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- 1. Photo by Aron Visuals on Unsplash Research Data Management and your PhD Judith Carr – Research Data Manager The Open Research Team - The Library
- 2. Aim:- To show how research data management can contribute to the success of your PhD. • What is research data and why it is important? • The Research Data lifecycle • Research Data – more than just your results • FAIR data and Open Research • DMP online tool
- 3. “an explicit process covering the creation and stewardship of research materials to enable their use for as long as they retain value.” Research data are Research data management is Any recorded information necessary to support or validate a research project’s observations, findings or outputs, regardless of format What are Research Data????
- 4. Research data value • University of Liverpool - https://www.liverpool.ac.uk/media/livacuk/computingservices/research- data-management/researchdatamanagementpolicy.pdf • UKRI ( funders policies) - https://www.ukri.org/apply-for-funding/before- you-apply/your-responsibilities-if-you-get-funding/making-research- data-open/ • Wellcome - https://wellcome.org/news/our-new-policy-sharing- research-data-what-it-means-you • Gates Foundation- https://gatesopenresearch.org/for-authors/data- guidelines For you • Forms the basis of your conclusions • You waste time if you can't find it, interpret or understand it, worse still if you lose it • If your research continues • If you are asked to collaborate • If you are part of a team For others • For future work in your discipline • Your department/school/University • Funders • RDM policies
- 5. Original ©Jisc and Bonner McHardy CC BY-NC-ND Data creation any format Data processing discipline specific or not Data analysis Most appropriate or discipline specific Data preservation selection, anonymise, pseudonymise Data access options Open Safeguarded Closed Data reuse data catalogues Essential
- 6. The planning stage – where you plan and then plan some more! www.Liverpool.ac.uk/rdm Plan because Avoid drowning in irrelevant information Avoid duplication Underpins integrity and efficiency of research Enables you to access data easily Aids collaboration Underpins data security and preservation – back up Plan to share – more efficient – time and money Ensure continuity of project/research
- 7. Create and collect, store, file, and manage the questions a data management plan can address Who owns the data you will be using, creating or collecting? If getting data involves interviewing people – ethics consideration – data protection – Get consent. Secondary data – check your source – are there restrictions on usage, on sharing, where you store, how long you can keep, how to cite the source Are there any legal, ethical or commercial considerations? YES! If secondary data YES! If primary and people are involved – always Yes! If you are working with a commercial concern Are there any standards for organising, labelling or describing research data in your field of research. What types of data will be collected or created? What formats will you use? How much data do you estimate you will be collecting and storing? Where will the data be stored during your project? Are there any security issues relating to the storage of the data. Who else will have access to this data during the project?.
- 8. Store and back up • Where? Important when dealing with personal/special category data, also when using secondary data. • Security? Passwords, encryption, limit access, only collect what you need, anonymise and delete • Never! One copy on tablet, phone, USB, unprotected laptop • University of Liverpool C or M Drive , Dept share drive, Active Data store • Information security – IT Services KB0012515
- 9. The ingredients for sharing Photo by Kelly Sikkema on Unsplas University of Liverpool Research Data Catalogue • Discipline or funder research data repository • Liverpool Research Data Catalogue • Persistent identifier – DOI – you can be cited! • Creative commons licence (CC-BY if possible) • Anonymise to share • Cannot go open – safeguarded or controlled sharing and data sharing agreement • Metadata – to find and understand your data • Formats – generic and accessible • LINK
- 10. Publish and share the questions you can ask yourself in a data management plan Will you be able to share any of your data? (if you don't prepare this can take up extra time and energy) How do you plan to share your data? Will it be 'open’? If not open how can someone find out about it? Which data will you be able to retain in the long term? Whether data is open or not – you need to consider FAIR data principles - more about this later What formats do you plan to use when depositing in a data repository ?
