peoples.

Japan is also relatively supportive of stem cell research and therapies. Japan has a more transparent regulatory framework, allowing for faster approval of regenerative medicine products, which has led to several advanced clinical trials and therapies. [31] South Korea is also actively engaged in stem cell research and has a history of breakthroughs in cloning and embryonic stem cells. [32] However, the field is controversial, and there are issues of scientific integrity. For example, the Korean FDA fast-tracked products for approval, [33] and in another instance, the oocyte source was unclear and possibly violated ethical standards. [34] Trust is important in research, as it builds collaborative foundations between colleagues, trial participant comfort, open-mindedness for complicated and sensitive discussions, and supports regulatory procedures for stakeholders. There is a need to respect the culture’s interest, engagement, and for research and clinical trials to be transparent and have ethical oversight to promote global research discourse and trust.

d. Middle East

Countries in the Middle East have varying degrees of acceptance of or restrictions to policies related to using embryonic stem cells due to cultural and religious influences. Saudi Arabia has made significant contributions to stem cell research, and conducts research based on international guidelines for ethical conduct and under strict adherence to guidelines in accordance with Islamic principles. Specifically, the Saudi government and people require ESC research to adhere to Sharia law. In addition to umbilical and placental stem cells, [35] Saudi Arabia permits the use of embryonic stem cells as long as they come from miscarriages, therapeutic abortions permissible by Sharia law, or are left over from in vitro fertilization and donated to research. [36] Laws and ethical guidelines for stem cell research allow the development of research institutions such as the King Abdullah International Medical Research Center, which has a cord blood bank and a stem cell registry with nearly 10,000 donors. [37] Such volume and acceptance are due to the ethical ‘permissibility’ of the donor sources, which do not conflict with religious pillars. However, some researchers err on the side of caution, choosing not to use embryos or fetal tissue as they feel it is unethical to do so. [38]

Jordan has a positive research ethics culture. [39] However, there is a significant issue of lack of trust in researchers, with 45.23 percent (38.66 percent agreeing and 6.57 percent strongly agreeing) of Jordanians holding a low level of trust in researchers, compared to 81.34 percent of Jordanians agreeing that they feel safe to participate in a research trial. [40] Safety testifies to the feeling of confidence that adequate measures are in place to protect participants from harm, whereas trust in researchers could represent the confidence in researchers to act in the participants’ best interests, adhere to ethical guidelines, provide accurate information, and respect participants’ rights and dignity. One method to improve trust would be to address communication issues relevant to ESC. Legislation surrounding stem cell research has adopted specific language, especially concerning clarification “between ‘stem cells’ and ‘embryonic stem cells’” in translation. [41] Furthermore, legislation “mandates the creation of a national committee… laying out specific regulations for stem-cell banking in accordance with international standards.” [42] This broad regulation opens the door for future global engagement and maintains transparency. However, these regulations may also constrain the influence of research direction, pace, and accessibility of research outcomes.

e. Europe

In the European Union (EU), ethics is also principle-based, but the principles of autonomy, dignity, integrity, and vulnerability are interconnected. [43] As such, the opportunity for cohesion and concessions between individuals’ thoughts and ideals allows for a more adaptable ethics model due to the flexible principles that relate to the human experience The EU has put forth a framework in its Convention for the Protection of Human Rights and Dignity of the Human Being allowing member states to take different approaches. Each European state applies these principles to its specific conventions, leading to or reflecting different acceptance levels of stem cell research. [44]

For example, in Germany, Lebenzusammenhang , or the coherence of life, references integrity in the unity of human culture. Namely, the personal sphere “should not be subject to external intervention.” [45] Stem cell interventions could affect this concept of bodily completeness, leading to heavy restrictions. Under the Grundgesetz, human dignity and the right to life with physical integrity are paramount. [46] The Embryo Protection Act of 1991 made producing cell lines illegal. Cell lines can be imported if approved by the Central Ethics Commission for Stem Cell Research only if they were derived before May 2007. [47] Stem cell research respects the integrity of life for the embryo with heavy specifications and intense oversight. This is vastly different in Finland, where the regulatory bodies find research more permissible in IVF excess, but only up to 14 days after fertilization. [48] Spain’s approach differs still, with a comprehensive regulatory framework. [49] Thus, research regulation can be culture-specific due to variations in applied principles. Diverse cultures call for various approaches to ethical permissibility. [50] Only an adaptive-deliberative model can address the cultural constructions of self and achieve positive, culturally sensitive stem cell research practices. [51]

II. Religious Perspectives on ESC

Embryonic stem cell sources are the main consideration within religious contexts. While individuals may not regard their own religious texts as authoritative or factual, religion can shape their foundations or perspectives.

