1. Semantic Geospatial Data Exchange & Access Control Ashraful Alam Bhavani Thuraisingham Ganesh Subbiah Latifur Khan

2. Outline Traditional Web Services Semantic Web Services Semantic Web Services for Geospatial Data Semantic Access Control Geospatial Data Integration GRDF for Distributed Geospatial Data

3. Static 500 million users more than 3 billion pages WWW URI, HTML, HTTP Semantic Web Services Vision

4. WWW URI, HTML, HTTP Serious Problems in information finding, information extracting, information representing, information interpreting and and information maintaining. Semantic Web RDF, RDF(S), OWL Static Semantic Web Services Vision

5. WWW URI, HTML, HTTP Bringing the computer back as a device for computation Semantic Web RDF, RDF(S), OWL Dynamic Web Services UDDI, WSDL, SOAP Static Semantic Web Services Vision

6. WWW URI, HTML, HTTP Bringing the web to its full potential Semantic Web RDF, RDF(S), OWL Dynamic Web Services UDDI, WSDL, SOAP Static Semantic Web Services Semantic Web Services Vision

7. WWW URI, HTML, HTTP Bringing the web to its full potential for Geospatial Domain Geospatial Semantic Web GRDF Dynamic Geo-Web Services UDDI, WSDL, SOAP,OGC -WS Static Geospatial Semantic Web Services DAGIS DAGIS Vision

8. Geospatial Interoperability Challenges Syntactic Naming Heterogeneity Distance – Float or Distance Type Structural Naming Heterogeneity Location expressed by two separate coordinates or by a point data type Semantic Heterogeneity Distance computed on the sphere or in a plane Service Discovery and Evaluation Hydrologist in charge of Flood Warnings has 3 Water-level Service Providers. Service Composition Service to Compute the outline of a Toxic cloud after a Chemical Spill.

9. Motivating Scenario Query: “Find movie theaters within 30 miles of 75080” within, near, overlap – Geospatial Operators Theaters, Restaurants – Businesses (Non-Geospatial data) Miles – Distance Unit 75080, Richardson – Geo References Cinemark Movies 10 Radisson Hotel Dallas North- Richardson

10. The human-centric Web The Application-centric Web The automated Web What is a Web Service ?

11. OWL-S Upper Ontology Mapping to WSDL communication protocol (RPC, HTTP, …) marshalling/serialization transformation to and from XSD to OWL Control flow of the service Black/Grey/Glass Box view Protocol Specification Abstract Messages Capability specification General features of the Service Quality of Service Classification in Service taxonomies

12. Query Grammar Define, Geospatial Objects as GB, Geospatial Operator as GO, Polygon Type as PT and Extension as E. Then, :: [ ] [ ] [ ] :: Non-geometric Concept :: :: Distance :: Within | Touches On | Intersect | Between :: Straight line | Circle

13. Generation of Semantic enabled profile for Geospatial Query Query Profile MilesZipCode Theaters Domain Ontology (Snapshot)Generated OWL-S Semantic Profile http://www.utdallas.edu/~gxs059000/Query.owl http://www.utdallas.edu/~gxs059000/OGCServiceontology.owl

14. Geospatial Service Selection and Discovery DAGIS Agent OWL-S MX Matchmaker Best Service Match : Functionality,QoS Degrees of Match: EXACT < PLUG-IN < SUBSUMES< SUBSUMED-BY<LOGIC BASED FAIL < NEAREST-NEIGHBOUR < FAIL

15. Geospatial Service Invocation -OWL-S grounding -WSDL Grounding -Service Invocation through AXIS GetTheater Process MilesZipCode Theaters GetTheater Atomic Process

16. DAGIS System Architecture DAGIS Query Interface OWL-S MatchMaker OWL-DL Reasoner for Matchmaker Service Providers 1. Register/ Advertise 3. Service Discovery, Service Enactment DAGIS Matchmaker Service Provider - 1 Service Provider - 1 Service Provider - n Service Provider - n DAGIS Agent DAGIS Agent Reasoner/ Matching Engine Reasoner/ Matching Engine DAGIS Interface DAGIS Interface … 2. Query

17. DAGIS for Complex Queries 1. Query Profile 2. Service Discovery 3. Compose Selection 4. Construct Sequence 5.Return Dynamic Service URI DAGIS Composer DAGIS Composer Match- Maker Match- Maker DAGIS Agent DAGIS Agent Client Composer Sequencer Composer Sequencer Find Movie Theaters within 30 Miles from Richardson, TX TX Zipcode Finder Zipcode Finder Theater Finder Theater Finder Richardson 30 Miles Theaters

18. DAGIS Composer Algorithm Recursive Back Chaining Inference Mechanism (Regression Planning) TX Richardson 30 Miles Movie Theaters Zipcodefinde r GetTheater Inputs:= City, State, DistanceOutput := Movie Theaters NO Service Provider Inputs:= City, State Output := ZipCode ZipCodeFinder Inputs:= ZipCode, DistanceOutput := MovieTheatersTheater Finder

19. DAGIS Query Interface

20. DAGIS Integration Scenarios QueryAvailabilityService TypeService Invoked Find Movie Theaters within 30 Miles of 75080 YESAtomic (Single) Service Provider GetTheatersAndMoviesS ervice Find Movie Theaters within 30 Miles of Richardson,TX NODAGIS Composes two Atomic Services: ZipCodeFinder, GetTheatersAndMovies Find Movie Theaters within 30 Miles of 75080 QoS: Response Time 30 Sec YES Two services with QoS 40 Sec and 50 Sec Available Atomic Service GetTheatersAndMoviesS ervice QoS Response Time 40 Sec Find Movie Theaters within 30 Miles of 75080 NOAtomic ServiceGetTheatersService

