thesis management data

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Data and your thesis

• Scholarly Communication
• Open Access
• Training, Outreach and Events

What is research data?

Research data are the evidence that underpins the answer to your research question and can support the findings or outputs of your research. Research data takes many different forms. They may include for example, statistics, digital images, sound recordings, films, transcripts of interviews, survey data, artworks, published texts or manuscripts, or fieldwork observations. The term 'data' is more familiar to researchers in Science, Technology, Engineering and Mathematics (STEM), but any outputs from research could be considered data. For example, Humanities, Arts and Social Sciences (HASS) researchers might create data in the form of presentations, spreadsheets, documents, images, works of art, or musical scores. The Research Data Management Team in the University Library aim to help you plan, create, organise, share, and look after your research materials, whatever form they take. For more information about the Research data Management Team, visit their website .

Data Management Plans

Research Data Management is a complex issue, but if done correctly from the start, could save you a lot of time and hassle when you are writing up your thesis. We advise all students to consider data management as early as possible and create a Data Management Plan (DMP). The Research Data Management Team offer help in creating your DMP and can offer advice and training on how to do this. There are some departments that have joined a pilot project to include Data Management Plans in the registration reviews of PhD students. As part of the pilot, students are asked to complete a brief Data Management Plan (DMP) and supervisors and assessors ensure that the student has thought about all the issues and their responses are reasonable. If your department is taking part in the pilot or would like to, see the Data Management Plans for Pilot for Cambridge PhD Students page. The Research Data Management Team will provide support for any students, supervisors or assessors that are in need.

Submitting your digital thesis and depositing your data

If you have created data that is connected to your thesis and the data is in a format separate to the thesis file itself, we recommend that you deposit it in the data repository and make it open access to improve discoverability. We will accept data that either does not contain third party copyright, or contains third party copyright that has been cleared and is data of the following types:

•     computer code written by the researcher
•     software written by the researcher
•     statistical data
•     raw data from experiments

If you have created a research output which is not one of those listed above, please contact us on the [email protected] address and we will advise whether you should deposit this with your thesis, or separately in the data repository. If you are ready to deposit your data in the data repository, please do so via symplectic elements. More information on how to deposit can be found on the Research Data Management pages . If you wish to cite your data in your thesis, we can arranged for placeholder DOIs to be created in the data repository before your thesis is submitted. For further information, please email:  [email protected]  

Third party copyright in your data

For an explanation of what is third party copyright, please see the OSC third party copyright page . If your data is based on, or contains third party copyright you will need to obtain clearance to make your data open access in the data repository. It is possible to apply a 12 month embargo to datasets while clearance is obtained if you need extra time to do this. However, if it is not possible to clear the third party copyrighted material, it is not possible to deposit your data in the data repository. In these cases, it might be preferable to deposit your data with your thesis instead, under controlled access, but this can be complicated if you wish to deposit the thesis itself under a different access level. Please email [email protected] with any queries and we can advise on the best solution.

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Research Data Management: Data Plan for your PhD

• Sensitive Data & Data Protection (GDPR)
• PhD DMP supervisors guide
• Support and Training

DMP for your PhD research

All first year post graduate researchers should complete a data management plan for their research and include it as part of their first three month review.  There is also a Blackboard course  Data Management Plans for Doctoral Students -  mandatory for all new doctoral students - to introduce you to research data management and help you complete the plan. Log into Blackboard using your university username and password.

A data management plan or DMP is a living document that helps you consider how you will organise your data, files, research notes and other supporting documentation throughout the length of the project.  The aim is to help you find these easily, keep them safe and have sufficient documentation to be able to re-use throughout your research and beyond.

You will need to complete a preliminary data management plan in your first three months, along with your Academic Needs Analysis.  Your DMP will continue to develop as your research progresses and you will need to update and review your DMP at every progression review. ( Code of Practice for Research Degree Candidature and Supervision, )

All researchers will have data. Data can be broadly defined as 'Material intended for analysis'.  This covers many forms and formats, and is not just about digital data.

For example, 

Art History - high resolution reproductions of photographs, notebook describing context

English literature - research notes on text, textual analysis

Engineering - experimental measurements on the physical properties of liquid metals

The University also has a definition for “Research Data” in its  Research Data Management Policy  that you should consider.

