RDM for librarians
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RDM for librarians



Presentation given at the University of Northampton in a 3 hour training session for academic liaison librarians.

Presentation given at the University of Northampton in a 3 hour training session for academic liaison librarians.



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RDM for librarians RDM for librarians Presentation Transcript

  • Research Data Management for librarians Sarah Jones & Marieke Guy Digital Curation CentreMiggie Pickton, University of Northampton
  • About this course Short presentations with exercises and discussion Five main sections ― Research data and RDM (30 mins) ― Data Management Planning (30 mins) ― Data sharing (20 mins) ― Skills (30 mins) ― RDM at Northampton (30 mins) Coffee break halfway through, after data sharing
  • IntroductionsIntroduce yourself and offer a reflection on the questions: What is your understanding of research? Do you know anything about data management? What do you want to find out today? Do you see a role for librarians in supporting RDM?
  • Research data and RDM
  • Exercise: What are research data? In pairs, list as many types of data as you can, focusing (if appropriate) on the subject areas you support You have 5 minutes
  • What are research data? All manner of things produced in the course of research
  • Defining research data Research data are collected, observed or created, for the purposes of analysis to produce and validate original research results Both analogue and digital materials are data Lab notebooks and software may be classed as data Digital data can be: ― created in a digital form (born digital) ― converted to a digital form (digitised)
  • Types of research data Instrument measurements Experimental observations Still images, video and audio Text documents, spreadsheets, databases Quantitative data (e.g. household survey data) Survey results & interview transcripts Simulation data, models & software Slides, artefacts, specimens, samples Sketches, diaries, lab notebooks …
  • What is data management?“the active management and appraisal of data overthe lifecycle of scholarly and scientific interest” Digital Curation Centre
  • What is involved in RDM? Data Management Planning Creating data Documenting data Create Accessing / using data Preserve Document Storage and backup Sharing data Share Use Preserving data Store
  • RDM principles and adviceto share with researchersn.b. Data Management Planning and Data Sharing arecovered in separate sectionsSee in particular:UK Data Archive, Managing and sharing data: best practice for researchershttp://data-archive.ac.uk/media/2894/managingsharing.pdf
  • Data creation Decide what data will be created and how - this should be communicated to the whole research team Develop procedures for consistency and data quality Choose appropriate software and formats - some are better for long-term preservation and reuse Ensure consent forms, licences and partnership agreements don’t limit options to share data if desired
  • Documentation Collect together all the information users would need to understand and reuse the data Create metadata at the time - it’s hard to do later Use standards where possible Name, structure and version files clearly
  • Access and use Restrict access to those who need to read/edit data Consider the data security implications or where you store data and from which devices you access files Choose appropriate methods to transfer / share data ― filestores & encrypted media rather than email & Dropbox
  • Storage and backup Use managed services where possible e.g. University filestores rather than local or external hard drives Ask the local IT team for advice 3… 2… 1… backup! ― at least 3 copies of a file ― on at least 2 different media ― with at least 1 offsite
  • Data selection It’s not possible to keep everything. Select based on: ― What has to be kept e.g. data underlying publications ― What legally must be destroyed ― What can’t be recreated e.g. environmental recordings ― What is potentially useful to others ― The scientific or historical value ― ...How to select and appraise research data:www.dcc.ac.uk/resources/how-guides/appraise-select-research-data
  • Data preservation Be aware of requirements to preserve data Consult and work with experts in this field Use available subject repositories, data centres and structured databases ― http://databib.org
  • Data Management Planning
  • Data Management PlanningDMPs are written at the start of a project to define: What data will be collected or created? How the data will be documented and described? Where the data will be stored? Who will be responsible for data security and backup? Which data will be shared and/or preserved? How the data will be shared and with whom?
