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Semantic Water Portal Project Status

Semantic Water Portal Project Status. Jin Guang Zheng, Tetherless World Constellation. Outline. Introduction General Information About Semantic Web Portal Research Problem Why Should We Care Semantic Water Portal Project General Information About The Project

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Semantic Water Portal Project Status

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  1. Semantic Water Portal Project Status Jin Guang Zheng, Tetherless World Constellation

  2. Outline • Introduction • General Information About Semantic Web Portal • Research Problem • Why Should We Care • Semantic Water Portal Project • General Information About The Project • Approach Solves The Research Problem • Current Status Of The Project • Features And Implementations • Conclusion • Why Semantic Water Portal Is Important • How Semantic Water Portal Solves Research Problem • What I Learn From The Project

  3. Introduction: SWP • Semantic Web Portal: • Web site that collects information for a group of users • For a community to share & exchange information • Based on Semantic Web Technologies • Existing Semantic Web Portals: • SEAL • Museum Finland • Health Finland

  4. Introduction: Research Problem • Problem Statement • How to use semantic web technology to leverage web portals and build an easy-to-deploy semantic web portal? • Different From Existing SWP • Semantic Web Technologies • Easy-to-deploy SWP

  5. Introduction:Why should we care • Semantic Web Technologies enables smart functionalities for portals • Automatic Inference and Reasoning • Data integration and aggregation • SWP helps deliver, demonstrate Semantic Web Technologies • Good for the Semantic Web Community

  6. Semantic Water Portal Project • General Information • Project’s Goal • Help citizens & scientist to identify polluted water source, and explore current and past states of the water source w.r.t known pollutants • Use Case • Citizen lives in Troy, he wants to know if Huston River is polluted? What is the current state? • Environmental Scientist wants to know current status on the water sources of Rhode Island.

  7. Approach:Meets the Use Case Need • Use Case Requirement • Data Requirement: • Water Source Data, Regulation Data, Facility Data • Modeling and Reasoning requirement • Ontology, Reasoner, Provenance • Our Solution • Data: USGS Data, EPA Data, State Regulation Data • Modeling & Reasoning: SWP Ontology, Back-end Reasoner using Jena+Pellet

  8. Approach:Semantic Web Technologies • Leverage Web Portals with Semantic Web Technologies • Data Integration & Aggregation • Automatic Reasoning: Ontology + Jena + Pellet • Provenance: • Data Level Provenance: Where is data coming from? • Reasoning Level Provenance: How does the system come with the conclusion? What are the data used in the reasoning steps?

  9. Approach:System Architecture Front – End Interface • System Architecture is simple • Easy to modify & replace the components • Easy to use each components individually Communication Back – End Service SPARQL Triple Store Converter Datasets

  10. Current Status • Semantic Web Technologies • Dataset: USGS Data, EPA Data, State Regulation Data • Data Conversion: Tim’s Converter • Ontology: for reasoning on polluted water source & factory violate EPA regulation • Visualization of Data on Geo Map • Provenance: • Data source Provenance • Application, Reasoning Provenance

  11. Features and Implementations • More Interesting Reasonings • Transitive Reasoning, Health Related Reasoning, etc. • Provenance • Provenance related visualization • Provenance related search • Ontology • Use, combine, learn “Applying Ontologies And Semantic Web Technologies To Environmental Sciences And Engineering” • Visualization • Showing trends of the water status

  12. Conclusion • Why Semantic Web Portal is important? • Semantic Web Portal helps deliver, and demonstrate Semantic Web Technologies • Enables functionalities that non-semantic web portal won’t be able to support • Problems: • How to use semantic web technology to leverage web portals and build an easy-to-deploy semantic web portal?

  13. Conclusion • Semantic Water Portal: • Easy to deploy portal system • Simple architecture, components are easy to use, modify, etc. • Leverage Web Portal by Semantic Web Technologies • Data aggregation, automatic reasoning, provenance related functionalities

  14. Conclusion • What I learn from the project? • Provenance related visualization & search • Review and learn ontology • Working with Jena + Pellet • Learn applying SWT to other domain

  15. Questions • Thank you for your attention!

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