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Research Data Mangagement Essentials, 5th July 2017
- 1. Research Data Management Essentials Graham Blyth Rachel Proudfoot
- 2. Overview • Setting the scene by starting at the end • Why RDM is important • Before project • During project • Project end, Deposit in WREO • Data Deposit, Research Data Leeds • Further information and training These slides will be shared
- 3. Data examples • http://doi.org/10.1038/nature14621 • Al Ma’Mari. F. et al. 2015. Beating the Stoner criterion using molecular interfaces. Nature 524(7563), pp.69–73. doi:10.1038/nature14621
- 4. Research data example • Mengoni, Marlène and Wilcox, Ruth (2015) Ovine annulus fibrosus interlamellar material model calibration data set. University of Leeds. [Dataset] http://doi.org/10.5518/2 • Associated with a paper in Journal of the Mechanical Behavior of Biomedical Materials
- 5. • Data set associated with 'Magnetic Phases of Sputter Deposited Thin-Film Erbium'. University of Leeds. [Dataset] • https://doi.org/10.5518/112
- 6. Performance data https://doi.org/10.5518/57 James Mooney discusses his data (6 mins)
- 7. Data linked to a PhD thesis • ‘Mapping the field of children’s literature’ (Arts) • Thesis http://etheses.whiterose.ac.uk/15304/ • Associated data https://doi.org/10.5518/41 • ‘Decellularisation and characterisation of porcine bone- medial meniscus-bone’ (Biological Sciences) • Thesis and associated data • http://etheses.whiterose.ac.uk/7661/
- 8. In sum • Data varies –No easy definition: more about how material is used than what it is • Data could be associated with a specific publication / thesis • Could be a primary output in its own right • Credit for research data
- 9. Exercise • Reasons why researchers in your field (i) would share data* (ii) wouldn’t / shouldn’t share data (*beyond the original research team)
- 10. Why? • Good research practice • Transparency • Compliance • For funder reasons –Use –Reuse –Repurpose • Increase impact • Reach collaborators • Legal and ethical constraints • Writing a publication • Being scooped • Applying for a patent Why not?
- 11. University of Leeds Research Data Management Policy (handout) • PIs responsible for –research data management within their projects –creating a data management plan for each proposed research project or funding application –creating and storing sufficient metadata to aid discovery and re-use –complying with relevant legislation –ensuring all relevant research data are made available at the completion of each research project • [https://library.leeds.ac.uk/research-data-policies]
- 12. • “…project specific data management policies and plans… …should exist for all data” • “data relied on in published research findings will, by default, be available for scrutiny by others” • statement in papers about access to data • data should have persistent URLs / DOIs “as open as possible, as closed as necessary” Horizon 2020
- 13. Benefits for you • Build academic profile • Increase impact • Get credit • Build research networks
- 14. creating data processing data analysing data preserving data giving access to data re-using data Data Lifecycle Practical housekeeping Decision making Who should I talk to?
- 15. Data management plans • Making data sharable takes planning! • Research Data Leeds web site http://researchdata.leeds.ac.uk Before project 1. Write a data management plan 2. Costs - examples
- 16. Questions • What data are you working with? • Practical housekeeping – how will you manage your material? • What can be shared? • When? • What permissions are needed? • Who do you need to talk to – e.g. supervisor, collaborators.
- 17. Exercise http://bit.ly/2htlnrO • Basic data management plan template (handout) 1. What sorts of data do you generate? 2. Any immediate issues? 3. Do you think a plan would help you? 4. Is there anything missing from the template? 5. Do you already have a data management approach?
- 18. Ethics, consent, and partnerships • Consent –Ensure the wording on any consent form matches what you plan to do with the data. Make sure consent is informed consent. • Industrial partnerships –Commercially sensitive data may be subject to restriction. Clarify ownership and release plans. ‘Available’ ≠ ‘open’. • Anonymisation –What is best practice?