The Qur'an states:

“And indeed We created man from a quintessence of clay. Then We placed within him a small quantity of nutfa (sperm to fertilize) in a safe place. Then We have fashioned the nutfa into an ‘alaqa (clinging clot or cell cluster), then We developed the ‘alaqa into mudgha (a lump of flesh), and We made mudgha into bones, and clothed the bones with flesh, then We brought it into being as a new creation. So Blessed is Allah, the Best of Creators.” [52]

Many scholars of Islam estimate the time of soul installment, marked by the angel breathing in the soul to bring the individual into creation, as 120 days from conception. [53] Personhood begins at this point, and the value of life would prohibit research or experimentation that could harm the individual. If the fetus is more than 120 days old, the time ensoulment is interpreted to occur according to Islamic law, abortion is no longer permissible. [54] There are a few opposing opinions about early embryos in Islamic traditions. According to some Islamic theologians, there is no ensoulment of the early embryo, which is the source of stem cells for ESC research. [55]

In Buddhism, the stance on stem cell research is not settled. The main tenets, the prohibition against harming or destroying others (ahimsa) and the pursuit of knowledge (prajña) and compassion (karuna), leave Buddhist scholars and communities divided. [56] Some scholars argue stem cell research is in accordance with the Buddhist tenet of seeking knowledge and ending human suffering. Others feel it violates the principle of not harming others. Finding the balance between these two points relies on the karmic burden of Buddhist morality. In trying to prevent ahimsa towards the embryo, Buddhist scholars suggest that to comply with Buddhist tenets, research cannot be done as the embryo has personhood at the moment of conception and would reincarnate immediately, harming the individual's ability to build their karmic burden. [57] On the other hand, the Bodhisattvas, those considered to be on the path to enlightenment or Nirvana, have given organs and flesh to others to help alleviate grieving and to benefit all. [58] Acceptance varies on applied beliefs and interpretations.

Catholicism does not support embryonic stem cell research, as it entails creation or destruction of human embryos. This destruction conflicts with the belief in the sanctity of life. For example, in the Old Testament, Genesis describes humanity as being created in God’s image and multiplying on the Earth, referencing the sacred rights to human conception and the purpose of development and life. In the Ten Commandments, the tenet that one should not kill has numerous interpretations where killing could mean murder or shedding of the sanctity of life, demonstrating the high value of human personhood. In other books, the theological conception of when life begins is interpreted as in utero, [59] highlighting the inviolability of life and its formation in vivo to make a religious point for accepting such research as relatively limited, if at all. [60] The Vatican has released ethical directives to help apply a theological basis to modern-day conflicts. The Magisterium of the Church states that “unless there is a moral certainty of not causing harm,” experimentation on fetuses, fertilized cells, stem cells, or embryos constitutes a crime. [61] Such procedures would not respect the human person who exists at these stages, according to Catholicism. Damages to the embryo are considered gravely immoral and illicit. [62] Although the Catholic Church officially opposes abortion, surveys demonstrate that many Catholic people hold pro-choice views, whether due to the context of conception, stage of pregnancy, threat to the mother’s life, or for other reasons, demonstrating that practicing members can also accept some but not all tenets. [63]

Some major Jewish denominations, such as the Reform, Conservative, and Reconstructionist movements, are open to supporting ESC use or research as long as it is for saving a life. [64] Within Judaism, the Talmud, or study, gives personhood to the child at birth and emphasizes that life does not begin at conception: [65]

“If she is found pregnant, until the fortieth day it is mere fluid,” [66]

Whereas most religions prioritize the status of human embryos, the Halakah (Jewish religious law) states that to save one life, most other religious laws can be ignored because it is in pursuit of preservation. [67] Stem cell research is accepted due to application of these religious laws.

