Data Management Planning at the DCC: a human factor
1. Data Management Planning
at the DCC: a human factor
Martin Donnelly
Digital Curation Centre
University of Edinburgh
FBA one-day workshop
King’s College London
14 February 2012
2. Running order
- About the DCC
- The DCC and data management planning
– Resources
– Collaborations
- DMP basics
- Checklist for a Data Management Plan
– Stages
– Sections
- DMP Online
– Functions
– Connections
– v3.0 (coming soon)
- Contacts and resources
3. The Digital Curation Centre
- Founded in 2004
- Mission to support the UK research
community in the management and curation
of digital resources, with a special focus on
research data
- Three partner organisations: Edinburgh,
Glasgow and Bath
- Primary funder is JISC
4. DCC and DMP
We became involved in response to increasingly prescriptive
data requirements…
– “Dealing with Data” (Lyon, 2008)
– Analysis of Funder Policies (Jones, 2009)
– Checklist for a Data Management Plan (Donnelly
and Jones, 2009)
– DMP Online (Donnelly, Pattenden-Fail and
Richardson, 2009-2012)
– “Data Management Plans and Planning”
(Donnelly, 2012) in Pryor (ed.) Managing
Research Data, London: Facet
Links to all DCC resources via http://www.dcc.ac.uk/resources/data-management-plans
5. Other resources
Jones, S. (2011). „How to Develop a Data
Management and Sharing Plan‟.
DCC How-to Guides. Edinburgh: Digital
Curation Centre.
Links to all DCC resources at www.dcc.ac.uk
6. Collaborations
- Generic data management guidance
( in conjunction with )
- Funder-specific guidance developed in collaboration
with the funders themselves
- Institution-specific guidance developed with key
institutional contacts
- Discipline-specific guidance developed and deployed
with JISC MRD projects (e.g. DMT Psych at York)
- Joint training programmes organised and delivered
by DCC and UKDA
- Provided advice to US consortium
7. “Dealing with Data”
JISC consultancy report...
REC 9. Each funded research project
should submit a structured Data
Management Plan for peer-review as
an integral part of the application for
funding. (1, 2)
http://www.ukoln.ac.uk/ukoln/staff/e.j.lyo
n/publications.html#2007-06-19
8. Why?
Why plan data management? The 5 Ps...
Perfect Planning Prevents Poor Performance
Data management is a journey with
multiple drivers /stakeholders, from
researchers to support staff to
curators to long-term data centres:
each of these has to follow the same
map in order to mitigate the risk of not
getting there.
9. Contributing Factors for Data
Management (Planning)
- Economic constraints
- Need for commonality in best practice
- “The nature of the beast...”
10. Research
Support Office Data Library / Repository / Archive
Researcher(s)
DATA
MANAGEMENT
PLAN
UNRULY
DATA
Computing Faculty Ethics
Support Etc...
Committee
11. The limits of planning
What can a plan not do?
It can‟t do the work for you.
The map is not the territory (Korzybski)
or
Chalk’s no shears (Scottish saying)
It is important to remember that the human challenges
in data management are often more difficult to meet
than the technological ones. Communication is vital.
12. A comprehensive checklist…
We pulled together a list of all the UK funders‟ requirements,
gathered them into thematic groups, and supplemented this
list with our own expertise... (Donnelly & Jones, 2009)
This became the first „Data Management Plan Content
Checklist‟ (Checklist v1.0‟) – it had 51 questions/headings.
(Post-consultation, v2.0 had 115 questions/headings.)
13. Stages of a Data Management Plan
We mapped our Checklist questions to each funder‟s data-
related requirements, and determined three key stages...
14. Stages of a Data Management Plan
1. Research conceptualisation / funding application
2. In-project (potentially multiple iterations)
3. Post-project / longer-term preservation
Remember, each stage will involve different
stakeholders and emphases…
15. The Checklist, Section by Section
The DMP Checklist
(Donnelly/Jones) is the underlying
intellectual framework which
supports all of the DCC‟s data
management planning work.
It is arranged into 10 sections, and
aims to be comprehensive.