- 19. Ethics, consent, and partnerships • Not all data may be subject to the same constraints. • Keep records of decisions made and permissions obtained. • Ethical review process: • “..think through the DMP before applying for ethical review as the ethics application form, participant information sheet and consent form will all need to be consistent with the info in the DMP…” UoL Senior Research Ethics Administrator
- 20. Permissions and copyright • Copyright for PhDs • https://library.leeds.ac.uk/copyright-for-phds • Research Student Handbook refers to “Inclusion of Supplementary Data/Information on a CD” • NB keep good records! Where, contact, permissions.
- 21. During project 1. More planning! 2. Store data • Filenaming • Folder structure • Formats • Storage and handling • Backup 3. Describe data • Metadata and documentation • e.g. table values 4. Decide what to keep In the field In the lab In an archive
- 22. What data to keep? 1. What data do I need to keep to validate the results of my published research? 2. Does my data have value beyond my publication / my thesis? 3. What’s irreplaceable, very expensive to repeat
- 23. Data appraisal Data Types Value Example Observational data captured around the time of the event Usually irreplaceable Sensor readings, telemetry, neuro-images, survey results, video of performance Experimental data from lab equipment Often reproducible but can be expensive Gene sequence, chromatograms, toroid magnetic field readings Simulation data generated from test models Model and metadata more important than output data Large modules can take a lot of computer time to reproduce Climate models, economic (inputs) models. Derived or compiled data Reproducible (but very expensive) Text and data mining, compiled databases, 3D models UoB
- 24. Service Remote access Single file limit Overall storage limit Store sensitive data? N Drive General shared areas • Citrix Web Access • VPN / Microsoft DirectAccess • 256TB (NTFS filesystem limit is 16 EB, limited by Windows Server 2012) • Faculty allocation • No, unless complies with UoL Information Protection Policy (encrypted, short-term only for sharing with authorised parties) M Drive Personal user work • Citrix Web Access • VPN / Microsoft DirectAccess • Quota limits managed by Core IT • 1GB students 5GB staff • Yes OneDrive Personal space that can be shared externally if necessary • Yes • 10GB • 1TB • No, unless complies with UoL Information Protection Policy (encrypted, short-term only for sharing with authorised parties) Data Centre Strategy planning for large and sensitive data
- 25. Burning questions / tea break? • Write on the whiteboard wall..
- 26. Data sharing and how not to do it.. What issues are raised in the video?
- 27. Metadata for discovery and identification • Title • Creator - ORCID • Abstract • Keywords • Data type • Geographic coverage • DOI • Metadata to enable unambiguous citation
- 28. Metadata for reuse • Field name meanings • Data guide / structural map • Data format • Research design and methodology • Field notes • License conditions • Software
- 29. Project end / Thesis submission 1. Deposit & share data • choose repository • what, when and how • metadata • reuse license and access control 2. Obtain DOI 3. Include data statement in publications (or thesis)
- 30. Choosing a repository • Does your funder have a preference? –e.g. Natural Environment RC data centres • Is there a well established subject repository? –E.g. Cambridge Crystallographic Data Centre (CCDC) • Does your publisher have a preference? • Do you?
- 31. How to deposit in Research Data Leeds 1. Email basic metadata to Research Data Leeds 2. RDL will create an N Drive folder for you and assign DOI 3. Complete metadata spreadsheet, upload files, say ‘yes’ to Deposit Agreement 4. Sign off in 'Review' repository 5. RDL make data live; mint Digital Object Identifier (DOI)
- 32. DOIs – Digital Object Identifiers • A DOI can be assigned at any point in the deposit process. • The DOI will be minted as soon as the data/metadata is available Most appropriate times to request a DOI: • When your paper has been accepted for publication – in time to be included in the proof • At submission • (Check it’s included in your paper!)
