UCLA: Data management, governance, and policy issues

Transcription

1 UCLA: Data management, governance, and policy issues Chris<ne L. Borgman Professor &Presiden<al Chair in Informa<on Studies University of California, Los Angeles Informa<on Technology & Planning Board February 19, 2015

2 Data issues for universi<es Research data Publica<on data Community records containing Personally Iden<fiable Informa<on (PII) Personnel records Ins<tu<onal records Student records Data governance

3 Data issues: Faculty concerns Research data Research data management policies Exper<se, cura<on, stewardship, resources Open records laws Human subjects regula<ons Publica<on data Library management Academic personnel records Evalua<on and credit Public- private partnerships Data governance

4 Data issues: Faculty concerns Research data Research data management policies Exper<se, cura<on, stewardship, resources Open records laws Human subjects regula<ons

5 Open access policies Australian Research Council Code for the Responsible Conduct of Research Data management plans Na<onal Science Founda<on Data sharing requirements Data management plans U.S. Federal policy Open access to publica<ons Open access to data European Union European Open Data Challenge OpenAIRE Research Councils of the UK Open access publishing Provisions for access to data 5

6 Responsibility Publica<ons Independent units Authorship is nego<ated Data Compound objects Ownership is rarely clear AZribu<on Long term responsibility: Inves<gators Exper<se for interpreta<on: Data collectors and analysts hudsonalpha.org

7 Credit and azribu<on Legal responsibility Licensing Form of azribu<on specified Ins<tu<on, e.g., human subjects data, patents Library, archive, repository Scholarly credit: contributorship Author of data Contributor of data to this publica<on Colleague who shared data So]ware developer Data collector Instrument builder Data curator / manager / scien<st / steward Field site staff Data calibra<on Data analysis, visualiza<on Funding source Data repository Lab director Principal inves<gator University research office Research subjects Research workers, e.g., ci<zen science 7

8 Metadata Metadata is structured informa<on that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an informa<on resource.* descrip<ve structural administra<ve *Na<onal Informa<on Standards Organiza<on 2004 photo

9 Provenance Libraries: Origin or source Museums: Chain of custody Internet: Provenance is informa<on about en<<es, ac<vi<es, and people involved in producing a piece of data or thing, which can be used to form assessments about its quality, reliability or trustworthiness.* *World Wide Web Consor<um (W3C) Provenance working group Bri<sh Library, provenance record: Bes<ary - cap<on: 'Owl mobbed by smaller birds'

10 Reuse across place and <me Reuse by inves<gator Reuse by collaborators Reuse by colleagues Reuse by unaffiliated others Reuse at later <mes Months Years Decades Centuries hzp://chandra.harvard.edu/photo/2013/kepler/kepler_525.jpg 10

11 Economics of the Knowledge Commons Subtractability / Rivalry Low High Exclusion Difficult Easy Public Goods General knowledge Public domain data Toll or Club Goods Subscrip<on journals Subscrip<on data Common- pool resources Libraries Data archives Private Goods Printed books Raw or compe<<ve data Adapted from C. Hess & E. Ostrom (Eds.), Understanding knowledge as a commons: From theory to prac7ce. MIT Press. 11

12 Data issues: Faculty concerns Publica<on data Library management Academic personnel records Evalua<on and credit Public- private partnerships Data governance

13 Data governance ques<ons How should UCLA collect, organize, and use research analy<cs about our community? Who should have access to these data? Within UCLA? In partnership with public and private en<<es? What are the governance principles? What are the governance processes?

14 Bibliometrics, Scientometrics, Informetrics, Webometrics Ohm, P. (2010). Broken Promises of Privacy: Responding to the Surprising Failure of Anonymiza<on. UCLA Law Review, 57, Borgman, C. L. (2015). Big Data, LiBle Data, No Data: Scholarship in the Networked World. Cambridge MA: MIT Press.

15 Published July 23, 2013; Altmetrics data as of Nov 5, 2014 Altmetrics

16 Mapping Scholarship Börner, K. (2010). Atlas of Science: Visualizing What We Know. Cambridge, Mass: The MIT Press.

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18 Metrics from Open Data

19 Metrics from Open Data Searches for author: Chris;ne Borgman, Chris;ne L. Borgman, CL Borgman (excluding other C Borgman authors) on July 28, 2014 Source Publica<ons Cita<ons received H- index Google Scholar (Google) Web of Science (Thomson- Reuters) Scopus (Elsevier) (a]er 1995)

20 Metrics from Research Informa<on Systems

21 Commercial providers of research analy<cs Providers include Elsevier, Thomson Reuters, Macmillan Digital Science,

22 Big Data, LiZle Data, No Data: Scholarship in the Networked World* Part I: Data and Scholarship Ch 1: Provoca<ons Ch 2: What Are Data? Ch 3: Data Scholarship Ch 4: Data Diversity Part II: Case Studies in Data Scholarship Ch 5: Data Scholarship in the Sciences Ch 6: Data Scholarship in the Social Sciences Ch 7: Data Scholarship in the Humani<es Part III: Data Policy and Prac<ce Ch 8: Releasing, Sharing, and Reusing Data Ch 9: Credit, AZribu<on, and Discovery Ch 10: What to Keep and Why *C. L. Borgman (2015, January) MIT Press 22

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