ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
Building RDM services: a data librarian's view
1. Building research data management
services:
a data librarian’s view
Robin Rice
Online Information
London: Nov 21, 2012
2. Overview
• Defining research data management
• Developing a Research Data
Management Policy at your institution
• Researcher vs institutional responsibilities
• Supporting and training researchers
• Other candidates for library-based RDM
services
3. Defining RDM
• An umbrella term to describe all aspects
of planning, organising, documenting,
storing sharing, and preserving data.
• It also takes into account issues such as
data protection and confidentiality.
• It provides a framework that supports
researchers and their data throughout the
course of their research and beyond.
4. University of Edinburgh Research
Data Mgmt Policy
• Passed by Senate in May, 2011
• Library-led: developed by committee led
by Library & Collections Director
• Involved academic champions
• Written by ex-DCC consultant
• Deemed ‘aspirational’
• Complimentary to
funders’ policies
6. Roles & Responsibilities
• Who will support your researchers’
planning?
• Who has responsibility during the research
project? Who has archival responsibility?
• Who has rights in the data?
• Are students considered?
7. Tips for policy development
Know the drivers for your own institution.
Practice the art of persuasion.
How big is your kirk? Seek alliances.
Who is your high-level champion?
Agree a style – mandate or enabling?
Postcard from the future: what will it
achieve?
8. Supporting and training
researchers
• Online guidance for academic staff
• Embedding RDM training into
postgraduate programmes (MANTRA)
• Tailored support for Data Mgmt Plans
(customising DMP Online tool)
• Training librarians & IT staff
• Awareness-raising across
schools and departments
12. Training liaison librarians
• DIY training facilitated by data librarians:
Topics:
• Data management planning
• Documenting & organising data
• Data storage & security
• Ethics & copyright
• Data sharing
13. Other candidates for library-based
RDM services
• Data discovery – portals, catalogues
• Open data repositories
• Archiving and preservation services
• Metadata & standards (curation)
16. Archiving and preservation
services for research data
• Should the institution be doing this?
– EPSRC says so
“Research organisations will ensure that EPSRC-funded research
data is securely preserved for a minimum of 10-years from the
date that any researcher ‘privileged access’ period expires or, if
others have accessed the data, from last date on which access
to the data was requested by a third party.”
• How to do digital preservation: “Know what
you’ve got and keep the bits safe.”
• – Tim Gollins, TNA
17. Metadata & standards (curation)
• Librarians are more interested in (at least
some kinds of) metadata than
researchers.
• Librarians are in a position to bring to light
emerging standards for data types to
researchers and benefits of use.
• Librarians have a natural ‘cross-
disciplinary’ viewpoint.
18. Challenges for Librarians in RDM
• Finding time to pursue new activities
• Developing new kinds of partnerships
• Establishing credibility in a new area of
expertise
• Learning new skills; ‘getting techie’
• Getting hands dirty with unpublished
material
• Adapting rapidly to opportunities
19. Links
• University of Edinburgh policy
– http://www.ed.ac.uk/is/research-data-policy
• Research data guidance
– http://www.ed.ac.uk/is/data-management
• MANTRA online training
– http://datalib.edina.ac.uk/mantra/
• UoE Data Library
– http://www.ed.ac.uk/is/data-library
• Edinburgh DataShare
– http://datashare.is.ed.ac.uk/
Edinburgh DataShare is an open repository for any research data created by Edinburgh University researchers, based on DSpace. Datasets are discoverable via search engines in order to maximise visibility and impact. Datasets can be licensed using suitable licences such as those from the Open Data Commons. This provides the facility to fulfil funder mandates when data is required to be published openly. The data submission process creates a permanent record, a persistent identifier, access statistics, and a suggested citation for formal attribution upon re-use. There are customisation options for look and feel (e.g. logos) and metadata fields by community or collection.