- 12. Research Data isn’t just • Your results • Your figures • Your conclusions Research Data is much more! What When Where Who How Which Why Vocabularies Data dictionaries
- 13. Photo by Derick McKinney on Unsplash Not the most exciting part of research! • For some might be as simple as filing, learning data descriptions or metadata vocabulary • For some it will mean a lot of conversations about what, how and where data is collected • Start out with a plan, then you avoid delays further down the line. Plan what you need, plan how to gather and analyse data and plan to share. www.Liverpool.ac.uk/rdm The How, What, Where, When, Who, shows how you analysed and worked with your data, illustrates the integrity of your research and how to replicate ( if appropriate). What would you need to know to do repeat this research 5 years?
- 14. Example:- filing of email, letters, attachments • Name of correspondent (sender or receiver as appropriate) • Subject description (where it is not given in the folder title) • Date of letter/email/memo • If incoming correspondence, include ‘rcvd’ • If an attachment, the same info as above, with additional: 'attch' - to indicate the document is an attachment and [2 digit number] of [2 digit number] - to indicate the number of attachments received with the same covering email Correct file name /…/Complaints/ BloggsJ20031205attch01of02.pdf BloggsJ20031205attch02of02.pdf BloggsJ20031205rcvd.txt BloggsJ20040105.rtf BloggsJ20040220.rtf BloggsJ20040220.rtf ThomasH20030610rcvd.txt ThomasH20030710.rtf (Ordered alphanumerically as the files would be in the directory list) Incorrect file name /…/Complaints/ AttachmentFromHThomas10Jun03.rtf Attachment1FromJBloggs.pdf Attachment2FromJBloggs.pdf EmailFromHelenThomas10Jun03.txt EmailToJoeBloggs5Dec03.txt LetterFromJoeBloggs5Jan04.rtf LetterToHelenThomas10Jul03.rtf LetterToJoeBloggs20Feb04.rtf (Ordered alphanumerically as the files would be in the directory list)
- 15. cea + from The Netherlands [CC BY 2.0] • Don’t drown in data/information • Don’t rely on your memory • Avoids repetitive reading, testing, analysing • Helps you find your data/information • Helps you to explain what you have done • Helps when collaborating – ask management questions first • Versioning, shows progress, thought process, development • No one size fits all Planning (Helps you get the answers you need)
- 16. Metadata helps you How do know where to store your data? How do you know what kind of security required? What data to delete? What versions you have? Who can access the data or not? What filing system to use for your format? Are you going to look in all your files to find data? To access versions, to know where data is to share, to view again. EXAMPLES Metadata and sharing Covid-19 research Schriml, L.M., Chuvochina, M., Davies, N. et al. COVID- 19 pandemic reveals the peril of ignoring metadata standards. Sci Data 7, 188 (2020). https://doi.org/10.1038/s41597-020-0524-5 https://www.youtube.com/watch?v=66oNv_DJ uPc&ab_channel=NYUHealthSciencesLibrary And is essential in helping others
- 17. https://findwise.com/blog/wp-content/uploads/2019/11/FAIR-Data-image-map-graphic-v2-721px.png FAIR DATA – an important initiative – supports open as possible, closed as necessary Human and Machine readable https://www.youtube.com/watch?v=2uZxFu9SFi8&ab_channel=UGent DataStewards
- 18. https://www.liverpool.ac.uk/open-research/ Photo by Jasmin Sessler on Unsplash https://unesdoc.unesco.org/ark:/4822 3/pf0000379949.locale=en
- 19. This session does not cover GDPR and Anonymisation GDPR - https://stream.liv.ac.uk/ss9k6g38 https://stream.liv.ac.uk/mfydsj3q https://stream.liv.ac.uk/et8de4tv https://www.liverpool.ac.uk/intranet/legal/data-protection- foi-staff/dataprotectiongdpr/ Anonymisation - https://stream.liv.ac.uk/ytqpctdt We have covered in this session • What is research data and why it is important? • The Research Data lifecycle • DMP online tool • Research Data – more than results - metadata • FAIR data and Open Research Ethics - https://www.liverpool.ac.uk/intranet/research- support-office/research-ethics/
- 20. To conclude PLAN from the beginning, be flexible, note down changes and why. Plan to share, think about what you would need to know if you wanted to use your own research data in years to come DMP online use this resource, use funder templates, ask questions of your collaborators at the beginning Metadata ask those questions, who, what, where, why, when, which – have readme files and protocols, whatever helps FAIR and Open planning helps you and others to work towards incorporating these initiatives.