We recognize that all religions contain subsets and sects. The variety of environmental and cultural differences within religious groups requires further analysis to respect the flexibility of religious thoughts and practices. We make no presumptions that all cultures require notions of autonomy or morality as under the common morality theory , which asserts a set of universal moral norms that all individuals share provides moral reasoning and guides ethical decisions. [68] We only wish to show that the interaction with morality varies between cultures and countries.

III. A Flexible Ethical Approach

The plurality of different moral approaches described above demonstrates that there can be no universally acceptable uniform law for ESC on a global scale. Instead of developing one standard, flexible ethical applications must be continued. We recommend local guidelines that incorporate important cultural and ethical priorities.

While the Declaration of Helsinki is more relevant to people in clinical trials receiving ESC products, in keeping with the tradition of protections for research subjects, consent of the donor is an ethical requirement for ESC donation in many jurisdictions including the US, Canada, and Europe. [69] The Declaration of Helsinki provides a reference point for regulatory standards and could potentially be used as a universal baseline for obtaining consent prior to gamete or embryo donation.

For instance, in Columbia University’s egg donor program for stem cell research, donors followed standard screening protocols and “underwent counseling sessions that included information as to the purpose of oocyte donation for research, what the oocytes would be used for, the risks and benefits of donation, and process of oocyte stimulation” to ensure transparency for consent. [70] The program helped advance stem cell research and provided clear and safe research methods with paid participants. Though paid participation or covering costs of incidental expenses may not be socially acceptable in every culture or context, [71] and creating embryos for ESC research is illegal in many jurisdictions, Columbia’s program was effective because of the clear and honest communications with donors, IRBs, and related stakeholders. This example demonstrates that cultural acceptance of scientific research and of the idea that an egg or embryo does not have personhood is likely behind societal acceptance of donating eggs for ESC research. As noted, many countries do not permit the creation of embryos for research.

Proper communication and education regarding the process and purpose of stem cell research may bolster comprehension and garner more acceptance. “Given the sensitive subject material, a complete consent process can support voluntary participation through trust, understanding, and ethical norms from the cultures and morals participants value. This can be hard for researchers entering countries of different socioeconomic stability, with different languages and different societal values. [72]

An adequate moral foundation in medical ethics is derived from the cultural and religious basis that informs knowledge and actions. [73] Understanding local cultural and religious values and their impact on research could help researchers develop humility and promote inclusion.

IV. Concerns

Some may argue that if researchers all adhere to one ethics standard, protection will be satisfied across all borders, and the global public will trust researchers. However, defining what needs to be protected and how to define such research standards is very specific to the people to which standards are applied. We suggest that applying one uniform guide cannot accurately protect each individual because we all possess our own perceptions and interpretations of social values. [74] Therefore, the issue of not adjusting to the moral pluralism between peoples in applying one standard of ethics can be resolved by building out ethics models that can be adapted to different cultures and religions.

Other concerns include medical tourism, which may promote health inequities. [75] Some countries may develop and approve products derived from ESC research before others, compromising research ethics or drug approval processes. There are also concerns about the sale of unauthorized stem cell treatments, for example, those without FDA approval in the United States. Countries with robust research infrastructures may be tempted to attract medical tourists, and some customers will have false hopes based on aggressive publicity of unproven treatments. [76]

For example, in China, stem cell clinics can market to foreign clients who are not protected under the regulatory regimes. Companies employ a marketing strategy of “ethically friendly” therapies. Specifically, in the case of Beike, China’s leading stem cell tourism company and sprouting network, ethical oversight of administrators or health bureaus at one site has “the unintended consequence of shifting questionable activities to another node in Beike's diffuse network.” [77] In contrast, Jordan is aware of stem cell research’s potential abuse and its own status as a “health-care hub.” Jordan’s expanded regulations include preserving the interests of individuals in clinical trials and banning private companies from ESC research to preserve transparency and the integrity of research practices. [78]