A PhD DMP template and guidance on how to complete your Data Management Plan is available ( see below ). All new doctoral students should complete the Data Management Plans for Doctoral Students module on Blackboard. Contact us if you need further information or have feedback via [email protected]

Guidance on depositing your research data at the end of your doctorate can be found on the Thesis Data Deposit guide. Please also see our depositing research data videos at  https://library.soton.ac.uk/researchdata/datasetvideos

Creating your DMP

• Introduction
• DMP and Project Overview
• About your Project Data
• Making Data Findable
• Making Data Accessible
• Making Data Reusable
• Making Data Secure
• Implementing the Plan
• Example Plans

What are data management plans? A data management plan is a document that describes:

• What data will be created
• What policies will apply to the data  
• Who will own and have access to the data
• What data management practices will be used 
• What facilities and equipment will be required 
• Who will be responsible for each of these activities

Your data management plan should be written specifically for the research that you will be doing.  Our template is a guide to help you identify the key areas that you need to consider, but not all sections will apply to everyone.  You may need to seek further guidance from your supervisor, colleagues in your department or other sources on best practice in your discipline.  We provide some details of guidance available in our training section and on our general research data management pages.

Each of the tabs looks at the different topics that can be included in a data management plan.  You can move through the tabs in any order.

Describing your Project

At the start of your data management plan (DMP) it is useful to include some basic information about the research you are planning to do.  This may already exist in other documents in more detail, but for the purposes of the DMP try to summarise in as few sentences as possible.

What policies will apply?

It is important that you think about who is funding your research and whether there are any requirements that you need to meet.  Are you funded by a UK Research Council? What policies do they have on research data - see  Funder Guidance .  What does our University Research Data Management policy  and Code for Conduct for Research state is required?

Does the type of data you will be creating, using, collecting mean that you have to meet certain legal conditions?  Will you be collecting any form of personal data, (see ICO Personal Data Definition ), special category data (see ICS Special Category definition ) or is it commercially sensitive?  For example, if you are involved in population health and clinical studies research data and records minimum retention could be 20-25 years for certain types of data - see the MRC Retention framework for research data and records  for further details. 

Do you need Ethics Approval?

Anyone who is dealing with human subjects or cultural heritage (see University policies ) will require to obtain ethics approval and this must be done prior to collecting any data.  Your DMP should inform what you say in your ethics application about how you will collect, store and re-use your data.  It is important that your DMP and your ethics application are in agreement and you provide your participants with the correct information. Once you receive your ethics approval, review your data management plan and update as necessary.

Reviewing your Data Management Plan

A DMP should be a living document and should be updated as your research develops.  It should be reviewed on a regular basis and good practice would encourage that the dates of review are included in the plan itself.  Use of a version table in any document can be helpful.

What data will be created?

In your data management plan you need to provide some detail about the material you will be collecting to support your research.  This should cover how you will collect notes, supporting documentation and bibliographic management as well as your primary data. Will all your data be held electronically or will you require to maintain a print notebook to collect your observations?

Are you using Secondary Data?

Not everyone has to collect their own data, it may already have been collected and made available.  This data is known as secondary data.  Some secondary data are freely available, but other data are released with terms and conditions that you need to meet.  In some cases this may influence where you can store and analyse the data.  You need to be aware of this as you plan the work you intend to do.

How are you collecting or creating your data?

How you collect or gather the material for your research will influence what you need to do to manage them. The way you do this may alter as your research progresses and you should update your plan as required. Will you be collecting data by observing, note-taking in an archive, carrying out experiments or a mixture of these? 

How much data are you likely to have?

Knowing how much data you might create is important as it will dictate where you can store your data and whether you need to ask for additional storage from iSolutions.  It is unlikely that you can say exactly what volume of data you might create, but you will have an idea of individual file sizes.  If you will be working with word, excel documents and a reference management software library then you are likely to be dealing with megabytes or gigabytes of data. If you will be collecting high resolution images then you may end up needing to store terabytes. Estimate as early as possible and if you think you may need additional space you should discuss this with your supervisor.

What formats will you be using?

A crucial factor in being able to share data is that it is in an open format or collected using disciplinary standard software that allow export to open formats.  Consider how open the format of your data will be when selecting the software, instruments, word processing packages that you use. See the Data formats section in  Introducing Research Data  Part III for points to consider.

Who will own the data?

If you have been sponsored by a research council, government, industry or commercial body the agreement you signed may cover ownership of the data that you create.  Being aware of this early is useful as it will influence what you are able to do when you come to writing papers, sharing and depositing your data when your finish. It may also impact on where you can store your data.  

How will you make your data findable?

