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Global Science Needs Global Data A Case for Data Sharing

The Fifth China - U.S. Roundtable on Scientific Data Cooperation. Global Science Needs Global Data A Case for Data Sharing. E. Lynn Usery. usery@usgs.gov. http://cegis.usgs.gov. Objectives.

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Global Science Needs Global Data A Case for Data Sharing

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  1. The Fifth China - U.S. Roundtable on Scientific Data Cooperation Global Science Needs Global DataA Case for Data Sharing E. Lynn Usery usery@usgs.gov http://cegis.usgs.gov

  2. Objectives • I will focus on the need for complete global geospatial datasets at high resolution to support global science modeling and analysis • Example Science Issues and Global Data Needs • Global Climate and Land Cover Change • Global Ecosystem Modeling • Global Hazards • Earthquakes • Sea Level Rise • Volcanism • Research on Semantic Web; platform for data sharing

  3. USGS Science Strategy http://www.usgs.gov/science_strategy /

  4. USGS Science • Understanding Ecosystems and Predicting Ecosystem Change • Climate Variability and Change • Energy and Minerals for America’s Future • A National Hazards, Risk, and Resilience Assessment Program • The Role of Environment and Wildlife in Human Health • A Water Census of the United States

  5. USGS Science • Data Integration and Beyond • The USGS will use its information resources to create a more integrated and accessible environment for its vast resources of past and future data. It will invest in cyberinfrastructure, nurture and cultivate programs in natural-science informatics, and participate in efforts to build a global integrated science and computing platform.

  6. Global Climate and Land Cover Change • Data Needs – One Example • High resolution (30 m or smaller pixels) satellite images for land cover extraction • U.S. has Landsat archive but does not • include all scenes from non-US-based • receiving stations • Extracted land cover • Classes must match, i.e., same classification • system and same level of detail

  7. Worldwide Usage of Landsat Imagery 1M

  8. Online Data Search, Browse and Order Tools Earth Explorer GLOVIS http://earthexplorer.usgs.gov http://glovis.usgs.gov

  9. Landsat International Data Usage (FY10)

  10. Landsat Global Archive Consolidation (LGAC) • Goal is to consolidate the entire Landsat archive • 5 million scenes held internationally vs. 2 million in the USGS archive • From current stations as well as historical stations • Each station has data that will enhance the USGS archive • Enables scientific analysis of most complete time-series of images for global land change • Facilitates large scale scene selection and data mining capability • Recover data not currently available to users • Some data at risk due to aging media and drive obsolescence • Provides data to global user community as standard product like current Landsat data from US archive

  11. LGAC International Data Holdings

  12. Landsat 8 • Similar requirement for global data from all receiving stations to be archived and made freely available to support global science

  13. Global Ecosystem Modeling – Data Needs • Global species data • Invasive species – cost in U.S. is billions of dollars each year – similar in other countries • Global secession data • Global climate records • As climate changes, how do species adapt; this is a global problem and requires global data sharing

  14. Global Hazards – Earthquakes • Locations, epicenters, seismic wave data, exchanged in real time • Soil effects data • Infrastructure damage • Relief effort and support depends on data availability

  15. Global Hazards – Volcanism • Volcano locations, eruption histories, types, distributed in realtime • Ash cloud distribution and models

  16. Global Hazards – Sea Level Rise • Global elevation high resolution • ASTER Global DEM (15 m resolution) is a start • Need lidar/IfSar along all coasts • Corresponding population data • (current highest resolution is 30 arc-sec) • Corresponding land cover data

  17. Volume – multiple global datasets at high resolution Structure – variety of structures, vector and raster, many different formats Semantics – various attribution and relation schemes, some feature-based, some layers Integration of multiple datasets – for maximum utility all datasets should be able to be integrated to produce new data and information Data Sharing ISSUES

  18. Volunteered Geographic Information/ User Generated Content • USGS “Did You Feel It?” • Open Street Map (OSM) • USGS now researching use of OSM for our transportation and structures data • VGI/UGC rivals traditional geospatial data sources and provides new basis for data sharing

  19. Technical problems • Compatible data models • Resolution, accuracy issues • Attribution issues – need ontology that allows matching across data schema • Data sharing is more than making data available for download over the Web • Requires standards • USGS data meets Federal Geographic Data Committee and Open Geospatial Consortium standards for metadata and packaging

  20. Semantics – Intelligence • USGS is exploring Semantic Web for data sharing; globally linked data • Requirements: • Ontology of features, attributes, and relationships: currently being developed. • Semantic Web triple format: Conversion for selected test areas is in progress. • Uniform Resource Identifiers (URIs) for individual features, i.e., each geographic feature has a unique URI

  21. USGS Semantic Web SPARQL Endpoint for Data Access http://usgs-ybother.srv.mst.edu:8890/sparql

  22. Query – Find the tributaries of West Hunter Creek Default Graph URI http://cegis.usgs.gov/rdf/ontologytest/ PREFIX ogc: <http://www.opengis.net/rdf#> PREFIX fid: <http://cegis.usgs.gov/rdf/nhd/featureID#> SELECT ?feature ?type WHERE { fid:_102217454 ogc:hasGeometry ?geo1. ?geo1 ogc:touches ?geo2. ?feature ogc:hasGeometry ?geo2. ?feature a ?type }

  23. Query Result http://cegis.usgs.gov/rdf/nhd/featureID#_102216432 http://cegis.usgs.gov/rdf/nhd/featureID#_102216448 http://cegis.usgs.gov/rdf/nhd/featureID#_102216340 http://cegis.usgs.gov/rdf/nhd/featureID#_102216320 http://cegis.usgs.gov/rdf/nhd/featureID#_102217454 http://cegis.usgs.gov/rdf/nhd/featureID#_102216276 http://cegis.usgs.gov/rdf/nhd/featureID#_102216358

  24. Major Challenges for Geospatial Data Sharing with Semantics • Semantic spatial data model • Coordinates on the Semantic Web in RDF • Geospatial feature ontologies • Ontology-driven geospatial operators • Moving multi-GB to TB of data to grid/cloud • Implementing spatial operators on Semantic Web and in • grid/cloud environment • Interfacing Semantic Web and grid/cloud capabilities

  25. The Fifth China - U.S. Roundtable on Scientific Data Cooperation Global Science Needs Global DataA Case for Data Sharing E. Lynn Usery usery@usgs.gov http://cegis.usgs.gov

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