The social priorities of the community are also a concern. The ISSCR explicitly states that guidelines “should be periodically revised to accommodate scientific advances, new challenges, and evolving social priorities.” [79] The adaptable ethics model extends this consideration further by addressing whether research is warranted given the varying degrees of socioeconomic conditions, political stability, and healthcare accessibilities and limitations. An ethical approach would require discussion about resource allocation and appropriate distribution of funds. [80]

While some religions emphasize the sanctity of life from conception, which may lead to public opposition to ESC research, others encourage ESC research due to its potential for healing and alleviating human pain. Many countries have special regulations that balance local views on embryonic personhood, the benefits of research as individual or societal goods, and the protection of human research subjects. To foster understanding and constructive dialogue, global policy frameworks should prioritize the protection of universal human rights, transparency, and informed consent. In addition to these foundational global policies, we recommend tailoring local guidelines to reflect the diverse cultural and religious perspectives of the populations they govern. Ethics models should be adapted to local populations to effectively establish research protections, growth, and possibilities of stem cell research.

For example, in countries with strong beliefs in the moral sanctity of embryos or heavy religious restrictions, an adaptive model can allow for discussion instead of immediate rejection. In countries with limited individual rights and voice in science policy, an adaptive model ensures cultural, moral, and religious views are taken into consideration, thereby building social inclusion. While this ethical consideration by the government may not give a complete voice to every individual, it will help balance policies and maintain the diverse perspectives of those it affects. Embracing an adaptive ethics model of ESC research promotes open-minded dialogue and respect for the importance of human belief and tradition. By actively engaging with cultural and religious values, researchers can better handle disagreements and promote ethical research practices that benefit each society.

This brief exploration of the religious and cultural differences that impact ESC research reveals the nuances of relative ethics and highlights a need for local policymakers to apply a more intense adaptive model.

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[5] Concerning the moral philosophies of stem cell research, our paper does not posit a personal moral stance nor delve into the “when” of human life begins. To read further about the philosophical debate, consider the following sources:

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[7] Socially, at its core, the Western approach to ethics is widely principle-based, autonomy being one of the key factors to ensure a fundamental respect for persons within research. For information regarding autonomy in research, see: Department of Health, Education, and Welfare, & National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (1978). The Belmont Report. Ethical principles and guidelines for the protection of human subjects of research.; For a more in-depth review of autonomy within the US, see: Beauchamp, T. L., & Childress, J. F. (1994). Principles of Biomedical Ethics . Oxford University Press.

[8] Sherley v. Sebelius , 644 F.3d 388 (D.C. Cir. 2011), citing 45 C.F.R. 46.204(b) and [42 U.S.C. § 289g(b)]. https://www.cadc.uscourts.gov/internet/opinions.nsf/6c690438a9b43dd685257a64004ebf99/$file/11-5241-1391178.pdf

[9] Stem Cell Research Enhancement Act of 2005, H. R. 810, 109 th Cong. (2001). https://www.govtrack.us/congress/bills/109/hr810/text ; Bush, G. W. (2006, July 19). Message to the House of Representatives . National Archives and Records Administration. https://georgewbush-whitehouse.archives.gov/news/releases/2006/07/20060719-5.html

[10] National Archives and Records Administration. (2009, March 9). Executive order 13505 -- removing barriers to responsible scientific research involving human stem cells . National Archives and Records Administration. https://obamawhitehouse.archives.gov/the-press-office/removing-barriers-responsible-scientific-research-involving-human-stem-cells

[11] Hurlbut, W. B. (2006). Science, Religion, and the Politics of Stem Cells. Social Research , 73 (3), 819–834. http://www.jstor.org/stable/40971854

[12] Akpa-Inyang, Francis & Chima, Sylvester. (2021). South African traditional values and beliefs regarding informed consent and limitations of the principle of respect for autonomy in African communities: a cross-cultural qualitative study. BMC Medical Ethics . 22. 10.1186/s12910-021-00678-4.

[13] Source for further reading: Tangwa G. B. (2007). Moral status of embryonic stem cells: perspective of an African villager. Bioethics , 21(8), 449–457. https://doi.org/10.1111/j.1467-8519.2007.00582.x , see also Mnisi, F. M. (2020). An African analysis based on ethics of Ubuntu - are human embryonic stem cell patents morally justifiable? African Insight , 49 (4).