  • Why develop a DMP?DMPs are often submitted with grant applications, butare useful whenever researchers are creating data.They can help researchers to: Make informed decisions to anticipate & avoid problems Avoid duplication, data loss and security breaches Develop procedures early on for consistency Ensure data are accurate, complete, reliable and secure
  • Which funders require a DMP?www.dcc.ac.uk/resources/policy-and-legal/ overview-funders-data-policies
  • What do research funders want? A brief plan submitted in grant applications, and in the case of NERC, a more detailed plan once funded 1-3 sides of A4 as attachment or a section in Je-S form Typically a prose statement covering suggested themes Outline data management and sharing plans, justifying decisions and any limitations
  • Five common themes / questions Description of data to be collected / created (i.e. content, type, format, volume...) Standards / methodologies for data collection & management Ethics and Intellectual Property (highlight any restrictions on data sharing e.g. embargoes, confidentiality) Plans for data sharing and access (i.e. how, when, to whom) Strategy for long-term preservation
  • Exercise: My DMP - a satire Read through the satirical DMP Highlight examples of bad practice Suggest alternative methods / approaches You have 15 minutesMy Data Management Plan – a satire, Dr C. Titus Brownhttp://ivory.idyll.org/blog/data-management.html
  • A useful framework to get started Think about why the questions are being asked Look at examples to get an idea of what to includewww.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/framework.html
  • Help from the DCC https://dmponline.dcc.ac.ukwww.dcc.ac.uk/resources/how-guides/develop-data-plan
  • How DMPonline works Create a plan based on relevant funder / institutional templates......and thenanswer the questions using the guidance provided
  • Supporting researchers with DMPsVarious types of support could be provided by libraries: Guidelines and templates on what to include in plans Example answers, guidance and links to local support A library of successful DMPs to reuse Training courses and guidance websites Tailored consultancy services Online tools (e.g. customised DMPonline)
  • Tips to share: writing DMPs Keep it simple, short and specific Seek advice - consult and collaborate Base plans on available skills and support Make sure implementation is feasible Justify any resources or restrictions neededAlso see: http://www.youtube.com/watch?v=7OJtiA53-Fk
  • Data sharing
  • What is data sharing? “… the practice of making data used for scholarly research available to others.” [Wikipedia]Who’s involved?  the data sharer  the data repository  the secondary data user  support staff!
  • Reasons to share dataBENEFITS DRIVERS Avoid duplication  Public expectations Scientific integrity  Government agenda More collaboration  RCUK Data Policy Better research ― www.rcuk.ac.uk/research/Pages/ DataPolicy.aspx Increased citation  Northampton RDM policy 69% increase shown in study ― http://tiny.cc/Research-Data- (Piwowar, 2007, PLoS) Policy
  • The expectation of public accessThe RCUK Common Principles state that: “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.”
  • Exercise: barriers to data sharing Briefly list some reasons why certain data can’t be shared and consider whether any actions could be taken to reduce or overcome these restrictions You have 10 minutesConstraints on data sharing Possible solutions / approaches
  • Managing restrictions on sharingEthicsBalance data protection with data sharing Informed consent – cover current and future use Confidentiality – is anonymisation appropriate? Access control – who, what, when?IPR Clarify copyright before research starts Consider licensing options e.g. Creative Commons
  • Select formats for data sharingIt’s better to use formats that are: Unencrypted Uncompressed Non-proprietary/patent-encumbered Research360 Open, documented standard Standard representation (ASCII, Unicode) Type Recommended Avoid for data sharingTabular data CSV, TSV, SPSS portable ExcelText Plain text, HTML, RTF Word PDF/A only if layout mattersMedia Container: MP4, Ogg Quicktime Codec: Theora, Dirac, FLAC H264Images TIFF, JPEG2000, PNG GIF, JPGStructured data XML, RDF RDBMS Further examples: http://www.data-archive.ac.uk/create-manage/format/formats-table
  • How to share research data Use appropriate repositories ― http://databib.org License the data so it is clear how it can be reused ― www.dcc.ac.uk/resources/how-guides/license-research-data Make sure it’s clear how to cite the data ― http://www.dcc.ac.uk/resources/how-guides/cite-datasets
  • Skills
  • How are libraries engaging in RDM?The library is leading on most DCC institutional engagements.They are involved in: defining the institutional strategy developing RDM policy delivering training courses helping researchers to write DMPs advising on data sharing and citation setting up data repositories Library ... Researchwww.dcc.ac.uk/community/institutional-engagements Office IT
  • Why should libraries support RDM?RDM requires the input of all support services, butlibraries are taking the lead in the UK – why? ― existing data and open access leadership roles ― often run publication repositories ― have good relationships with researchers ― proven liaison and negotiation skills ― knowledge of information management, metadata etc ― highly relevant skill set
  • Exercise: skills to support RDM Based on the activities we discussed earlier, consider who may have relevant skills or expertise to share. You have 15 minutes Activity Library and IT Services Other professional Learning Services services Copyright Data citation Information literacy Data storage Digital preservation Metadata ...