Using standards to capture the essential metadata is a good way to help create data that will be easy to find.  It will also make preparing for deposit in the future more straightforward.  The Research Data Alliance has a helpful list of  disciplinary metadata  and use case examples.  You can make reference to these in your plan once you know what will be most appropriate to use.

Where will you store the data during your PhD?

Where you store your data will depend on things such as the type and size of data you are collecting.  Certain types of data, such as personal , special category data (formerly referred to as sensitive data) or commercially confidential data, will require to be stored more securely than others.  This type of data generally requires to be stored on University network drives that have additional protection and not on personal computers or cloud storage (for example, Office 365, One Drive). Where you are collecting less sensitive data your choice of storage is wider.  For all storage it should in a location with good back-up procedures in place. Consult iSolutions knowledge base  for further information.

How will you name your files and folders?

It can be helpful to think about creating a procedure on how you will name your files. This is a basic step where it is useful to consider how easy it will be to interpret the name in the future.  Abbreviations can be good, but ask yourself how someone else might understand the file name should you need to share it with them. What would make it easy to know what each file contains?  While it is possible to have quite longer file names this can cause problems when you zip files. 

How will you tell one version of a file from another?

How will you be able to tell whether you are dealing with the latest version of a file? How will you manage major versus minor changes?  What if you want to return to an earlier version?  Use the data management plan to investigate what would be the optimum method for you and establish a good procedure from the beginning.  Generally the use of 'draft', 'latest' or 'final' should be avoided.  Instead consider using the data (YYYY-MM-DD) or a version number, for example, v.1.0  where the nominal value increases with major changes and decimal for minor ones.  Adding a version table at the end of a document can also be helpful.

How can you share your data?

To make data accessible is not about doing something at the end of the project, but needs to be planned for from the beginning.  During your research you are likely to have colleagues or collaborators who will need to be able to access the data - how will you do this?  Will you need a collaborative space and if so what can you use?  Does it need to be is a protected location with restricted access due to the type of data you are using? By establishing good procedures on documentation, metadata collection, file-naming and using disciplinary standards this will assist you throughout your research, as well as helping at the end.

How do you handle personal, sensitive or commercially confidential data?

If the data you are collecting contains   personal ,  special category  data (formerly referred to as sensitive data) or commercially confidential data  then sharing or transferring the files needs to be carried out in a way that does not make the data vulnerable. Data should be anonymised or pseudo-anonymised as early as possible after collection, seek disciplinary guidance prior to collection. 

The medium of transfer must be secure and where necessary encryption should be used. You may want to consider one of the following:

There may be other software available and you should check if there is a standard in your discipline. 

Transferring data via USB or external drives is not recommended, but where required these should be encrypted. Avoid using email to send files and instead use our University SafeSend service.  This offers transfer of files up to 50GB and your files can be encrypted by ticking "Encrypt every file" when creating a new drop-off - see ' How secure is SaveSend'

What data do you need to keep and what do you need to destroy?

Not all the data from a project needs to be kept and the data you collect should be reviewed regularly.  The Digital Curation Centre (2014) guide  ' Five steps to decide what data to keep: a checklist for appraising research data v.1 ' may help you to decide what to retain. It is important that you retain or discard data in line with your ethics approval.

You also need to consider what data needs to be destroyed, how you will mark the data for destruction and when this needs to happen. Destroying paper based records is relatively easy through our confidential waste system.   Destroying digital data is less so as it may need to be done so that it cannot be forensically recovered. Guidance on destroying your data is available  or contact iSolutions for advice.

Why do you need to consider the long-term storage now?

At the end of your PhD you will be encouraged to share your data as openly as possible, and as closed as necessary. To do this safely consider what you need to do to enable your data to be accessible in the future.  Knowing where the best place to store your data may inform what you need to plan for in its creation or collection.  Are you aware of any disciplinary data repositories that hold similar data?  Examples are:

• Archaeology - Archaeology Data Service  
• ESRC - UK Data Archive
• STFC -  eData   
• NERC - data centres
• Biology - GenBank
• General repository - Zenodo

Investigate what requirements these repositories have on formats, documentation etc and incorporate these into your plan. Otherwise you should plan to deposit in the University Institutional Repository . 

There are currently no costs for depositing most dataset in our Institutional Repository unless the data requires specialist archive storage or is in excess of 1TB. External repositories may have charges for depositing data. 

Who will be creating the archive?

Generally as a PhD the job of drawing together your data into a dataset ready for deposit will fall to you as the researcher.  It is not the responsibility of your supervisor, although they may be able to advise on what needs to be done.  If you are part of a larger project there may be someone designated to curate the project data.  For further assistance contact [email protected] . 

