DATA MANAGEMENT PLAN ADVISING? A NEW BUSINESS VENTURE FOR LIBRARIES

Andrew Sallans

Head of Strategic Data Initiatives

Special Libraries Association

15 June 2011

“SCIENTISTS SEEKING NSF FUNDING WILL SOON BE

REQUIRED TO SUBMIT DATA MANAGEMENT PLANS”Press Release 10-077, May 5, 2010

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Policy prior to January 18, 2011:

o “To advance science by encouraging data sharing among researchers”

o Data obtained with federal funds be accessible to the general public

o Grantees must develop and submit specific plans to share materials collected with NSF support, except where this is inappropriate or impossible

Policy after January 18, 2011:

o All new NSF proposals will be required to include a data management plan in the form of a 2 pg supplementary document (peer reviewed)

o New policy is meant to be a 1st step toward a more comprehensive approach to data management

o Exact requirements vague, scientific communities will specify

THE CHALLENGE FOR INSTITUTIONS

Data is expensive

Time, instrumentation, inability to reproduce

Increasing regulation

Granting agencies and journals require

submission

Inadequate training

No formal data management curriculum

Preservation of data is not a priority

For most researchers, preservation takes time

away from the work that is rewarded

(publication, teaching) 3

SO…WHO’S GOING TO TAKE THIS ON?

Researchers?

Research Office?

Central IT?

Sponsored Research?

University Library?

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WHY THE LIBRARY? A FEW POINTS…

Neutral: works across the entire institution

Strong in relationship building: has

experience fostering discussion and relationships,

and cultivates an existing support network

Intellectual Property expertise: has dealt

with copyright, can translate to data

Service-oriented: uniquely positioned as an

intellectual service unit within the institution

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THREE POINT SERVICE STRATEGY

1. Assessment through data interviews

2. Planning through DMPs

3. Implementation support

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POINT 1 – DATA ASSESSMENT INTERVIEWS

Growing awareness of consulting service

Broad assessment

Baseline of research data management practices

Protocol involves:

60 minute interview discussion (researcher / SciDaCconsultants / subject librarian)

Development of a report

SciDaC consultants give researchers improvement recommendations and plan

SciDaC consultants work with researchers to implement recommended solutions

Based on Data Asset Framework, Data CurationProfile, and other similar assessment tools 7

POINT 2 – DATA MANAGEMENT PLANNING

Funding agency requirements - highest

priority of responding to and addressing support

needs (ie. NSF, others)

Risk management – identifying opportunities

to improve data management practices as a

means of institutional risk management

Coordination of effort across institution –

Library as leader, coordinates between VPR,

CIO, OSP, schools/colleges, etc.

Boilerplate versus customized – a balance of

generic, institutional DMPs versus boutique and

focused only on the project 8

POINT 3 –IMPLEMENTATION SUPPORT

Institutional repository “Libra” (http://libra.virginia.edu)

Built upon Hydra architecture

Three components: open access publications, data, and electronic theses/dissertations

Working on figuring out storage and cost models to support management of big and small data from across institution’s research community

Consulting with researchers on how to implement the data management plans for their projects

Serving as a bridge between the many silos of the institution, with competency in the many areas of research data management

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AN INSIDE VIEW OF DATA MANAGEMENT PLANS

Consulted on 14 data management plan (DMP) proposals (since 1/18)

DMPs included the following areas: Biology (3)

Chemical Engineering (2)

Civil Engineering (1)

Computer Science (1)

Education (2)

Electrical Engineering (3)

Environmental Science (2)

Gained feedback and insight of reviewing practices on first submitted DMP

Development of templates that associate NSF directorate requirements with available resources and support services to streamline plan development and allow researchers to make informed decisions on a tight schedule (currently 7 templates)

The bigger picture: a multi-institution, international collaboration to develop web-based DMP authoring tool that:

1. Streamlines DMP development

2. Associates researchers with support resources 10

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CHALLENGES AHEAD…

Time: how to best manage staff time NSF research support alone is going to be very time

consuming (UVA had about 140 proposals over the past year, 44 in November alone)

Funding: work with leaders to find sources Make the case

Explore the options

Test the feasibility

Strategy: decide how to invest How might units be reorganized?

How do we expand to other disciplines?

How could staff resources and expertise be refocused?

What additional partnerships would add value?12

THANK YOU!

Andrew Sallans

Head of Strategic Data Initiatives, SciDaC Group

University of Virginia Library

Email: als9q@virginia.edu

Twitter: asallans

http://www.lib.virginia.edu/brown/data

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