The next part of this talk gives an overview of these
sections, with a little commentary from me on who
might be involved in filling them in...
16. Checklist Headings
§1: Introduction and Context
§2: Data Types, Formats, Standards and
Capture Methods
§3: Ethics and Intellectual Property
§4: Access, Data Sharing and Re-use
§5: Short-Term Storage and Data
Management
§6: Deposit and Long-Term Preservation
§7: Resourcing Checklist for a Data Management
Plan v3.0 (Donnelly and Jones,
§8: Adherence and Review March 2011)
§9: Agreement/Ratification by
Stakeholders
§10: Annexes
17. §1: Introduction and Context
What?
Basic project and administrative information
Aims and purpose of the research
Relevant policies (institutional, departmental, funder-
specific...)
Who?
Researcher(s)
Research support officers
18. §2: Data Types, Formats, Standards and Capture
Methods
What?
Data (and metadata) specifics
New and existing data
Justifications of decisions
Who?
Researcher(s)
Technicians
Librarians / Data Centre staff?
19. §3: Ethics and Intellectual Property
What?
Ethical and privacy issues (inc. Data Protection Act)
Ownership of datasets
Licensing of datasets
Who?
Researcher(s)
Faculty ethics committees
Institutional legal/IP advisors
20. §4: Access, Data Sharing and Re-use
What?
Plans for sharing data / making accessible
Freedom of Information
Re-use expectations
Embargoes, publications etc
Who?
Researcher(s)
FOI officer / records manager
Data centres
21. §5: Short-Term Storage and Data Management
What?
In-project data management specifics
Storage media
Backups
Security
Who?
Researcher(s)
Computing support
23. §7: Resourcing
What?
Roles and responsibilities for implementation
Funding (in-project and post-project)
Who?
Researcher(s)
Funder
Institutional staff
Archive / data repository
24. §8: Adherence and Review
What?
Roles and responsibilities
Timetable for review / versioning
Who?
Researcher(s)
Funder
Institutional staff
25. §9: Agreement/Ratification by Stakeholders
What?
Statement of agreement (N.B. This is optional)
Who?
Relevant level of authority/seniority
26. §10: Annexes
What?
Contact details and expertise of named individuals
Glossary of terms
Other annexes as required
Who?
Project staff
Others will depend on content
27. Checklist: last words
N.B.
All research projects are different
The DMP will depend upon the nature of
the research AND the context (funder,
domain, institution(s) etc)
DMPs are both metadata and
communication tools
29. What does it do?
DMP Online is a web-based tool that enables users to...
i. Create, store and update multiple versions of Data
Management Plans at the application and in-
project stages
ii. Meet funders‟ specific data-related requirements*
iii. Get funder- and institution-specific guidance on
best practice and helpful contacts, at the point of
need
iv. Customise and export DMPs in a variety of formats
* Disclaimer: mappings are not yet fully endorsed by funders, but we‟re
working on it...
30. Connections
DMP Online can also be used in conjunction
with other tools that support the data
management/curation lifecycle, e.g.…
- DAF (Data Asset Framework)
- DRAMBORA (Digital Repository Audit Method
Based On Risk Assessment)
- CARDIO (Collaborative Assessment of
Research Data Infrastructure and Objectives)
Also non-DCC tools:
- LIFE
- Planets tools
- and more
31. Coming Soon: DMP Online v3.0
- Improved user interface
- New features
- Overlaying multiple (‘hybrid’) templates
- Template phases (e.g. pre, during, post)
- Granular read/write/share permissions
- API for systems interoperability
- Endorsement from funders
- Launching Spring 2012
32.
33. To sum...
All of our DMP-related resources available online via:
www.dcc.ac.uk/dmponline/
34. Thank you
Martin Donnelly
Digital Curation Centre
University of Edinburgh
www.dcc.ac.uk/dmponline
martin.donnelly@ed.ac.uk
Twitter: @mkdDCC
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Editor's Notes
Research is more than the sum of its parts, and data management planning is primarily about communication for ensuring smooth and accurate interactions