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Meeting the NSF Data Management Plan Requirement Indiana Forum for Research Administrators August 9, 2012.

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Presentation on theme: "Meeting the NSF Data Management Plan Requirement Indiana Forum for Research Administrators August 9, 2012."— Presentation transcript:

1 Meeting the NSF Data Management Plan Requirement Indiana Forum for Research Administrators August 9, 2012

2 My life as a researcher Research Assistant (1997-1999) Lab Coordinator (2002-2006) Clinical Research Coordinator (2006-2010; certified by SoCRA 2008) Graduate Student PI (2009-2010) Faculty PI (2011-present) My life as a researcher Research Assistant (1997-1999) Lab Coordinator (2002-2006) Clinical Research Coordinator (2006-2010; certified by SoCRA 2008) Graduate Student PI (2009-2010) Faculty PI (2011-present) Who am I? Heather Coates Digital Scholarship & Data Management Librarian IUPUI University Library IFRA: August 9, 2012

3 Responsible Conduct of Research Digital preservation Scholarly communication IFRA: August 9, 2012 DATA

4 DATA researchers librarians/ies research administration IT publishers students journalists institutions funding agencies consumers/ patients policy-makers commercial enterprises data centers Standards agencies

5 IFRA: August 9, 2012 Cyberinfrastructure: computing resources & networks, services, & people (Empowering People IU Strategic Plan, 2009) Data management: technical processing and preparation of data for analysis Data curation: selection of data for preservation and adding value for current and future use Data citation: mechanisms enabling easy reuse and verification, track impact of data, and create structures to recognize and reward researchers (DataCite) Data sharing: making data available beyond individual request; a spectrum with many options Data stewardship: responsibility to ensure knowledgeable and appropriate use of data; core concept is accountability

6 Responsible Conduct of Research IFRA: August 9, 2012

7 Where does data fit in? Data management practices: 1 of 9 essential areas of the Responsible Conduct of Research (Office of Research Integrity The way data is collected, processed, and managed affects validity and integrity IFRA: August 9, 2012

8 Data ownership: legal rights during and after project is completed (includes access and control) Data collection: consistent, systematic method (reliability) and ongoing system for evaluating and recording changes (validity) Data storage: amount of data needed to reconstruct results Data protection: protecting from physical damage, protecting data integrity Data retention: length of time to keep data; secure destruction Data analysis: how raw data are chosen, evaluated, and interpreted Data sharing: how project data and research results are disseminated to researchers and general public Data Reporting: publication of conclusive findings IFRA: August 9, 2012

9 Data Producers Goal: scientific discovery Data acquisition and reduction Data visualization, integration, and interpretation Scientific standards Limitations Documentation is variable and time consuming Data Consumers Goal: data discovery Data discoverability and access Cross-disciplinary Scientific standards Interpretation Documentation is key for: – assuring data integrity and validity – preventing misuse IFRA: August 9, 2012 Data Providers Goal: data access, preservation, re- use Data formats and standards Documentation and preservation Scientific and Metadata standards Data citation Interoperability and Linked Data Users/Usability Promote access

10 @ IUPUI University Library Data Services Group – Working with specific graduate courses and programs to provide data management and other training with holistic view of RCR Research, Education, Ethics, Policy (ORA) – CITI modules: NSF & NIH RCR requirements IFRA: August 9, 2012

11 Scholarly Communications IFRA: August 9, 2012

12 Source:

13 Where does data fit in? Scientific record Scientific process – Reproducibility – Replicability Publication (reward mechanism, currency) – Traditional model – Open access – Data citation IFRA: August 9, 2012

14 @ IUPUI University Library Data Services Program – Incorporating mechanisms for data citation in our data repository – Helping faculty include impact of research data in their P&T dossiers UITS – Create systems to support data preservation and sharing Faculty Affairs, Faculty Council, Deans, Chairs – Recognize data as a valuable scholarly product IFRA: August 9, 2012

15 Digital Preservation IFRA: August 9, 2012

16 Where does data fit in? IFRA: August 9, 2012 Ensuring that future generations have access to the foundation (data) of the scholarly record that informs their understanding of the world.

17 Keep it safe, make it findable, make it usable Maintaining the scholarly record Planning for persistent access (100+ years) If we can’t find it, it doesn’t exist What does preservation mean? IFRA: August 9, 2012

18 Data sharing is a spectrum, not an all-or-none decision Preservation is a prerequisite Selection and preparation of data Preparing sufficient and accurate documentation Implementing mechanisms of dissemination and reward What does sharing entail? IFRA: August 9, 2012

19 NSF Data Management Plan Requirement IFRA: August 9, 2012

20 Incremental steps towards openness – National Research Council, 1985 – Office of Management & Budget, 1999: Circular A-110 Circular A-110 – NIH Data Sharing Policy, 2003 – NIH Public Access Policy, 2008 – NSF DMP Requirement, 2011 – Other policies: NEH, NOAA, NASA, Howard Hughes Medical Institute Wellcome Trust Other Federal Policies IFRA: August 9, 2012

21 WHY?

22 Types, format, etc. Organization, storage, back-up Data Metadata & documentation Standards Permissions & restrictions Who, when, how Sharing Re-use, re-distribution, and production of derivatives Re… Long-term (25, 50, 100 years) discoverability, accessibility, usability Preservation IFRA: August 9, 2012

23 Saves time Increases efficiency Prevents data loss Makes preservation easier It’s required! Benefits of planning IFRA: August 9, 2012

24 A DMP should describe what researchers will do with their data during and after the proposed project. Demonstrate awareness of issues and be feasible Explain the rationale for decisions Identify roles for data management and preservation activities Remember: the DMP is an imperfect working document NSF expects progress to be reported In plain English, please IFRA: August 9, 2012


26 Key players Libraries Research Administration – OVPR/OVCR – Research & Sponsored Programs – Compliance units: IRB, C&G CIO & IT units Informatics/computing science/information science research groups Statistics research/service groups Other survey and policy research groups IFRA: August 9, 2012

27 ARL survey: E-Science support 61 respondents of 125 member institutions; conducted in 2009 4 (9%) report primarily institution-wide approach 11 (25%) report highly decentralized structures/approaches (ex: MIT, Purdue) 27 (61%) report a hybrid approach to supporting e-Science 20 of 41 (49%) report collaborating with other institutions; often result of grants 23 of 42 (55%) institutions indicated that there were no designated units to provide data curation and support for scientific research data on their campus 19 institutions (45%) identified the presence of designated unit(s) 73% of the respondents (29 of 40) indicated the library involvement; 87% (27 of 31) noted that their e-science services were provided in collaboration with at least one other unit on campus, with a majority of those being the centralized IT unit IFRA: August 9, 2012

28 Purdue IUPUI IUB Notre Dame UI @ UC

29 discovery, access, preservation Trusted member of the institution Organizational structure lends itself to collaboration with researchers Interdisciplinary by nature Existing infrastructure for digital information Existing expertise in enabling discovery, access, and preserving information Why the library? IFRA: August 9, 2012

30 University Library @ IUPUI Data Services Program – Pilot projects to learn about needs, capacity, processes – The future…the Wild, Wild West IUPUIDataWorks – Institutional repository for preserving and sharing data – Focus on “small science” data (the long tail) IFRA: August 9, 2012

31 THE END IFRA: August 9, 2012

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