- 21. Thank you and any questions? Webpages www.Liverpool.ac.uk/rdm – Liverpool Research Data https://www.liverpool.ac.uk/legal/data_protection/ - Data Protection https://www.liverpool.ac.uk/csd/security/information-security/ - Information security – IT Services KB0012515 https://www.ukdataservice.ac.uk/manage-data/legal- ethical/anonymisation/step-by-step.aspx - UK Data Service https://www.re3data.org/ - registry of research data repositories
Editor's Notes
- Hi Welcome to this session about Research Data Management and your PhD. My name is ………. I head up Liverpool Research Data – the RDM service based within the Open Research Team in the Library.
- So what I will be doing is covering the following Firstly let talk about what are Research Data? I always start with this definition because it is useful to make sure we all know what we are talking about.
- Regardless of Format Retain Value – what does that mean
- That value intially of course is for you – data is obviously important but you can waste time if you don't know where it is , if you cannot understand it what you have recorded or what you did 2 years after you have collected/analysied it then it is not much use when you come to write up – or worse if you lose it. The research data behind your thesis can also form part of continuing research, can help if you are asked to contribute to another project ( in which case particularly important that others can use and read and understand data and you certainly do not want to speadn time checking before you share, a waste of your time. If your thesis forms part of a bigger project then that data becomes important to your colleagues. however research data also has value to others, maybe not whilst you are doing your PhD, certainly after. Go thru.
- The Research Data lifecycle, follows a project lifecycle and where you are in the project depends on what you should be doing with your data. start with planning and designing collection but remember any format – not just about spreadsheet but how collect data before that or other ways to create, collect data. In addition if you are using data for another party, you need to know what you can and cannot do – more about that soon. Data processing and analysis – this can be prescribed by your discipline but this is not always the case. You should find out – if there is a common way to express data then use it – do not reinvent the wheel, it serves no purpose, even if you can. You may at this stage come across data that others have made available via discipline specific repositories, look at how they represent their data – it will not all be good. Remember the things that annoyed you! Don’t repeat but improve on that. Remember you are going to have to come back to the data you worked with in 6 months, a year and interpret. Are you going to remember? Now is time to look at these stages in more detail.
- So lets look at this lifecycle, in more detail, at each stage. First of plan, and plan some more. tempting to dive right in and get that data but… that way you will drown in information, duplicate what you are doing ( do not under estimate the number of experiments redone 6 months, year later because someone could not read results – it could even mean not using data, which is a waste of time and energy – yours) . Planning helps to address other issues, such as integrity – showing a plan, shows you have thought about what you are doing. Planning where and how you are going to file your data means when someone asks for it, you can find it! Makes you look good. It means you can consider before it becomes an urgent issue or before you loose some data what you are going to do to secure this data, backing up, etc. Plan to share you data, even if you don’t share all in the end, why because it makes you think of what you are doing and documenting it ( more later about this). If you can share, think how much time and energy you have saved others , there is no need to replicate research that is already been undertaken. And then sharing, means you can increase the potential to collaborate with others. Just suppose your data was used by someone, you were cited/credited and they went on to win a Nobel prize or solve a major problem.
- The data management will ask questions that you means you have ot address issues that occurr when you are creating/collecting, storing, filing and managing your research data. Go thru these statements.
