Polar CI: A Clound based Polar Resource Discovery Engine
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The document describes Polar CI, a cloud-based portal for discovering polar resources. The portal aims to provide a one-stop shop for polar data and services through semantic search and quality evaluation tools. It consists of six main components: 1) a data harvesting middleware to collect metadata from various sources, 2) a search broker to translate user queries and retrieve results, 3) a data warehouse to store metadata, 4) a semantic engine to refine search queries, 5) a quality of service engine to evaluate service performance, and 6) visualization tools to display results. The portal harvests over 2 million metadata records from 10 sources and is implemented using .NET, ASP.NET, and Silverlight on the Amazon EC2 cloud.
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Polar CI: A Clound based Polar Resource Discovery Engine
- 1. Polar CI: A Cloud based Polar Resource Discovery Portal Yongyao Jiang Department of Geography and Geoinformation Science, George Mason University Colleagues: Jizhe Xia, Kai Liu
- 2. • Background • Objective • Architecture • Implementation • Contribution • Demo Agenda
- 3. Background • Polar regions: 1)natural resources 2)indicators of climate changes • Dispersed distribution • Search: key-word based matching • Lack of information to help making selection • Visualization (polar projection)
- 4. Objective • One-stop polar resource portal – Data, service • Semantic-based search • Service quality • Visualization tools NOAA USGS Portal Users
- 11. Data Harvesting Middleware • Harvest metadata from other sources – Customize search request – Convert metadata formats • 2 million metadata from 10 sources(dataset and service)
- 12. Search Broker • Middleware between user and data • Translate user’s input • Parse server’s response • Async query
- 13. Data Warehouse • Built upon GeoNetwork (open source spatial catalog) • Connected with PostGIS • Support catalog service – web (CSW)
- 14. Semantic Engine • Translate search input into query rules • Calculate relevance index between input and search result
- 15. Quality of Service Engine • Monitor service performance • Collect information from other evaluation systems • Calculate overall service quality
- 16. Visualization Tools • Visualize data and data service • Paged list viewer • Bing maps viewer • Pivot viewer • Service quality viewer
- 17. Implementation • Microsoft .NET framework (Search broker) • ASP. NET (Server side) • Silverlight (Client side) • Windows Communication Foundation’ (WCF) services
- 18. Contributions • Developed the data harvesting middleware • Developed the polar viewer based on Openlayers 3 • Developed the metadata parser in the search broker • Moved the entire system from Windows Azure to Amazon EC2 • Wrote a book chapter • Developing the data quality module to evaluate quality of data and help user make selection
- 19. Demo • Polar CI: http://52.6.44.195/
Notes de l'éditeur
- it is a collaborative project. It was initially developed by Jizhe and Kai who have been included them in the author list, and now I am the one who is in charge of this project in our center. My contribution in the project includes a few things: 1. Developed the data harvesting middleware to harvest data from various sources. Specifically, to deal with heterogeneity, it customizes search request for each different source and convert response from server into format that are recognizable to our data warehouse. Currently, sources that the middleware supports include GEOSS clearinghouse, NSIDC, NGDC, NODC, NASA ECHO and Data.gov. 2. Developed the polar viewer based on Openlayers 3 to better visualize polar data and service 3. Modified the metadata parser in the search broker (client side) to support more data format from the server 4. Moved the entire system from Windows Azure to Amazon EC2 5. Wrote a book chapter called "Polar CI Portal: A cloud based polar resource discovery engine", which will be published soon 6. Developing the data quality module to evaluate quality of data and help user make selection, which will be integrated into this system shortly