The Local Goes Global
description
Transcript of The Local Goes Global
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Ann Zimmerman1075 Beal Ave.Ann Arbor, MI 48109-2112asz@@umich.edu
The Local Goes GlobalHow do data come to be shared?
Ann ZimmermanResearch Assistant Professor
ASIST Data Summit, April 10, 2010
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Data collections
•Research•Community•Reference
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Local project
Share Publish Create Reference Collection
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
• Why is it hard to share data?
• Why is data sharing more common in some fields than others?
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Science-based
Technical
Organizational
Social
Legal
Political
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Implications
• Who is involved
• What count as data
• What gets shared
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
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Step 1: Scientist publishes a a paper in a journal.
Step 2: A data curator scans journals for data, extracts data and descriptive information, and enters
it all into a computer.
Step 3: Data are integrated with other data into one database and made available to anyone via the
Internet.
Step 4: Other people use the data. They provide input that results in additions of new types of data or
corrections to the database.
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Step 1: Scientist publishes a a paper in a journal.
Step 2: Scientist submits the data associated with the paper to a repository as a requirement of
publication.
Step 3: Data are integrated with other data into one database and made available to anyone via the
Internet.
Step 4: Other people use the data. They provide input that results in additions of new types of data or
corrections to the database.
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Step 1: Individuals get together to decide upon standard data
collection protocols.
Step 2: Every laboratory uses the agreed upon methods to collect data.
Step 3: Data are integrated and made available to anyone via the
Internet.
Step 4: Other people use the data. They provide input that influences how new data are collected or that
result in corrections to existing data.
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Implications
• Who is involved
• What count as data
• What gets shared
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Materials science data
ImagesGraphsSpectraColumns of numbers
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Shared Needs
• Long term access to data
• Finding data later
• Understanding the context of the data to use it in a meaningful way
• Accessing data, and information about data, from multiple locations
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Open Questions• What makes it hard to share data?
• How does the “state” of data affect sharing?
• What makes documentation sufficient for reuse?
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Developing Capacity• Open Data IGERT (Margaret
Hedstrom) http://opendata.si.umich.edu
• “i-School” Masters programs
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Ann Zimmerman1075 Beal AvenueAnn Arbor, MI [email protected]
Acknowledgments• Data Summit organizers & attendees
• Research participants
• Dharma Akmon & Morgan Daniels, PhD students, UM School of Information
• NSF Grants OCI 0724300 and IIS 0085981 (Gary Olson, PI)