Data and Access: Views from a Research Administrator ( and recovering meteorologist)

1. Data and Access: Views from a Research Administrator (and recovering meteorologist) Kelvin K. Droegemeier Vice President for Research University of Oklahoma UNT 3rd Annual Symposium on Open Access May 20-21, 2012

2. A HUGE Spectrum Zillions of small data; ubiquitous, streaming,unexpected, highly perishable, non-reproducible, geo-referenced, mobile Huge structured data;anticipated, well defined, streaming, fixed in space,reproducible

3. Lots of Reports and ActivitiesLots of Dust in the Air

4. The Easy Way Out?

5. Some of the Key Questions • Definition of DATA • Who owns it and when, and who decides? • What should be kept and who decides? • How and where should it be kept and who decides? • How is quality assured and who determines it? • Who provides access and who pays? • How is access provided and who decides? • Who is given access and when, and who decides? • When should access be denied and who decides? • Who provides technical assistance in using data? • How should credit be given for generating/maintaining data, and who decides? • Who ensures and pays for compliance?

6. Data: The Way it Was • Federal research agencies and laboratories • Money for research • Big iron • High capacity network backbone • Lots of storage • Special large and shared facilities (telescopes, ships, aircraft, accelerators) • Little compliance or policy apart from health-related information • Focus on physical science and engineering • Universities • Researchers (faculty, students, post docs) • Modest computing for data analysis and visualization • Links to backbone plus modest on-campus connectivity • Some storage • Coordination at department/college level with distributed IT management

7. Data: The Way It’s Becoming • Federal research agencies and laboratories • Money for research • Big iron • High capacity network backbone • Lots of storage • Special large and shared facilities (telescopes, ships, aircraft, accelerators) • Significant compliance mandates, data management plans, IP implications • ALL disciplines now involved in data in VERY different ways! • Universities • Researchers (faculty, students, post docs) • Significant computing for data analysis and visualization • Links to backbone plus significant wired/wireless on-campus connectivity • Large storage • Local digital repositories • Components of data systems for federated data bases • Emerging interaction among Library, IT Leadership, Research Office, Academic Leadership at the institutional level

8. My Role as VP for Research • Assist faculty across all disciplines within a comprehensive research university in achieving their scholarly goals and dreams • Help locate and create opportunity • Help build collaborations internally and externally • Help define research program trajectories and prepare competitive proposals • Provide financial and other resources • Create incentives and rewards • Promulgate useful policies and reduce administrative burden • Ensure tight integration of instruction and research • Shine a bright light on achievement • Recruit and retain the best faculty and students – to continue the cycle

9. View from a Vice President for Research • Key Point #1: Facilitating Research With Data • A means to tackle some of the most compelling intellectual challenges at the intersections of multiple disciplines • It’s not only about providing access but also helping ensure EFFECTIVE use of data – which is not automatic! • The institution must help: bring people together, stimulate conversations, bridge language barriers, build trust, guide thinking, provide support • Library has a unique role to play – a renaissance as the intellectual commons of our campuses • As IT has opened new doors and brought people/disciplines together, so can the “data challenge” if we handle it properly! • Especially critical for engagement of social sciences and the humanities

10. Are All the Data Making a Difference?

11. Are All the Data Making a Difference?

12. Data Don’t Guarantee Understanding! Numerical Simulation 24 hours CPU = 1 hour real 20 TB of output Still trying to understand Mother Nature Real time! Still trying to understand

13. View from a Vice President for Research • Key Point #2: Providing Credit and Support • System (but importantly also a philosophy) for giving credit to faculty for generating, maintaining, and provisioning data (similar to how IP has been added to portfolio) • Provost, Deans, Tenure Committees, Senior Faculty • Building data stewardship into research metrics aka citations, impact factors, etc • Creation of persistent identifiers/tags (EZID, DataCiteConsortium) – but also WHAT credit means • Creation of an indirect cost component for data and compliance

14. View from a Vice President for Research • Key Point #3: Logistics and Cost • Coordination and consolidation of data management approaches across the institution: Provost, Library Dean, CIO, VPR • Appropriate cyberinfrastructure, security, systems-level approach • Integration into the broader academic ecosystem • The strategies in which we invest today may be quite different in a short time – shifting sands • Division of responsibilities (local and national) • When will the dust settle regarding policies? • Unity versus diversity in approaches • Roles from Fran Berman’s recent article • Universities: Expand repositories (pay via fees, gifts, tuition, grants) • Agencies: Research, workforce, repositories, good policies • Private Sector: Capacity and services, partnerships, federation

15. View from a Vice President for Research • Strategy for OU • Just hired a new Dean of Libraries (Rick Luce) • Bringing in a blue ribbon visiting team to evaluate IT support of research in its broadest definition • Data issue is a key component of the agenda • Like some universities, OU doesn’t have a lot to “undo” in the way of a unified approach to data management • New coordination among Library Dean, CIO, Provost, VPR

16. Closing Thoughts • Like so many things in our world, our ability to generate data has far outstripped our ability to utilize them effectively for research and decision making • In our necessary haste to make data available, we must also learn how to use data effectively • We’re now somewhat in a valley – data deluge has slowed progress in some ways and accelerated it in others • Some of the greatest advances in the history of civilization will be made in the next 50 years provided we can tackle the data challenge holistically (i.e., provision, effective use)