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TWC-SWQP: A Semantically-Enabled Provenance-Aware Water Quality Portal

The TWC-SWQP (Tetherless World Constellation Semantic Water Quality Portal) provides a cutting-edge solution for water quality management through a semantic web approach. Developed by a team of researchers, the portal utilizes a comprehensive ontology design that integrates water measurement data and regulatory information. Key features include provenance capture and visualization, enabling users to track data origins and pollution levels. Future enhancements aim to incorporate health data and expand regulation coverage across multiple states, ensuring a robust framework for environmental monitoring.

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TWC-SWQP: A Semantically-Enabled Provenance-Aware Water Quality Portal

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  1. TWC-SWQP: A Semantically-Enabled Provenance-Aware Water Quality Portal Ping Wang, Jin Guang Zheng, Linyun Fu, Evan W. Patton, Timothy Lebo, Li Ding, Joanne S. Luciano, Deborah L. McGuinness Tetherless World Constellation RPI

  2. Outline • Introduction • Data Sources • Semantic Web Approach • Future Work

  3. Outline • Introduction • Data Sources • Semantic Web Approach • Future Work

  4. SWQP Overview

  5. Apply CA Regulation

  6. Retrieval by Characteristic

  7. Detailed polluting facility

  8. Provenance of water data

  9. Provenance of regulations

  10. Measurement Visualization

  11. Outline • Introduction • Data Sources • Semantic Web Approach • Future Work

  12. Data Sources

  13. Outline • Introduction • Data Sources • Semantic Web Approach • Future Work

  14. Domain Knowledge Modeling • Core ontology design1 1 http://purl.org/twc/ontology/swqp/core

  15. Domain Knowledge Modeling • Regulation ontology design2 2e.g., http://purl.org/twc/ontology/swqp/region/ny and http://purl.org/twc/ontology/swqp/region/ri; others are listed at http://purl.org/twc/ontology/swqp/region/

  16. Reasoning Domain Data with Regulations • Combining the water measurement data, the core and regulation ontologies, a reasoner can decide if a water body is polluted using OWL2 classification.

  17. Data Integration • We used the open source tool csv2rdf4lod3,4. • Linking ontological terms • Aligning instance references • Converting complex objects 3 Lebo, T., Williams, G.T., 2010. Converting governmental datasets into linked data. Proceedings of the 6th International Conference on Semantic Systems, I-SEMANTICS ’10, pp. 38:1–38:3. 4 http://purl.org/twc/id/software/csv2rdf4lod

  18. Provenance Support • Provenance Capture • Provenance Usage • Data Source Widget • Data Trace Visualization

  19. Water Data Provenance Capture

  20. Water Regulation Provenance Capture See complete table at http://tw.rpi.edu/web/project/TWC-SWQP/compare_five_regulation

  21. Water Regulation Provenance Capture See complete table at http://tw.rpi.edu/web/project/TWC-SWQP/compare_five_regulation

  22. Data Source Widget

  23. Data Source Widget • Usage • Presentation of the data sources on the interface • Source based data retrieval

  24. Provenance Visualization

  25. Future Work • Convert data and encode the regulations for the remaining states • Linking to Health Domain • Utilize data from other sources, e.g. weather and flood forecasts • Apply this architecture to other applications, e.g. the Clean Air Status and Trends demo5 5 http://logd.tw.rpi.edu/demo/clean_air_status_and_trends_-_ozone

  26. Thank you!

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