- During your project, if you already know where you going to store, label and back up – the data collection, analysis, etc is so much easier. It is important to consider where it is appropriate to store your data. In terms of security you need to assess what is most appropriate. IT services have a useful guide to assess where is best to store data of any sort – KB0012515 What is important is that you plan, especially if your data is sensitive or personal. 1st of all back up is important – there is a rule 321 – three copies two different storage methods – one separate location – that is not having laptop and sep hard drive in the same back pack that was under you as you fell down stairs or on the desk below where the shower leaked! All things that have happened to people. the next question is security – you need passwords, encryption, limit access and of course always consider anonymisation – anonymise early and using the data becomes easier. What you should never do is have one copy of anything on something insecure, a tablet, USB stick, phone!!
- I admit I am biased, where possible you should make your data open as possible. Whatever happens when you finish your PhD, planning that you will , means that you will have the documentation, the explanations you need will help you, the future you,who has to look back and see what you have done to write up and explain what you have done. if you can and want to go open at Uol we have the LRDC where data can be made open or but even if you cannot share openly then you should be able to share in a more controlled manner and considering the ingredients needed for sharing helps Go thru these.
- A data management plan will mean you have to consider the questions about publishing and sharing – such as the following
- So the top image is what you see when you log onto DMP via our RDM webpages. You will then have to fill in some basic information and click write plan. Then the questions will appear like the third image. Click next page
- But and this is a BIG but the details you need to know in year 3 regarding what you did in year 1 or 2 isn’t just the results and your conclusions – you and others you share with need to know much more. What you will all need to know if the what when where who how which why, maybe even vocabularies, data dictionaries. What is that metadata!!
- Absolutely not what you want to do, you want to jump straight in and research and collect, create, analyse stuff. But! Spend time first on how you organise and annotate metadata can help you later one. There is this tool which will help you with this. DMP online - it is free to use, log in using Uni email and can select a UoL template but also a funder. It asks basic questions but these help you think about what to plan. You can go into great detail regarding your how you wish to annotate your data or you can refer to discipline specific schemas or you can keep things simple depending on your needs. When collaborating it is useful to go into more detail. Much depends on the operating system and software you are using but get to know early on what you will be using. Here is a simple example of what I mean.
- This is just one context but it recognises what is important in this data collection/archiving and what can do with the operating system. Go thru
- So that example just shows you that for you and others metadata is a love note to the future for sure. Go thru. It is easy for me to say this, but this is not necessarily easy, so if you do need to access data from data repositories learn how to express your data in a similar way, or learn by their mistakes, make it one of priorities to learn the systems you use to collect and analyse data so that you know the best way to file and store. And if someone else says doing it this way, labelling like this works then copy.
- And yes it does help throughout a project. Firstly the paper – which is very up to date. Then let’s play the video Now I am going to introduce something different but still connected with research data management
- FAIR data principles are becoming increasingly important because they are being adopted and promoted by funders especially in Europe but also here. The principles are about sharing but not necessarily being open, which in some ways is what is best to consider. As I have said, preparing to share is helpful to your future self and others. Go thru At the bottom here I have included a really useful video about these principles. So when you are considering what you need to record and what software, etc you should have your final results in these principles will help.
- You will hear the term open research or open science ( for in Europe the term Science means research – perhaps in a lot of languages except English annoyingly) Open Research covers practices that include open access for journal articles and outputs at the end of a project and sharing research data openly but is much more. Such as open lab books, registered reports, open protocols, open funding, open peer review, using platforms to show your research practise throughtout the whole lifecycle such as the Open Science Framework, sharing code on Github. It would hard at this point to consider being open in everything but it is worth being aware that you have options. Indeed your thesis will be published openly via the University repository and you can certainly consider making your data open. Open Science is going to become even more important in future years UNESCO Finally, I am going to show you a screenshot what our template looks like for the completion of a DMP>
- I have not had time to cover the following in this session but I would like to signpost the following resources. Well videos on our channel which can help you when you consider GDPR and Anonymisation. Plus if you go onto our RKH page there is a section on web based tools and there you will find other resources.
- I realise we have gone through quite a lot, I would therefore conclude by hightlighting the following. Thank you.