How long should the data be kept?

This will depend on a number of factors.  Your funder may have a policy that requires the data to be held for a minimum of 10 years from last use.  If you are working in certain medical areas the data may need to be held for 25 years.  There may be some restrictions on how long you can retain personal data relating to Data Protection Act 2018 (GDPR).  Significant data that has been given a persistent identifier (DOI) will be kept permanently.

What documentation or additional information needs to accompany the data?

Keeping a record of what changes you have made, when data was collected, where data was collected from, observations, definitions of what has been collected are all crucial to allowing data to be used safely and with integrity. How do you plan to do this? How will you make sure that you can match up your notes with the files they refer to?  Some programming languages such as Python and R allow you to make notes in the files about what you are doing which is really helpful.  Where this is not an option then you will need to develop your own method to make sure that processes applied to the data are recorded and available to you to refer back to later.  Creating a register of your files by type using an excel spreadsheet may be worth considering, but it should be manageable and importantly kept up-to-date.

In order for data to be reusable it requires data provenance.  Data provenance is used to document where a piece of data comes from and the process and methodology by which it is produced. It is important to confirm the authenticity of data enabling trust, credibility and reproducibility. This is becoming increasingly important, especially in the eScience community where research is data intensive and often involves complex data transformations and procedures.

• Research Data Management and Sharing - Documentation The importance of systematically documenting your research data. more... less... From the Coursera Research Data Management and Sharing course https://www.coursera.org/learn/data-management

What restrictions will need to apply?

Not all data can be made openly available.  Some data may only be shared once a data sharing agreement has been signed, while other data may not be suitable for sharing.  Funding councils encourage all data to be as open as possible and as closed as necessary. Where will your data fit with this?  What agreements do you need to be able to share your data?

When can data be made available?

Data can be deposited in our Institutional Repository  and kept as an 'entry in progress' until it is ready for publication. 

Not all data needs to be made immediately available at the end of your PhD.  It is possible to add an embargo to give yourself some additional time to find funding to continue your work and re-use your own data.  See Regulations on embargoes.

However, it is not always necessary for you to wait until the end of your PhD before depositing data.  If you write a conference or journal paper it is likely that you will be asked to make the underpinning data available.

How will you keep your data safe?

What would happen if your files became corrupted or your laptop was stolen, would you be able to restore them?  What would happen if someone was able to access your data without your knowledge or approval?  If you are holding personal  or   special category  data (formerly referred to as sensitive data) and these became public this would be a data breach with potentially serious consequences.

Dr Fitzgerald  Loss of seven years of Ebola research  

Consider carefully the impact to you and your research if these were to happen and what procedures you may need to put into place to reduce the risk of these happening.

• Research Data Management and Sharing - Data Security Ensuring your research data are kept safe from corruption, and that access is suitably controlled more... less... From the Coursera Research Data Management and Sharing course https://www.coursera.org/learn/data-management

How will you back up your data?

Good housing keeping of your data is important and this includes doing regular back ups of your data.  University storage is backed up regularly but it is important to have your own 'back up' folders, kept separately from your working files.  Back up should be done on as regular a basis as required.  This can be defined by the length of time you are prepared to repeat work lost.  You may need to back up daily, weekly or monthly depending on the nature of your research.  

• Research Data Management and Sharing - Backup Effective backup strategies for your research data. more... less... From the Coursera Research Data Management and Sharing course https://www.coursera.org/learn/data-management

As well as establishing a process for backing up your files, you should check the process of restoring your files.  You will need to check that the files restore correctly.  Having good documentation on what your files contain, what transformations or analysis has been carried out will be invaluable for this process.

How can you safely destroy data?

Destroying data, especially   personal ,  special category  data (formerly referred to as sensitive data) or commercially confidential data , is not as straightforward as just deleting the file.  Further action is required otherwise the data could be recovered.  Please read our guidance on destruction of data   and GDPR regulations .

• Data Disposal Essential guidance from the UK Data Archive on data disposal

An important part of research data management is that your plan is implemented and part of your everyday good research practice.  The plan should be a living document and reflect your practice.  You may find that some parts become redundant or that there is a better way to carry out a process so your plan should be updated. As a PhD researcher it is likely that you will be the person responsible for implementing the plan.  If your research is part of a wider research project there may be someone in the team who has been given the role and you should discuss your data management plan with them.

Having written your plan consider what actions do you need to take in order to carry it out? What further information do you need to find? Investigate what training or briefing sessions are available via PGR Manager.  If you want to enhance your data analysis skills check out material on Linked in Learning 

Over time we will add plans to this section as we get permission to share them.

