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SEAD: Opening Data in the “Long Tail” for Active and Social Curation AGU2012 IN13B-1505 Margaret Hedstrom, University of Michigan hedstrom@ umich.edu , , Praveen Kumar, University of Illinois kumar1 @ illinois.edu Jim Myers, Rensselaer Polytechnic Institute MYERSJ4@ rpi.edu Beth A. Plale, Indiana University plale@ cs.indiana.edu Data Management: Current Practice Create & Analyze Data Publish Results Deposit Data Curat e Data Discov er Archiv ed Data Reus e Data 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/metadata Generate derived data products Actionable data layer 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. Social Curation Virtual Archive Services Discovery and Ruse 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 representation of 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 Data Long tail

SEAD: Opening Data in the "Long Tail" for Active and Social Curation

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A poster presented at AGU 2012.

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Page 1: SEAD: Opening Data in the "Long Tail" for Active and Social Curation

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