- 33. Link papers and data in Symplectic
- 35. A word about open access… Gold Open Access • Payment of Article Processing Charges (APC) to a publisher • Published article becomes free to read on publisher website • University can pay APC if you are funded by COAF or RCUK or are publishing in RSC, certain Taylor and Francis or Springer journals http://library.leeds.ac.uk/open-access- funding • Paper should also be added to Publications Database Green Open Access • Paper still published in normal way • Log in to the University’s Publications Database using your IT username and password and add your research outputs (author accepted manuscript) https://publications.leeds.ac.uk • No cost involved • Library checks, adds it to the institutional repository (White Rose Research Online) and applies any embargoes
- 36. Consider using LUCID • A specialist team of expert Information Specialists who are part of the Library Research Support Team • We work for researchers across the University on literature searches for funded projects • Cost us into your research bids • We develop and execute searches and manage references through EndNote including de-duplicating library. • https://library.leeds.ac.uk/lucid
- 37. Training and Support • LIDA – Leeds Institute of Data Analytics –http://lida.leeds.ac.uk/study-training/ –“introductory courses for postgraduate students through to advanced training for data scientists”
- 38. Training and Support • MOOC – Research Data Management and Sharing – free, Coursera platform, videos, quizzes. Registration required. (Uni of Edinburgh and Uni of Carolina at North Chapel Hill) • MANTRA – free, self paced, online (Uni of Edinburgh) • Coursera – many specialist online courses • Examples of data management plans
- 39. Training and Support • UK Data Service – practical guidance on all aspects of data management, including handling sensitive data • Digital Curation Centre – online data management planning tool (DMPOnline), How-To guides Data management planning tool • DMPOnline: https://dmponline.dcc.ac.uk/ • Templates for major research funders
- 40. Further help and information • RDL website • http://researchdata.leeds.ac.uk • Email • researchdataenquiries@leeds.ac.uk • Tel: 0113 343 4554 • Twitter: @OpenResLeeds • Research Data Leeds repository: http://archive.researchdata.leeds.ac.uk
- 41. More useful resources • Filenaming: Jisc ‘Choosing a file name’ • University storage: File storage • University IT policies, including the Information Protection policy: https://it.leeds.ac.uk/info/116/policies
- 42. Please fill in the feedback form • http://bit.ly/2h96rSc • Bonus content
- 43. Research data sharing in practice Dr Gabriela Lopez- Gonzalez, School of Geography
- 44. More information on filenaming • Information from the Research Data Leeds web site • Straightforward, 10 minute video tutorial covering the basics of filenaming from the State Library of North Carolina • Version control guidance from the University of Aberdeen • Slides on file and folder naming and file versioning from MIT
Notes de l'éditeur
- Research data management (RDM) has become a hot topic over the last 2-3 years. This session looks at why RDM has become more prominent and some practicalities researchers should think about before, during and after a research project.
- The DOI links to a recently published paper in Nature (August 2015). If you click on the affiliation tab, you can see that there is a data availability statement at the bottom of the page. The DOI links to the associated data in the Research Data Leeds repository. A DOI – digital object identifier – is a unique string of characters associated with a digital object. It is also a web link to a digital object. The published paper has a DOI (allocated by Nature); the related data has a DOI (allocated by University of Leeds). The paper links to the data; the data links back to the paper. Both are indexed in Google and other search engines so provide a good way for people to find both the paper and the data. Data sharing is becoming the norm, particularly for data underpinning publications. For PhD students, the advice in this session is equally applicable: your PhD is a publication – is there associated data you can link to? Who owns the data? At what point is it appropriate for data to be made available?
- This example shows data which was made available whilst the publication was ‘in press’. The researchers have chosen to include some images from a laboratory notebook as part of their dataset / contextual information. If you look at the record, you will note that some of the researchers have ORCiDs – for instance, Gavin Burnell. The link to Gavin’s profile also lists his publications, which in turn link back to the associated data. Digital materials are increasingly linked. Each provides a route to other information about the researcher and/or associated research outputs.