21. Online Ontology Repository http://www.utdallas.edu/~gxs059000/QoSUpper.owl http://www.utdallas.edu/~gxs059000/QoSMiddle.owl http://www.utdallas.edu/~gxs059000/GetTheatersAndMovies.owl http://www.utdallas.edu/~gxs059000/GetTheatersAndMovies1.owl http://www.utdallas.edu/~gxs059000/GetTheaters.owl http://www.utdallas.edu/~gxs059000/ZipCodeFinder.owl http://www.utdallas.edu/~gxs059000/DAGISCompServ1.owl

22. Geospatial Operators Between, Near, Within etc. Precision required for geospatial tasks How to define the operator semantics? (‘Between’ A and B  ‘Between’ B and A) Context required for better precision (e.g., near 20 miles)

23. Geospatial Operator (Google Maps)

25. Geospatial Operator (DAGIS)

26. Geospatial Data Integration Intra-domain Integration Problem All participating domains are of geographic nature. Controlled environment, controlled data. Inter-domain Integration Problem Integration of geospatial and non-geospatial data Controlled data, but chaotic environment

27. Inter-domain Integration Issues Disparate Sources: Sensors, Web pages, Satellites, Excel sheets Disparate Types: Vector data, Tabular, Temporal data Disparate Formats: GML, Shapefile, Gedcom, HTML

28. Geospatial Data Integration Emerging trends in geospatial applications Google Earth, Emergency Response System, Location-based Services Requires free mixing of geospatial with non- geospatial data Hard to do with XML-based approaches

29. Semantic Web (RDF Model) Logic-aware languages Ontology sharing and reuse RDF Data Model: Subject Object Predicate

30. GRDF GRDF (Geospatial Resource Description Framework) Adds semantics to data Loosely-structured (easy to freely mix with other non-geospatial data) Semantically extensible ComputerScience Building hasExtent (33.98111, -96.4011) (33.989999, -96.4022)

31. GRDF Example (Topology) <owl:minCardinality rdf:datatype="http://www.w3.org/2001/XMLSchema#int" >1 …

32. Seamless Data Manipulation DAGIS Provider A Provider B SubjectPredicateObject Datastore

33. Geospatial Data Integration (cont.) Upper-level ontologies Mid-level ontology (GRDF) Domain ontologies Concrete Definitions of All Relevant Geospatial Concepts Abstract Definitions of Main Geospatial Concepts Hydrology ontology Hydrology ontology Cartography ontology Cartography ontology Image ontology Image ontology

34. Semantic Access Control (SAC) Traditional Access Control Traditional Access Control Semantic Web Semantic Access Control

35. Motivation Shortcomings of Traditional Access Control Proprietary systems Lack of modularity Changes in access control schemas break the system Changes in data schemas break the system Path to resources (e.g., XPATH) is clumsy //school/department/professor/personal/ssn – LONG! Non-optimal for distributed/federation environment

36. Modularity Problem People this policy applies to Resources this policy applies to Actions allowed for this policy Target Box

37. SAC Ontology Written in OWL ( Web Ontology Language ) User-centric Modular Easily extensible Available at : http://utd61105.campus.ad.utdallas.edu/geo/voc/newaccessonto

38. Geo-WS Security Data providers (e.g., geospatial clearinghouses, research centers) need access control on serviceable resources. Access policies have geospatial dimension Bob has access on Building A Bob does NOT have access on Building B Building A and B have overlapping area Current access control mechanisms are static and non- modular.

39. Geo-WS Security: Policy Components Subjects: Software Agents or Human clients Resources: Assets exposed through WS Actions: Read, Write, Execute Conditions: Additional constraints (e.g., geospatial parameters) on policy enforcement Resources Subjects Actions Condition Policy Set

40. Geo-WS Security: Architecture Client DAGISDAGIS DAGISDAGIS Geospatial Semantic WS Provider Enforcement Module Decision Module Authorization Module Semantic-enabled Policy DB Web Service Client SideWeb Service Provider Side

41. Geo-WS Security: Semantics Policy rules are based on description logic (DL). DL allows machine-processed deductions on policy base. Example 1: DL Rule: ‘Stores’ Inv. Prop. ‘Is Stored In’ Fact: Airplane_Hanger(X) ‘stores’ Airplane(Y) Example 2: DL Rule: ‘Is Located In’ is Symmetric Fact: Polygon(S) ‘Is Located In’ Polygon(V) Polygon(V) ‘Is Located In’ Polygon(T)

42. Geo-WS Security: Inferencing Geospatial Data Store Semantic-enabled Policy DB Inferencing Module Obvious facts Deduced facts

43. SAC in Action Environment: University Campus Campus Ontology http://utd61105.campus.ad.utdallas.edu/geo/voc/campusonto Main Resources Computer Science Building Pharmacy Building Electric Generator in each Building

44. SAC in Action User Access: Bob has ‘execute’ access to all Building Resources Bob doesn’t have any access to CS Building Bob has ‘modify’ access to Building resources within a certain geographic extent Policy File located at http://utd61105.campus.ad.utdallas.edu/geo/voc/policyfile1

45. Future Directions QoS based Selection for Complex Queries Automatic Trust Negotiation for DAGIS Define a specification for access control semantics Geospatial dataset development Thank You!