• PhD DMP Example (Web Science) This is an example PhD Data Management Plan for a research project looking at learner engagement and peer support in digital environments.
• Arts and Humanities
• Science, Medicine and Engineering
• Social Sciences
• Further Reading

Courses offered by the University:

Data Management Plans for Doctoral Students -  mandatory course on for all new doctoral students. Log into Blackboard using your university username and password.

Data Management Plan: Q&A Clinic - as a follow up to the compulsary online course, the Library is running twice weekly clinics to answer your DMP queries. Book PGR Development Hub .

Data Management Plan: Why Plan?  45 minute briefing.  A Panopto recording of this course  is  available

Research Data Management: What you need to know from the start .  45 minute briefing. Book via Gradbook

Research Data Management Workshop .180 minute workshop Book via Gradbook

• Introduction to research data (visual arts) Introduction to research data in the visual arts, wirtten by Marie-Therese Gramstadt as part of the Kultur project
• Manage, improve and open up your research and data PARTHENOS training module on various aspect on data management
• VADS4R Data Management Planning A toolkit developed by the Visual Arts Data Skills for Researchers (vads4R)
• Cross-Linguistic Data Formats, advancing data sharing and re-use in comparative linguistics The Cross-Linguistic Data Formats initiative proposes new standards for two basic types of data in historical and typological language comparison (word lists, structural datasets) and a framework to incorporate more data types (e.g. parallel texts, and dictionaries). The new specification for cross-linguistic data formats comes along with a software package for validation and manipulation, a basic ontology which links to more general frameworks, and usage examples of best practices. [article]
• EMBL-EBI Training EMBL-EBI train scientists at all levels to get the most out of publicly available biological data.
• Datatree - Data Training A free online course, aimed at PhD and early career researchers, with all you need to know for research data management, along with ways to engage and share data with business, policymakers, media and the wider public. more... less... The course is for any scientist, whether you look after your own data or are guided by an organisation.
• Expert Tour Guide on Data Management A guide for social science researchers who are in an early stage of practising research data management.
• CESSDA ERIC RDM User Guides Brief guides on important topics in data management and a helpful checklist
• Guide to Social Science Data Preparation and Archiving An important guide covering the different stages of data management to enable the sharing and preserving of data in the Social Sciences
• Managing your dissertation data : Thinking ahead Maureen Haaker and Scott Summers from the UK Data Service gave this presentation. The session sought to help the students ensure transparency in the collection and writing up of their dissertation, whilst also ensuring that good practices in data management were followed. more... less... Although aimed at undergraduate dissertation it provides useful information for everyone.
• UK Data Service Prepare and Manage Data Good data management practices are essential in research, to make sure that research data are of high quality, are well organised, documented, preserved and accessible and their validity controlled at all times. This results in efficient and excelling research.
• FAIR Principlies Guidelines to improve the findability, accessibility, interoperability, and reuse of digital assets
• How to Develop a Data Management and Sharing Plan Jones, S. (2011). ‘How to Develop a Data Management and Sharing Plan’. DCC How-to Guides. Edinburgh: Digital Curation Centre. Available online: http://www.dcc.ac.uk/resources/how-guides
• MRC Retention framework for research data and records guidance on retention of research data an records resulting from population health and clinical studies
• Open Data Handbook Handbook that discusses the why, what and how of open data – why to go open, what open is, and the how to ‘open’ data.
• Open Research Data and Materials Open Science Training Handbook section on research data

Key Documents

• DMP Templates
• Deposit Guide

The template below has been provided to assist you in writing your data management plan.  Not all sections will be relevant, but you should consider carefully each section.

• Template for PhD DMP (pdf)
• Template for PhD DMP (Word)
• Code of Conduct for Research University of Southampton policy - October 2017
• Data Protection Policy University of Southampton policy May 2018
• Data Sharing Protocol University of Southampton protocol - May 2018. [Login required]
• Ethics - Human participant policy University of Southampton policy - March 2012
• Ethics - Policy on Cultural Heritage University of Southampton policy - October 2018
• Research Data Management Policy University of Southampton policy - 2015

When the time comes to deposit your data, follow the advice in our Thesis Data Deposit guide . 

Email us on: [email protected]

Who's Who in the Research Engagement Team

Research Support Guide

  research support.

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• Last Updated: Mar 21, 2024 2:36 PM
• URL: https://library.soton.ac.uk/researchdata