- Link to James Mooney talking about his music data (go to 17:20 – 19:15) This is the music which was playing before the start of today’s workshop. It illustrates how ‘data’ can mean different things to different people and there will be choices to be made about how to organise data into meaningful (and potentially citable) units. This data contrasts with the Al-MaMari and Burnell examples where the data is closely associated with a specific publication. In this case, the data is a primary research output in its own right which may become associated with publications at a future date.
- There is no one rigid definition of research data; it’s largely an academic judgement. What is valuable to share? How can it be structured and shared? Data has a lifecycle. It’s worth thinking about who needs to access and understand the data through its lifecycle.
- Why are we here? Why manage your data? Good data management is simply good research practice. But there are additional drivers around managing and sharing research data including: Transparency – validate your results, compare your results using other methods Compliance – keep your funding Funders – compliance – but why do they want it? Ensure other researchers can access the work they funded. Avoid unnecessary duplication of research. Data as ‘a public good’. Research data skills – useful during PhD but also in ongoing academic work – and in other contexts. You may be the first ‘reuser’ of your own data – make sure you have documented any key decisions and have adopted practical strategies so you can find and understand your own work in two or three years’ time. Opening up research and research data can be an excellent way to boost your own impact but also to help build networks and collaborations around shared areas of academic interest. Some research areas already have a culture of data sharing (e.g. gene sequences, crystallography) but in other areas data sharing is less prevalent or tends to take place informally between researchers. Much research is publicly funded. The Research Councils’ statement on data emphasises “Publicly funded research data are a public good, produced in the public interest, which should be made openly available with as few restrictions as possible in a timely and responsible manner that does not harm intellectual property.” [RCUK Common Principles on Data Policy, www.rcuk.ac.uk/research/datapolicy/] Many Universities have data management policies (not just in the UK). The Leeds data policy is online at http://researchdata.leeds.ac.uk/management-policy Some journal publishers expect the data underpinning published papers to be available – it may be a condition of acceptance (e.g. Nature, PLoS) All the Research Councils have data management expectations and there is a major data pilot as part of the European Horizon 2020 programme. The EPSRC has been particular strong in this area and have had a significant impact on Leeds’ approach to research data management.
- We will be coming back to these points during the session. This University has a data management policy – and many other Universities have similar policies. Appropriate data management and, where possible, data sharing is becoming expected standard practice.
- EPSRC issued a set of expectation which apply to both Universities and to individual researchers. The full expectations and supporting guidance are available online at https://www.epsrc.ac.uk/about/standards/researchdata/expectations/ Some research areas already have a culture of data sharing (e.g. gene sequences, crystallography) but in other areas data sharing is less prevalent or tends to take place informally between researchers. Much research is publicly funded. The Research Councils’ statement on data emphasises “Publicly funded research data are a public good, produced in the public interest, which should be made openly available with as few restrictions as possible in a timely and responsible manner that does not harm intellectual property.” [RCUK Common Principles on Data Policy, www.rcuk.ac.uk/research/datapolicy/] Many Universities have data management policies (not just in the UK). The Leeds data policy is online at http://researchdata.leeds.ac.uk/management-policy Some journal publishers expect the data underpinning published papers to be available – it may be a condition of acceptance (e.g. Nature, PLoS) All the Research Councils have data management expectations and there is a major data pilot as part of the European Horizon 2020 programme. The EPSRC has been particular strong in this area and have had a significant impact on Leeds’ approach to research data management. The move towards improving data management and data sharing is international.
- Research data skills – useful during PhD but also in ongoing academic work – and in other contexts. You may be the first ‘reuser’ of your own data – make sure you have documented any key decisions and have adopted practical strategies so you can find and understand your own work in two or three years’ time. Opening up research and research data can be an excellent way to boost your own impact but also to help build networks and collaborations around shared areas of academic interest.
