Research data management from an institutional perspective Professor K. Schürer Pro-Vice Chancellor, Research and Enterpri...
Why is it important for Universities to manage research data? <ul><li>To fulfil legal obligations </li></ul><ul><ul><ul><u...
How can one implement a University-wide approach to RDM? <ul><li>With difficulty </li></ul><ul><ul><ul><ul><li>and with JI...
Challenges for institutions (#1) <ul><li>Ownership and responsibility </li></ul><ul><ul><ul><ul><li>Needs to be more mains...
Challenges for institutions (#2) <ul><li>Need researchers to take their share of the responsibility in life cycle research...
Upcoming SlideShare
Loading in …5
×

Kevin Schurer - The institutional perspective on managing research data

874 views
822 views

Published on

Professor Kevin Schurer's keynote presentation at the JISC Research Integrity Conference.

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
874
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Kevin Schurer - The institutional perspective on managing research data

  1. 1. Research data management from an institutional perspective Professor K. Schürer Pro-Vice Chancellor, Research and Enterprise University of Leicester www.le.ac.uk JISC Research Integrity Conference The Importance of good data management 13 September 2011
  2. 2. Why is it important for Universities to manage research data? <ul><li>To fulfil legal obligations </li></ul><ul><ul><ul><ul><li>Research award contracts </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Stationary requirements </li></ul></ul></ul></ul><ul><li>To fulfil moral obligations </li></ul><ul><li>Minimise exposure to risk </li></ul><ul><li>Maximise value, benefit & investment </li></ul><ul><li>REF </li></ul><ul><li>But not just research data </li></ul>
  3. 3. How can one implement a University-wide approach to RDM? <ul><li>With difficulty </li></ul><ul><ul><ul><ul><li>and with JISC’s help </li></ul></ul></ul></ul><ul><li>Coming together of factors and different drivers </li></ul><ul><ul><ul><ul><li>IT driven- e.g. storage, fragmentation </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Research driver – e.g. access, accountability </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Information Management driven- library, registry services </li></ul></ul></ul></ul><ul><li>But often too bottom up, not enough top down- need to balance </li></ul><ul><li>Do not re-invent wheels </li></ul><ul><ul><ul><ul><li>Learn from others </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Share - use data centres etc </li></ul></ul></ul></ul>
  4. 4. Challenges for institutions (#1) <ul><li>Ownership and responsibility </li></ul><ul><ul><ul><ul><li>Needs to be more mainstream </li></ul></ul></ul></ul><ul><li>Little sense of what data archiving and preservation are as opposed to storage </li></ul><ul><ul><ul><ul><li>No real concept of appraisal </li></ul></ul></ul></ul><ul><li>Little sense of resource implications </li></ul><ul><li>Need to separate infrastructure (IT) from processes (data management) </li></ul>
  5. 5. Challenges for institutions (#2) <ul><li>Need researchers to take their share of the responsibility in life cycle research data management </li></ul><ul><ul><ul><ul><li>all sticks, no carrots and not enough sticks </li></ul></ul></ul></ul><ul><li>Not all research RC/publically funded, and ratio will change </li></ul><ul><li>Not all institutions are the same </li></ul><ul><ul><ul><ul><li>At different stages of journey - different data mix </li></ul></ul></ul></ul>

×