Research Data Management for librarians

Research Data Management
for Support Staff
Jonathan Rans & Kerry Miller, Digital Curation Centre
About this course
 Short presentations with exercises and discussion
 Five main sections
Research data and RDM (30 mins)
RDM at Surrey (15 mins)
Skills exercise
Data Management Planning (30 mins)
Data sharing (30 mins)
Breakout sessions –
 Practical DMP support or Metadata and Documentation
 Lunch @ 13:30
Introduce 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?
 How do you see yourself supporting RDM?
Research data and RDM
So, what is meant by ‘research data’?
Anything & everything
produced in the course of
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 over the
lifecycle of scholarly and scientific interest”
Digital Curation Centre
What is involved in research data
management (RDM)?
 Data Management Planning
 Creating data
 Documenting data
 Accessing / using data
 Storage and backup
 Sharing data
 Preserving data
What do research funders expect?
RDM principles and advice
to share with researchers
n.b. Data Management Planning and Data Sharing are
covered in separate sections
See in particular:
UK Data Archive, Managing and sharing data: best practice for researchers
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
 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 of 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. Surrey shared
drives 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 – or desirable - 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
Guidance on selection and appraisal
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
How are support staff engaging in RDM?
Defining institutional strategy and policy
Implementing infrastructure
Advising researchers
Developing and delivering training
Supporting data management planning
Supporting data sharing
When does RDM engagement happen?
Responding to researcher requests
Institutional support projects
Fulfilling funder requirements
FOI requests
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
Data Citation
Information Literacy
Data Storage
Digital Preservation
The Library
Enterprise Services
Other Research
Support Services
 This Training has been adapted from the RDM for
Librarians course created jointly by the DCC and the
University of Northampton. Full details at:
Ideas and content have been taken from various courses:
 Skills matrix, ADMIRe project, University of Nottingham
 DIY Training Kit for Librarians, University of Edinburgh
 Managing your research data, Research360, University of Bath
 RDMRose Lite, University of Sheffield
 RoaDMaP training materials, University of Leeds
 SupportDM modules, University of East London

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