- For many projects the plans and infrastructure are already in place – an ongoing area of research with well established protocols and SOPs. For PhD students this may not be the case. You are likely to need to adapt to new ways of working where these are already established in your research group or develop your own plans almost from scratch – with input from your supervisor and colleagues. Thinking about sharing will drive data appraisal and preservation decisions later in the project. Day to day housekeeping and consistent approaches to all aspects of file handling will seem like an overhead to begin with but are likely to save a lot of time (and perhaps even avoid disasters) in the long run. Recording interview or laboratory procedures, software used in processing, samples or archive material details should be happening all the time. … more later The questions you should be asking yourself: What data are you working with? How will you manage your material? What can be shared? When? What permissions are needed? Who do you need to talk to – e.g. supervisor, collaborators.
- Much data management is business as usual and should be a routine part of research practice. Some early planning can save a lot of grief later. It is particularly important to consider data management costs and whether these can be added to a grant application. You want to make sure you have sufficient resources to carry out your research effectively. Your funder may require a data management plan at application. The exact format of plans varies but there is a lot of core common ground The Leeds data management plan is designed to help you cost your project. Potential research data related cost items would be: storage and archival storage if data volumes are very large, website costs, data preparation, special pieces of equipment. The Research Data Leeds web site is structured to help you plan through the whole project and beyond.
- Has anyone already done a data management plan? Share experience. What sorts of issues were coming up?
- Not all data can or should be made available openly. Unduly restrictive agreements may make it difficult to share your data so think carefully about gaining informed consent from your participants. Data availability is important for a transparency and to enable research result validation. Risk By not using the informed consent procedure to communicate/make provision for the storage, sharing and re-use of your research data, the risk of not being in a position to validate your research findings is very real. Third parties who collaborate in publicly funded research should be made aware of the importance of ensuring that published findings can be validated by others'. (EPSRC guidelines)
- Not all data can or should be made available openly. Unduly restrictive agreements may make it difficult to share your data so think carefully about gaining informed consent from your participants. Data availability is important for a transparency and to enable research result validation. Risk By not using the informed consent procedure to communicate/make provision for the storage, sharing and re-use of your research data, the risk of not being in a position to validate your research findings is very real. Third parties who collaborate in publicly funded research should be made aware of the importance of ensuring that published findings can be validated by others'. (EPSRC guidelines)
- Whether your using material within your thesis, as supplementary information for your thesis or in a journal paper or book chapter, make sure you are aware of any copyright restrictions on third party materials. Make sure you seek appropriate permissions and keep a record. You might be referring to your records for a long time during the course of your thesis so be consistent.
- Data management is an ongoing process; review and update your plans and practices. Agree standard filenaming and folder structures so files are readily shared and understood within and beyond your project. Use open formats where possible. How will a re-user be able to read your data in 5 years, 10 years? If you store and share data, you will need some metadata and documentation – both for yourself but also for anyone coming to your data in the future. You may have moved institutions or be unavailable so the data needs to be understandable in its own right. There is no requirement to keep everything. Selecting the most relevant data from what you have generated requires academic judgement; as the expert in your own data, it will be your call.
- If you were reading a paper in your field, what data would you expect to see to support the results reported in the paper? Research data is valuable in its own right; it doesn’t have to be linked with one specific publication. You will need to judge the value of your data against the costs of long term storage and curation. Further guidance is available on the Research Data Leeds web site or from the Research Data Leeds team.
- This slide shows some different types of data, their value and examples of each type. This continues the theme that there is a wide variety in research data and introduces the notion that research data has value associated with how much it would cost to replace or reproduce the data. The value of research is a way in to thinking about how much you should invest in keeping and managing the data.
