1. Lifecycle perspectives A “big picture” of research data today Monday, August 9, 2010 1

2. Outline This has been a decade for data! The research lifecycle. The data lifecycle. The data services lifecycle. Distinguishing data from all that is digital. 2

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5. Data’s shameful neglect Nature, September 10, 2009 5

6. Data as an asset One of the most significant changes of the past decade has been the widespread recognition of data as an asset rather than the refuse of research. 6

7. Drivers behind this change Policy Shifts OECD Committee for Scientific and Technological Policy Ministerial Declaration on Access to Research Data from Public Funding, January 30, 2004. Public or open access to research findings and data sharing policies by research councils in the United States (NIH), the UK (BBSRC, ESRC, MRC, NERC) and Canada (CIHR). 7

8. Drivers behind this change Practice Shifts A sea change in digital instrumentation in research and in society. Big science investments in e-science or cyberinfrastructure that capitalize on high-speed networks, grid technology and large data centers. The rising expectation for access to all kinds of data on the Internet. Large-scale investments in digitization projects by the library and heritage sectors. 8

9. Data as an asset As an asset, data need proper management and stewardship to ensure their long-term preservation and access. 9 Data management consists of all activities dealing with data throughout the full research lifecycle. Data stewardship ensures that the roles and responsibilities of those engaged in these activities are clearly identified and known. Data management consists of all activities dealing with data throughout the full research lifecycle. Data stewardship ensures that the roles and responsibilities of those engaged in these activities are clearly identified and known.

10. http://www.jisc.ac.uk/whatwedo/ campaigns/res3/jischelp.aspx Joint Information Systems Committee (JISC)

11. http://www.jisc.ac.uk/whatwedo/ campaigns/res3/jischelp.aspx Joint Information Systems Committee (JISC) Data deposit

12. Lifecycle management The research lifecycle is a representation of the activities that occur throughout a research project. Grouped into sequential steps or stages, they cover everything from conceptualization to knowledge transfer. Each stage consists of a set of related activities that culminate in a significant product or outcome that is then passed to the next stage. By linking together a series of stages in a logical sequence, the research process is described. Within the research lifecycle, several stages involve the production and management of data and metadata. 12

13. Lifecycle management As with any project management operation, the views of a project vary depending on the granularity at which activities are described. Similarly, the stages in the research lifecycle can be aggregated or disaggregated into larger or smaller groupings, depending on the viewpoint one desires. Keep these points in mind while examining the following lifecycle representations. Now let’s move from a research lifecycle to a data lifecycle. 13

14. Data lifecycle 14 http://www.iassistdata.org/files/images/DDIlifecycle.jpg

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16. 16 http://www.dcc.ac.uk/lifecycle-model/

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19. This table lists changes to the stages in the DCC model, re-aggregating activities in the lifecycle to create a data services viewpoint. DCCData service create or receive data production appraisal and select dissemination ingest, store, access and use data repository discovery transformrepurpose 19

20. Data services lifecycle 20 Data Repurposing Data Production Data Repository Data Dissemination Data Discovery

21. Lifecycle contributions Lifecycle management can help in preparing a data management plan that will ensure the research process is well documented. This includes using standardized metadata to drive many of the tasks throughout the research process and to facilitate access to the data and its submission for preservation. Lifecycle management also can help identify those individuals or groups who have responsibilities across the stages of the research process. The essence of data stewardship is identifying the persons or agencies with responsibilities for data throughout the research process. 21

22. Research Data “Is everything that is digital also data?” This was a question raised during the Canadian National Data Archive Consultation in 2001. 22 “By research data, we are referring to digital information that has been structured by methodology for the purpose of producing new knowledge.” National Data Archive Consultation: Phase One Needs Assessment Report. Social Sciences and Humanities Research Council. 2001. “By research data, we are referring to digital information that has been structured by methodology for the purpose of producing new knowledge.” National Data Archive Consultation: Phase One Needs Assessment Report. Social Sciences and Humanities Research Council. 2001.

23. http://www.jisc.ac.uk/whatwedo/ campaigns/res3/jischelp.aspx Joint Information Systems Committee (JISC) Data deposit Observe, experiment, compute Observe, experiment, compute

24. Methods of producing data 24 Observational Methods Experimental Methods Computational Methods Focus is on developing observational instruments to collect data Focus is on manipulating causal agents to measure change in a response agent Focus is on modeling phenomena through mathematical equations CorrelationCausationPrediction Replicate the analysis (same data or similar) Replicate the experimentReplicate the simulation Statistics summarize observations Statistics summarize experiment results Statistics summarize simulation results C. Humphrey, Winter Institute on Statistical Literacy for Librarians. Download from Day 1, Session Powerpoint at http://datalib.library.ualberta.ca/wisll/downloads/Downloads.html

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27. Take a break! When we come back… we’ll discuss social science data. 27