when and why should research data be sustained? national science foundation workshop...
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When and Why Should Research Data be Sustained?
National Science Foundation WorkshopCyberinfrastructure for Large FacilitiesDecember 1-2, 2015
Christine L. BorgmanDistinguished Professor & Presidential Chair in Information StudiesUniversity of California, Los [email protected]
Center for Knowledge Infrastructureshttps://knowledgeinfrastructures.gseis.ucla.edu/
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Open Data: OECD criteria• Openness • flexibility • transparency• legal conformity • protection of intellectual property • formal responsibility • professionalism • interoperability • quality• security • efficiency • accountability • sustainability 2
Organization for Economic Cooperation and Development (2007)http://www.oecd.org/science/sci-tech/38500813.pdf
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• Purposes– Record of observations– Reference– Reproducibility of research– Aggregation from multiple sources
• Users– Investigator– Collaborators– Unaffiliated or unknown others
• Time frame– Months– Years– Decades– Centuries http://chandra.harvard.edu/photo/2013/kepler/kepler_525.jpg
Why sustain access to data?
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Simplifying the Challenge
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5http://www.datameer.com/product/hadoop.html
Big Data
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Long tail of dataVo
lum
e of
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Number of researchers
Slide: The Institute for Empowering Long Tail Research 6
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Big Science <–> Little Science
• Large instruments• High cost• Long duration• Many collaborators• Distributed work• Centralized data
collection
• Small instruments• Low cost• Short duration• Small teams• Local work• Decentralized data
collection
7Sloan Digital Sky Survey
Sensor networks for science
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How to sustain data?• Identify the form and content• Identify related objects• Interpret• Evaluate• Open• Read• Compute upon• Reuse• Combine• Describe• Annotate… 8Image from Soumitri Varadarajan blog. Iceberg image © Ralph A. Clevenger. Flickr photo
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When to invest in data?
9http://www.lib.uci.edu/dss/images/lifecycle.jpg
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When to invest in data?
10http://www.finance.umich.edu/programs
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Economics of the Knowledge Commons
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Subtractability / Rivalry
Low High
Exclusion Difficult Public GoodsGeneral knowledgePublic domain data
Common-pool resourcesLibrariesData archives
Easy Toll or Club GoodsSubscription journalsSubscription data
Private GoodsPrinted booksRaw or competitive data
Adapted from C. Hess & E. Ostrom (Eds.), Understanding knowledge as a commons: From theory to practice. MIT Press.
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C.L. Borgman (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press
http://www.genome.gov/dmd/img.cfm?node=Photos/Graphics&id=85327
Data are representations of observations, objects, or other entities used as evidence of phenomena for the purposes of research or scholarship.