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A poster presented at AGU 2012.
Citation preview
SEAD: Opening Data in the “Long Tail” for Active and Social Curation AGU2012 IN13B-1505
Margaret Hedstrom, University of Michigan [email protected], , Praveen Kumar, University of Illinois [email protected] Jim Myers, Rensselaer Polytechnic Institute [email protected] Beth A. Plale, Indiana University [email protected]
Data Management: Current Practice
Create &Analyze Data
PublishResults
Deposit Data
CurateData
DiscoverArchived
Data
ReuseData
Time
Months Years
SEAD is an Active Data Management and Preservation Environment
www.sead-data.net
Web & Desktop Interfaces
Deposit - Store – View – Annotate -
Organize - Discover
Active Curation Services
Collect data/metadataGenerate derived data
products
Actio
nabl
e da
ta la
yer
Social Curation Services
Discover projects – people –expertise - publications – data - discussion
Current data management practice is a linear process. Data are handed off to repositories for long-term archiving and reuse by others. Users discover data through citations in publications and/or search of repository catalogs.
Soci
al C
urati
on
Virtual
Virtual ArchiveServices
Dis
cove
ry a
nd R
use
SEAD Services Secure storage for active data Automatic metadata extraction Display of data on map overlays Preview data in thumbnails Easy upload and download of data sets Data sharing controlled by the data owner Annotation and tagging Discovery of active data Integration of data in diverse formats Export to permanent archives (local
institutional repositories, topical archives) Discovery of data and publications Reuse data Visualize data in citation & topic networks
Hyperspectral Image Vector GIS map
+New dataset with
improved visualization and better
representationof the scene
SEAD’s Contributions to Science Accelerate data discovery Simplify data management Reduce curation costs and effort for
researchers Improve data quality Increase the value of data to others Preserve data Maintain connections between
people, publications and data
SEAD serves the “long tail” of science(Small centers, projects, collaboratories, single PI’s)• Low barriers to entry• Light-weight data management tools• Easy discovery of data, results, expertise• Long-term preservation solutions
Big
Dat
a
Long tail