[14] Jecker, N. S., & Atuire, C. (2021). Bioethics in Africa: A contextually enlightened analysis of three cases. Developing World Bioethics , 22 (2), 112–122. https://doi.org/10.1111/dewb.12324

[15] Jecker, N. S., & Atuire, C. (2021). Bioethics in Africa: A contextually enlightened analysis of three cases. Developing World Bioethics, 22(2), 112–122. https://doi.org/10.1111/dewb.12324

[16] Jackson, C.S., Pepper, M.S. Opportunities and barriers to establishing a cell therapy programme in South Africa. Stem Cell Res Ther 4 , 54 (2013). https://doi.org/10.1186/scrt204 ; Pew Research Center. (2014, May 1). Public health a major priority in African nations . Pew Research Center’s Global Attitudes Project. https://www.pewresearch.org/global/2014/05/01/public-health-a-major-priority-in-african-nations/

[17] Department of Health Republic of South Africa. (2021). Health Research Priorities (revised) for South Africa 2021-2024 . National Health Research Strategy. https://www.health.gov.za/wp-content/uploads/2022/05/National-Health-Research-Priorities-2021-2024.pdf

[18] Oosthuizen, H. (2013). Legal and Ethical Issues in Stem Cell Research in South Africa. In: Beran, R. (eds) Legal and Forensic Medicine. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32338-6_80 , see also: Gaobotse G (2018) Stem Cell Research in Africa: Legislation and Challenges. J Regen Med 7:1. doi: 10.4172/2325-9620.1000142

[19] United States Bureau of Citizenship and Immigration Services. (1998). Tunisia: Information on the status of Christian conversions in Tunisia . UNHCR Web Archive. https://webarchive.archive.unhcr.org/20230522142618/https://www.refworld.org/docid/3df0be9a2.html

[20] Gaobotse, G. (2018) Stem Cell Research in Africa: Legislation and Challenges. J Regen Med 7:1. doi: 10.4172/2325-9620.1000142

[21] Kooli, C. Review of assisted reproduction techniques, laws, and regulations in Muslim countries. Middle East Fertil Soc J 24 , 8 (2020). https://doi.org/10.1186/s43043-019-0011-0 ; Gaobotse, G. (2018) Stem Cell Research in Africa: Legislation and Challenges. J Regen Med 7:1. doi: 10.4172/2325-9620.1000142

[22] Pang M. C. (1999). Protective truthfulness: the Chinese way of safeguarding patients in informed treatment decisions. Journal of medical ethics , 25(3), 247–253. https://doi.org/10.1136/jme.25.3.247

[23] Wang, L., Wang, F., & Zhang, W. (2021). Bioethics in China’s biosecurity law: Forms, effects, and unsettled issues. Journal of law and the biosciences , 8(1). https://doi.org/10.1093/jlb/lsab019 https://academic.oup.com/jlb/article/8/1/lsab019/6299199

[24] Wang, Y., Xue, Y., & Guo, H. D. (2022). Intervention effects of traditional Chinese medicine on stem cell therapy of myocardial infarction. Frontiers in pharmacology , 13 , 1013740. https://doi.org/10.3389/fphar.2022.1013740

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[30] Chen, H., Wei, T., Wang, H. et al. Association of China’s two-child policy with changes in number of births and birth defects rate, 2008–2017. BMC Public Health 22 , 434 (2022). https://doi.org/10.1186/s12889-022-12839-0

[31] Azuma, K. Regulatory Landscape of Regenerative Medicine in Japan. Curr Stem Cell Rep 1 , 118–128 (2015). https://doi.org/10.1007/s40778-015-0012-6

[32] Harris, R. (2005, May 19). Researchers Report Advance in Stem Cell Production . NPR. https://www.npr.org/2005/05/19/4658967/researchers-report-advance-in-stem-cell-production

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[35] Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: interviews with researchers from Saudi Arabia. BMC medical ethics, 21(1), 35. https://doi.org/10.1186/s12910-020-00482-6

[36] Association for the Advancement of Blood and Biotherapies. https://www.aabb.org/regulatory-and-advocacy/regulatory-affairs/regulatory-for-cellular-therapies/international-competent-authorities/saudi-arabia

