W3C Video on the Web Workshop December 2007, San Jose, California Video on the Semantic Sensor Web Amit Sheth Amit Sheth with Cory Henson, Prateek Jain, Josh Pschorr and Terry Rapoch LexisNexis Ohio Eminent Scholar Kno.e.sis Center, Wright State University

Outline 1.Background on the Sensor Web 2.Introducing the Semantic Sensor Web 3.Prototyping the Semantic Sensor Web

Background on the Sensor Web Sensor Web Enablement

OGC Mission To lead in the development, promotion and harmonization of open spatial standards Open Geospatial Consortium Consortium of 330+ companies, government agencies, and academic institutes Open Standards development by consensus process Interoperability Programs provide end-to-end implementation and testing before spec approval Standard encodings, e.g. –GeographyML, SensorML, Observations & Measurements, TransducerML, etc. Standard Web Service interfaces, e.g. –Web Map Service –Web Feature Service –Web Coverage Service –Catalog Service –Sensor Web Enablement Services (Sensor Observation Service, Sensor Alert Service, Sensor Process Service, etc.)

Network Services Vast set of users and applications Constellations of heterogeneous sensors Weather Chemical Detectors Biological Detectors Sea State Surveillance Airborne Satellite Distributed self-describing sensors and related services Link sensors to network and network- centric services Common XML encodings, information models, and metadata for sensors and observations Access observation data for value added processing and decision support applications Users on exploitation workstations, web browsers, and mobile devices Sensor Web Enablement

GeographyML (GML) TransducerML (TML) Observations & Measurements (O&M) Information Model for Observations and Sensing Sensor and Processing Description Language Multiplexed, Real Time Streaming Protocol Common Model for Geography Systems and Features SensorML (SML) Sam Bacharach, “GML by OGC to AIXM 5 UGM,” OGC, Feb. 27, SWE Languages and Encodings

Catalog Service SOSSASSPS Clients Access Sensor Description and Data Command and Task Sensor Systems Dispatch Sensor Alerts to registered Users Discover Services, Sensors, Providers, Data Accessible from various types of clients from PDAs and Cell Phones to high end Workstations Sam Bacharach, “GML by OGC to AIXM 5 UGM,” OGC, Feb. 27, SWE Components – Web Services

Introducing the Semantic Sensor Web

Semantic Sensor Web What is the Semantic Sensor Web? Adding semantic annotations to existing standard Sensor Web languages in order to provide semantic descriptions and enhanced access to sensor data This is accomplished with model-references to ontology concepts that provide more expressive concept descriptions By using model-references to link SML annotated sensor data with concepts within an OWL-Time ontology we attain a representation of temporal semantics on sensor data

Model Reference XLink Used for describing links between resources in XML documents. Several important attributes within XLink include: –type: describes the element type of the link (i.e., simple, extended) –role: semantic attribute that describes the meaning of resources within the context of a link –href: locator attribute that supplies the URI needed to find a remote resource Other Model Reference Languages SAWSDL: Defines mechanisms to add semantic annotations to WSDL and XML-Schema components (W3C Recommendation) SA-REST: Defines mechanisms to add semantic annotations to REST-based Web services. W3C, XML Linking Language,

12 Model Reference (SensorML) Instant Interval OWL-Time Ontology

Semantic Query Semantic Temporal Query Model-references from SML to OWL-Time ontology concepts provides the ability to perform semantic temporal queries Supported semantic query operators include: –contains: user-specified interval falls wholly within a sensor reading interval (also called inside) –within: sensor reading interval falls wholly within the user-specified interval (inverse of contains or inside) –overlaps: user-specified interval overlaps the sensor reading interval Example SPARQL query defining the temporal operator ‘within’

Prototyping the Semantic Sensor Web

15 StorageQuery Extraction & Metadata Creation Video Conversion Filtering & OCR SML Annotation Generation Time & Date information Converted Videos SML (Xindice) OWL-Time (Jena) UI SML Interface OWL-Time Interface AVI OWL-Time Annotation Generation Google Maps JSP Architecture Data Collection YouTube

16 Temporal Data Extraction Channel Minimal Suppression 1 8-neighbor median for ‘bad’ pixels 1 Temporal Minimal Suppression 2 Binarization via adaptive threshold 1 Tesseract OCR engine Regular Expression parsing SensorML output

17 Prototype Application

Conclusion Future Work Incorporation of spatial ontology in order to include spatial analytics and query (perhaps with OGC GML Ontology or ontology developed by W3C Geospatial Incubator Group - GeoXG) Thematic query with keyword search through YouTube API and model reference to domain ontology Extension of SPARQL with enhanced spatiotemporal analytics and querySPARQL with enhanced spatiotemporal analytics and query Integration of framework with emergent applications, including video on mobile devices running Android OS W3C, XML Linking Language,

Kno.e.sis project on Semantic Sensor Web: Open Geospatial Consortium, Sensor Web Enablement WG, W3C, Time Ontology in OWL, W3C, Geospatial Incubator Group, Amit Sheth et al., SA-REST: Semantically Interoperable and Easier-to-Use Services and Mashups, IEEE Internet Computing, November/December 2007 (Vol.11, No.6) pp DOI: W3C, Semantic Annotations for WSDL and XML Schema, W3C, XML Linking Language, Google Code, Tesseract, References