- For a bit more detail see http://it.leeds.ac.uk/info/25/file_storage http://it.leeds.ac.uk/info/223/onedrive-university_of_leeds/789/comparison_of_m_drive_with_onedrive
- Issues raised in this video include: long term storage, file formats, identifying / disambiguating academic colleagues, recording sufficient metadata, use of data beyond its original purpose / in another academic field and curation of software. It also highlights the value of curating data in its own right and associating publications unambiguously with underlying data.
- Don’t worry about the word ‘metadata’; it’s descriptive information and documentation Many repository systems have similar, basic descriptive fields to allow datasets to be cited as a primary research output and to help potential reusers discover the data.
- The documentation is likely to relate to you instrumentation, software – do it well once and reuse yourself Some of it might be structured – are there ontologies or metadata schema in use in your discipline?
- Data can be deposited in a repository or data centre; this is more stable than storing data on a local drive.
- If there is an obvious place for your data to go, deposit it there so long as it undertakes long term access and curation, gives you a unique and persistent identifier for your data and does not impose unnecessary restrictions on who can access and reuse the data. Some funders specify where data should be deposited. Some journals will also have a preference for where data is deposited and may have a relationship with a data repository (e.g. some journals use Figshare, others Dryad). Many repositories are available. If in doubt talk to the Research Data Leeds service. Any experience to share? How would you look for data? Make sure any data service issues a unique and persistent identifier for your work. Include a statement referring to the data in your publications. Writing ‘contact the author’ is unlikely to satisfy your funder and is not a stable way to supply data.
- We will allocated a DOI at submission or acceptance. At submission, there may be more changes to the dataset as a result of peer review – or the paper may be rejected. On the other hand, you have more time to prepare your data. At acceptance, we know the paper is going ahead and you may be clearer what data need to be uploaded. For datasets not associated with a publication DOIs will be allocated and minted as part of the upload process.
- This will be relevant to them if they are hoping to publish journal articles or conference papers throughout their PhD. Important for them to be aware of requirements of OA publishing if continuing academic career post-PhD. Explain what the two routes are Two routes to open access Gold: If you are funded externally: Check whether there is a requirement to make OA Check whether there is any money available to you The University receives a block grant from the Research Councils UK and the Charity Open Access Fund (COAF) to pay open access article processing charges (APCs). We have a limited number of APC credits for Royal Society of Chemistry and some T&F and Springer journals – Phd students are eligible to apply for these see R@L for details Green If no money or don’t want to pay for gold. Add the author accepted manuscript (version which has been accepted and agreed with publisher, but has not undergone any copyediting, typesetting or publisher branding).
- The Library has a literature searching service. You can take advantage of a free scoping search; more extensive searchers can be costed into bids.
- There are several sources of training and support which may be of interest to you. Some are generic, but the large MOOC platforms like Coursera and FutureLearn have a growing number of more specialised short courses relevant to specific areas of research and research data. MANTRA is a free, modular training resource written by the University of Edinburgh. It covers several of today’s topics in more detail. The Research Data Management and Sharing MOOC has similar content to MANTRA but is more lecture / video based and you can choose whether to do the course on your own or as part of an online student ‘cohort’.
- There are several sources of training and support which may be of interest to you. Some are generic, but the large MOOC platforms like Coursera and FutureLearn have a growing number of more specialised short courses relevant to specific areas of research and research data. MANTRA is a free, modular training resource written by the University of Edinburgh. It covers several of today’s topics in more detail. The Research Data Management and Sharing MOOC has similar content to MANTRA but is more lecture / video based and you can choose whether to do the course on your own or as part of an online student ‘cohort’.
- Further information and links to training resources can be found on the Research Data Leeds web site. DMPOnline is a free online tool which offers data management plan templates for several funders and it can be used to create a generic data management plan for any project. DMPOnline can be used to write collaborative documents and once you’ve created an account can be accessed using your University login.
- This video is about assigning DOIs to data and why DOIs are great! It also highlights several other areas of research data management practice. Exercise – What data were gathered? What information would you need to understand the data?