[37] Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: Interviews with researchers from Saudi Arabia. BMC medical ethics , 21 (1), 35. https://doi.org/10.1186/s12910-020-00482-6

[38] Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: Interviews with researchers from Saudi Arabia. BMC medical ethics , 21(1), 35. https://doi.org/10.1186/s12910-020-00482-6

Culturally, autonomy practices follow a relational autonomy approach based on a paternalistic deontological health care model. The adherence to strict international research policies and religious pillars within the regulatory environment is a great foundation for research ethics. However, there is a need to develop locally targeted ethics approaches for research (as called for in Alahmad, G., Aljohani, S., & Najjar, M. F. (2020). Ethical challenges regarding the use of stem cells: interviews with researchers from Saudi Arabia. BMC medical ethics, 21(1), 35. https://doi.org/10.1186/s12910-020-00482-6), this decision-making approach may help advise a research decision model. For more on the clinical cultural autonomy approaches, see: Alabdullah, Y. Y., Alzaid, E., Alsaad, S., Alamri, T., Alolayan, S. W., Bah, S., & Aljoudi, A. S. (2022). Autonomy and paternalism in Shared decision‐making in a Saudi Arabian tertiary hospital: A cross‐sectional study. Developing World Bioethics , 23 (3), 260–268. https://doi.org/10.1111/dewb.12355 ; Bukhari, A. A. (2017). Universal Principles of Bioethics and Patient Rights in Saudi Arabia (Doctoral dissertation, Duquesne University). https://dsc.duq.edu/etd/124; Ladha, S., Nakshawani, S. A., Alzaidy, A., & Tarab, B. (2023, October 26). Islam and Bioethics: What We All Need to Know . Columbia University School of Professional Studies. https://sps.columbia.edu/events/islam-and-bioethics-what-we-all-need-know

[39] Ababneh, M. A., Al-Azzam, S. I., Alzoubi, K., Rababa’h, A., & Al Demour, S. (2021). Understanding and attitudes of the Jordanian public about clinical research ethics. Research Ethics , 17 (2), 228-241. https://doi.org/10.1177/1747016120966779

[40] Ababneh, M. A., Al-Azzam, S. I., Alzoubi, K., Rababa’h, A., & Al Demour, S. (2021). Understanding and attitudes of the Jordanian public about clinical research ethics. Research Ethics , 17 (2), 228-241. https://doi.org/10.1177/1747016120966779

[41] Dajani, R. (2014). Jordan’s stem-cell law can guide the Middle East. Nature 510, 189. https://doi.org/10.1038/510189a

[42] Dajani, R. (2014). Jordan’s stem-cell law can guide the Middle East. Nature 510, 189. https://doi.org/10.1038/510189a

[43] The EU’s definition of autonomy relates to the capacity for creating ideas, moral insight, decisions, and actions without constraint, personal responsibility, and informed consent. However, the EU views autonomy as not completely able to protect individuals and depends on other principles, such as dignity, which “expresses the intrinsic worth and fundamental equality of all human beings.” Rendtorff, J.D., Kemp, P. (2019). Four Ethical Principles in European Bioethics and Biolaw: Autonomy, Dignity, Integrity and Vulnerability. In: Valdés, E., Lecaros, J. (eds) Biolaw and Policy in the Twenty-First Century. International Library of Ethics, Law, and the New Medicine, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-05903-3_3

[44] Council of Europe. Convention for the protection of Human Rights and Dignity of the Human Being with regard to the Application of Biology and Medicine: Convention on Human Rights and Biomedicine (ETS No. 164) https://www.coe.int/en/web/conventions/full-list?module=treaty-detail&treatynum=164 (forbidding the creation of embryos for research purposes only, and suggests embryos in vitro have protections.); Also see Drabiak-Syed B. K. (2013). New President, New Human Embryonic Stem Cell Research Policy: Comparative International Perspectives and Embryonic Stem Cell Research Laws in France. Biotechnology Law Report , 32 (6), 349–356. https://doi.org/10.1089/blr.2013.9865

