1. Value Proposition for Spatial Ontologies & Incorporating Semantics and Ontologies into SDI Kevin Backe Army Geospatial Data Model Program Manager John Moeller Northrop Grumman SOCoP Co-Chairs

2. Observations on Ontology SBIR with small company on ontology tools to address heterogeneous geospatial data sources –Tools ahead of demand –Lack of first adopters‘ for beta tools –Successful implementation hidden part of technical architecture Ontology R&D programs within various agencies –Good use-cases for ontologies examined –One Scientist/Engineer Advocate for ontologies within Agency Socio-cultural ontology development within Army research program –Prototype S-C ontology –Ontology was buried within a proprietary tool without any export capability --could only provide screen shots as output from tool Socio-cultural Ontology work –Underfunded –Insufficient team to integrate ontology work with rest of architecture Ontologies as part of Organization’s Enterprise, specifically Geospatial Enterprise –No Program of Record (PORs) identified –Two examples within found “Intel” organization’s enterprise Used to intelligently parse through unstructured messages to categories and provide semi-structure to “free text.” Enable automation of large volumes of msgs. to categories into bins/folders and flag key msg. may be related to topic. Both cases part of a large enterprise set of tools/capabilities Ontologies will be in our Future –Ontology(s) will be nested within robust enterprise system as part of service(s) –Domain SME serving as Knowledge Engineers (with Ontology tool) within organization analogous to DM team, DBA, ….

3. Ontology Value-Proposition Challenge Need componentization of semantic tools (incorporate ontologies) that simplify integration within a SOA enterprise –w/o need for an integration team of experts. Need significant operational examples that demonstrate the benefit to enterprise using semantic technologies including ontologies

4. What is the value that Ontologies provide to an Enterprise Better capture richness of semantics? Better model of reality? Reduce N 2 mapping between COI semantics to 2N? i.e. each COI semantics maps to a common ontology? Better organization for human and machine consumption? Higher degree of automation, less human interaction to parse through large volumes of data? What are the meaningful, measurable benefit that provide the impetus for an organization to consider inserting semantic Tools/technology including ontologies into their enterprise?

5. Chris Welty Coverage, correctness, richness, commitment [Kashyap, 2003] Organization, modularity [Rector, 2002] Related to reality [Smith & Welty, 2001]

6. What is a Spatial Data Infrastructure ? A Spatial Data Infrastructure is the “Dial-Tone” of the geospatial web –“the means to assemble geographic information that describes the arrangement and attributes of features and phenomena on the Earth” (US National Research Council) –‘the technology, policies, standards, and human resources necessary to acquire, process, store, distribute and improve utilization of geospatial data” (US NSDI EO 12906) –“the policies, organizational remits, data, technologies, standards, delivery mechanisms, and financial and human resources necessary to ensure that those working at the global and regional scale are not impeded in meeting their objectives” (GSDI Association)

7. SDI Key Components Network Spatial Data Catalogues/Clearing Houses/Registries Data Services An Integrating Data Framework/Foundation Guidelines/policies Standards and Specifications –Metadata –Core/base data –Spatial data –Services Institutional capacity and partnerships

8. SDI Development Pre –SDI through Initial Development and Implementation 1990’s – current Web-based, standards based understanding of value of geospatial as an integrating function for the enterprise Early 2000 – current Implementation of service oriented architectures, development of implementation profiles and service chaining Web services 2006 – 2009 Enterprise connections enabled through semantic capabilities, embedded business processes, sensor integration, data discrimination services Anticipated timeframe: 2008 – 2010 Intelligent SDI Networks are in place using metadata for date, service, applications and models etc, registries and catalogues, semantics, chained services, e-commerce, to provide cost/accuracy/time options to meet users requests Anticipated timeframe: 2010

9. Geoparser From a Foundation of SDI Best Practices Reduce deployment costs by reusing information from other communitiesReduce deployment costs by reusing information from other communities Meet requirements for Citizen access.Meet requirements for Citizen access. Foundation for interoperable service networksFoundation for interoperable service networks Easier access to multiple online info sources and services Easier access to multiple online info sources and services Use and reuse different vendor solutions. Use and reuse different vendor solutions. Clearinghouse Geoparser Vendor Data Local Government National Government Other Collections Clearinghouse Whoville Cedar Lake Whoville Cedar Lake Buildings Roads Images Targets Boundaries... Catalog View Common interfaces enable interoperability Queries extract info from diverse sources Integrated View Gazetteer Coordinate Transform Web Mapping Server, Web Feature Server, Web Coverage Server Catalog Services Other Services Metadata Data Metadata Data Metadata Data Metadata Internet Geoparser Geocoder Source: Open Geospatial Consortium

10. Moving from a Foundation of SDI Best Practices To Geospatially Enabling The Enterprise Source: Open Geospatial Consortium Where do Ontologies and Semantics Fit??

11. Some Comments/Questions Open standards provide the framework for geospatial interoperability and data sharing SDI’s around the world are expressing support for interoperable solutions Are with ontology and semantic tools ready for incorporation into SDI’s of different levels of maturity or only in the most mature? If not what is needed to stimulate implementation?