  • Possible Library RDM roles Leading on local (institutional) data policy Bringing data into undergraduate research-based learning Teaching data literacy to postgraduate students Developing researcher data awareness Providing advice, e.g. on writing DMPs or advice on RDM within a project Explaining the impact of sharing data, and how to cite data Signposting who in the Uni to consult in relation to a particular question Auditing to identify data sets for archiving or RDM needs Developing and managing access to data collections Documenting what datasets an institution has Developing local data curation capacity RDMRose Lite Promoting data reuse by making known what is available
  • An exciting opportunity “Researchers need help to manage their data. This is a really exciting opportunity for libraries….” Liz Lyon, VALA 2012 Leadership Providing tools and support Advocacy and training Developing data informatics capacity & capability
  • Potential challenges Librarians are already over-taxed! ― Other challenges in supporting research (Auckland, 2012) ― Getting up-to-speed and keeping up-to-date How deep is our understanding of research, especially scientific research and our level of subject knowledge? Translating library practices to research data issues Will researchers look to libraries for this support? RDMRose Lite Still need to resource and develop infrastructure
  • RDM at Northampton
  • RDM drivers at Northampton REF: research environment; impact Institutional reputation Pressure from funders: government; RCUK; EPSRC (sharing mandates) Publisher demands: evidence to support published work Legislative requirements: FOI/EIR requests; Data Protection Long term (open) access: reuse and repurpose Good research practice
  • A (very) brief history of RDM at NorthamptonMay-June • First research data (DAF) project aims to establish researchers’ current RDM practices 2010 • DAF project report presented to University Research Committee (URC)October 2010 • URC working group convened to develop research data policyJan-June • Research Data Policy proposed, refined and approved by URC 2011 • Research data roadmap created in response to EPSRC requirementsApril 2012 • DCC ‘engagement starts • RDM training and guidance for researchers – led by DCC, supported by LLSOngoing • Piloting of TUNDRA2 for research data storage and access
  • Northampton RDM policy Adopt the RCUK code of good practice Write and follow a Data Management Plan Make data accessible wherever possible Deposit in a repository for preservation www.northampton.ac.uk/info/20283/academic- research/1606/research-data-policy
  • UoN research data roadmap Maps current and planned practice to EPSRC expectations Covers: awareness of regulatory environment; connection with published papers; access to datasets; use of metadata; and data curation Coverage extended to all subject areas to encourage good data management practice and ensure equality of provision Roadmap approved by R&EC in April 2012 But extra resources still need approval by UET
  • DCC Engagement So far DCC staff have run training sessions on: ― Managing your PhD data (for research students) ― Managing data through the research lifecycle (Business) ― Meeting funders’ requirements for RDM (Social Sciences) And provided guidance: ― Creation of a DMPonline template for the University of Northampton, with attached guidelines ― Development of a guide to meeting ESRC data management planning requirements (in conjunction with John Horton) We have also run one-to-one RDM clinics for researchers Still to come: ― Further training for Schools ― Series of posts on the Research Support Hub ― Further support for research data storage...
  • TUNDRA2 for research data The University (led by Phil Oakman) is rolling out TUNDRA 2 ― open content management system ― to store, manage and preserve files ― facility to share internally and externally Jane Callaghan & colleagues are piloting this for managing research data in her big European project Phil hopes to develop a generic template in TUNDRA2 that will serve other research projects Let us know if you know of others who would like to be involved
  • Exercise: supporting RDM at Northampton? In small groups, discuss which activities you think should fall within your role and which shouldn’t. Do you feel confident to support RDM? How would you like to see things develop? You have 15 minutes
  • Conclusion
  • Summary In the light of external drivers, researchers at Northampton need support for RDM LLS has a key role in shaping services for researchers in this area LLS staff have an opportunity to apply their skills in a new and exciting way 
  • Feedback Has the event met your expectations? ― If not, what would you have liked to see more / less of? Was the content useful? Did you like the mix of exercises?
  • AcknowledgementIdeas and content have been taken from various courses: ― Skills matrix, ADMIRe project, University of Nottingham http://admire.jiscinvolve.org/wp/2012/09/18/rdmnottingham-training-event ― DIY Training Kit for Librarians, University of Edinburgh http://datalib.edina.ac.uk/mantra/libtraining.html ― Managing your research data, Research360, University of Bath http://opus.bath.ac.uk/32296 ― RDMRose Lite, University of Sheffield http://rdmrose.group.shef.ac.uk/?page_id=364 ― RoaDMaP training materials, University of Leeds http://library.leeds.ac.uk/roadmap-project-outputs ― SupportDM modules, University of East London http://www.uel.ac.uk/trad/outputs/resources