[45] Rendtorff, J.D., Kemp, P. (2019). Four Ethical Principles in European Bioethics and Biolaw: Autonomy, Dignity, Integrity and Vulnerability. In: Valdés, E., Lecaros, J. (eds) Biolaw and Policy in the Twenty-First Century. International Library of Ethics, Law, and the New Medicine, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-05903-3_3

[46] Tomuschat, C., Currie, D. P., Kommers, D. P., & Kerr, R. (Trans.). (1949, May 23). Basic law for the Federal Republic of Germany. https://www.btg-bestellservice.de/pdf/80201000.pdf

[47] Regulation of Stem Cell Research in Germany . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-germany

[48] Regulation of Stem Cell Research in Finland . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-finland

[49] Regulation of Stem Cell Research in Spain . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-spain

[50] Some sources to consider regarding ethics models or regulatory oversights of other cultures not covered:

Kara MA. Applicability of the principle of respect for autonomy: the perspective of Turkey. J Med Ethics. 2007 Nov;33(11):627-30. doi: 10.1136/jme.2006.017400. PMID: 17971462; PMCID: PMC2598110.

Ugarte, O. N., & Acioly, M. A. (2014). The principle of autonomy in Brazil: one needs to discuss it ... Revista do Colegio Brasileiro de Cirurgioes , 41 (5), 374–377. https://doi.org/10.1590/0100-69912014005013

Bharadwaj, A., & Glasner, P. E. (2012). Local cells, global science: The rise of embryonic stem cell research in India . Routledge.

For further research on specific European countries regarding ethical and regulatory framework, we recommend this database: Regulation of Stem Cell Research in Europe . Eurostemcell. (2017, April 26). https://www.eurostemcell.org/regulation-stem-cell-research-europe

[51] Klitzman, R. (2006). Complications of culture in obtaining informed consent. The American Journal of Bioethics, 6(1), 20–21. https://doi.org/10.1080/15265160500394671 see also: Ekmekci, P. E., & Arda, B. (2017). Interculturalism and Informed Consent: Respecting Cultural Differences without Breaching Human Rights. Cultura (Iasi, Romania) , 14 (2), 159–172.; For why trust is important in research, see also: Gray, B., Hilder, J., Macdonald, L., Tester, R., Dowell, A., & Stubbe, M. (2017). Are research ethics guidelines culturally competent? Research Ethics , 13 (1), 23-41. https://doi.org/10.1177/1747016116650235

[52] The Qur'an (M. Khattab, Trans.). (1965). Al-Mu’minun, 23: 12-14. https://quran.com/23

[53] Lenfest, Y. (2017, December 8). Islam and the beginning of human life . Bill of Health. https://blog.petrieflom.law.harvard.edu/2017/12/08/islam-and-the-beginning-of-human-life/

[54] Aksoy, S. (2005). Making regulations and drawing up legislation in Islamic countries under conditions of uncertainty, with special reference to embryonic stem cell research. Journal of Medical Ethics , 31: 399-403.; see also: Mahmoud, Azza. "Islamic Bioethics: National Regulations and Guidelines of Human Stem Cell Research in the Muslim World." Master's thesis, Chapman University, 2022. https://doi.org/10.36837/ chapman.000386

[55] Rashid, R. (2022). When does Ensoulment occur in the Human Foetus. Journal of the British Islamic Medical Association , 12 (4). ISSN 2634 8071. https://www.jbima.com/wp-content/uploads/2023/01/2-Ethics-3_-Ensoulment_Rafaqat.pdf.

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[57] Jafari, M., Elahi, F., Ozyurt, S. & Wrigley, T. (2007). 4. Religious Perspectives on Embryonic Stem Cell Research. In K. Monroe, R. Miller & J. Tobis (Ed.), Fundamentals of the Stem Cell Debate: The Scientific, Religious, Ethical, and Political Issues (pp. 79-94). Berkeley: University of California Press. https://escholarship.org/content/qt9rj0k7s3/qt9rj0k7s3_noSplash_f9aca2e02c3777c7fb76ea768ba458f0.pdf https://doi.org/10.1525/9780520940994-005

[58] Lecso, P. A. (1991). The Bodhisattva Ideal and Organ Transplantation. Journal of Religion and Health , 30 (1), 35–41. http://www.jstor.org/stable/27510629 ; Bodhisattva, S. (n.d.). The Key of Becoming a Bodhisattva . A Guide to the Bodhisattva Way of Life. http://www.buddhism.org/Sutras/2/BodhisattvaWay.htm

[59] There is no explicit religious reference to when life begins or how to conduct research that interacts with the concept of life. However, these are relevant verses pertaining to how the fetus is viewed. (( King James Bible . (1999). Oxford University Press. (original work published 1769))

Jerimiah 1: 5 “Before I formed thee in the belly I knew thee; and before thou camest forth out of the womb I sanctified thee…”

In prophet Jerimiah’s insight, God set him apart as a person known before childbirth, a theme carried within the Psalm of David.

Psalm 139: 13-14 “…Thou hast covered me in my mother's womb. I will praise thee; for I am fearfully and wonderfully made…”

These verses demonstrate David’s respect for God as an entity that would know of all man’s thoughts and doings even before birth.

[60] It should be noted that abortion is not supported as well.

[61] The Vatican. (1987, February 22). Instruction on Respect for Human Life in Its Origin and on the Dignity of Procreation Replies to Certain Questions of the Day . Congregation For the Doctrine of the Faith. https://www.vatican.va/roman_curia/congregations/cfaith/documents/rc_con_cfaith_doc_19870222_respect-for-human-life_en.html

[62] The Vatican. (2000, August 25). Declaration On the Production and the Scientific and Therapeutic Use of Human Embryonic Stem Cells . Pontifical Academy for Life. https://www.vatican.va/roman_curia/pontifical_academies/acdlife/documents/rc_pa_acdlife_doc_20000824_cellule-staminali_en.html ; Ohara, N. (2003). Ethical Consideration of Experimentation Using Living Human Embryos: The Catholic Church’s Position on Human Embryonic Stem Cell Research and Human Cloning. Department of Obstetrics and Gynecology . Retrieved from https://article.imrpress.com/journal/CEOG/30/2-3/pii/2003018/77-81.pdf.

[63] Smith, G. A. (2022, May 23). Like Americans overall, Catholics vary in their abortion views, with regular mass attenders most opposed . Pew Research Center. https://www.pewresearch.org/short-reads/2022/05/23/like-americans-overall-catholics-vary-in-their-abortion-views-with-regular-mass-attenders-most-opposed/

[64] Rosner, F., & Reichman, E. (2002). Embryonic stem cell research in Jewish law. Journal of halacha and contemporary society , (43), 49–68.; Jafari, M., Elahi, F., Ozyurt, S. & Wrigley, T. (2007). 4. Religious Perspectives on Embryonic Stem Cell Research. In K. Monroe, R. Miller & J. Tobis (Ed.), Fundamentals of the Stem Cell Debate: The Scientific, Religious, Ethical, and Political Issues (pp. 79-94). Berkeley: University of California Press. https://escholarship.org/content/qt9rj0k7s3/qt9rj0k7s3_noSplash_f9aca2e02c3777c7fb76ea768ba458f0.pdf https://doi.org/10.1525/9780520940994-005

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Mifrah Hayath

SM Candidate Harvard Medical School, MS Biotechnology Johns Hopkins University

Olivia Bowers

MS Bioethics Columbia University (Disclosure: affiliated with Voices in Bioethics)

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Afrodite Malliari

1. Introduction

2. The role of theory in LIS research

3. Research strategies in LIS

3.2. Data collection and analysis

Table 1.

Table 2.

Table 3.

3.3. Results

Table 4.

Figure 1.

3.3.2. Research approach and methodology

Figure 2.

Table 5.

Table 6.

3.3.3. Methods of data analysis

Table 7.

3.4. Discussions and conclusions

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Forecasting the future of library and information science and its sub-fields

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Introduction

Literature review

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Prediction types in the field of scholarly communication and bibliometrics

Methodology

Clustering and determination of LIS sub-fields

Time series analysis and time series forecasting

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Number of references per paper

Forecasting author collaborations

Possibility of consistent forecasting in the publish or perish world

Forecasting the research subjects

Discussion and conclusion

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