1. Exploitation of Dynamic Information Relations in the Service-Oriented AFRL Information Management Systems Andrzej Uszok, Larry Bunch, Jeffrey M. Bradshaw James Hanna, Albert Frantz

2. Outline AFRL Information Management System and its limitations Motivation for Dynamic Information Semantic model of information Document ontology and annotation Information relevance ontology and folksonomy Architecture of IMS extensions with Dynamic Information Conclusion

3. AFRL Information Management System Information Management System consists of a server, a client interface (CAPI), and associated clients IM Server consists of set of services performing information brokering and dissemination Information is packaged into Managed Information Objects (MIOs) – Consists of metadata (XML) and payload (binary) Client operations include – Publish – Subscribe – Query

4. Information Space Overview During the previous KSCO we presented Federation Service for IMS.

5. IMS Limitation Require applications to map to “single managed information format Information instances immutable Subscription and Query scoped by information type Lack of support for unstructured query Limited usefulness and adaptability of IMS to the coalition information sharing. – Strict restriction on used types and formats of information – Inability to selectively extract parts of the information intended for sharing

6. Current Assumptions of IMS The type of information object used for publication, subscription and query has to be registered in the Information Type Service.

7. Vision for Dynamic Information Flexible information model supporting a variety of existing information schema with rich semantic Ability to correlate dynamic information in order to provide comprehensive mission information – a generic semantic relationship representation – discovery of relationships among semantically-related information – dynamic information groups Use of semantic relationships to provide – Support subscription and Query across multiple information types – Unstructured Query, system creates new information "on the fly” – Stream annotations

8. Syntactic Mapping Requirement to support variety of information type representation: XMLSchema, DDL, RDF, Office etc. Mapping from less expressive representation to more expressive is feasible Common expressive representation eliminates needs for one to one mapping Relations are easily represented in OWL/SPARQL RDF/OWL representation provides an explicit semantics allowing for establishment of information relationships The resulted mapping is annotated with information of the origin as the reverse translation is necessary

9. Semantic Linkage Technology Existing standards and techniques for semantically linked data Uniform semantic layer provides marriages across various standards allowing automated pattern searches and queries across previously unconnected sources.

10. Document metadata: author, create date, etc. Document elements: titles, text runs, captions, etc. Shapes and picture elements Structure – Nested documents – Documents parts Document Formats Ontology for Documents

11. Fragment of Document Ontology

12. Capabilities – Create an OWL description for the contents of a MS Powerpoint and Wordx document – Create an image for each slide in a Powerpoint Technologies – Off-the-shelf parser Apache POI v.3.7 http://poi.apache.orghttp://poi.apache.org – KAoS Java libraries for constructing OWL Relies on Jena http://jena.sourceforge.net http://jena.sourceforge.net Office Mapping to Ontology

13. Natural Language Indexing Published information is processed by GATE text processing system – Named-entity-extraction – who, when, where and what – Pattern matching grammar rules are based on the ontology classes Uses UCORE-SL (extended) Annotated Information is indexed by Apache Lucerne Semantic annotation and metadata are stored in ontology store (Jena TDB) Support for free text search integration with SPARQL

14. UCORE-SL Military ontology associated with UCORE XML message format standard

15. Analysis of Information Relevance

16. Support for Folksonomy Free tagging are needed in many situations: – There can be omissions in ontology – Concepts for new things and phenomena – Instance data, e.g., persons, places, events etc. too numerous Integration of new free keywords into ontologies in an annotation environment – The keyword are mapped to the existing ontology usually through the rdfs:subClassOf property

17. Service Oriented IMS Latest AFRL reincarnation of IMS Phoenix has Service Ordinated Architecture Set of independent, flexibly deployable IM services – Submission, Subscription, Information Brokering, Dissemination, Repository, Query, Type Management, Event Notification, Service Brokering, Session Management, Information Discovery, Security, Stream Service This features allowed us to: – gradually extended selected services of the IMS with the new capabilities – dynamically configured IMS

18. Dynamic Information Type Management Service Parser specific to the given type provides a uniform view for the relation discovery mechanism (additional schema annotations) Precompute (or acquire from the user) information relationships when new information types are created in the repository The precomputed relationships are the potential relationships realized by information depending on their actual values

19. GUI for New Information Type Service Create and manage a unified model of information types Import new type descriptions from existing XML Schema, DDL and Office documents. These types are mapped and integrated into the unified OWL model View, Update, and Define – information type descriptions in OWL – relationships among type descriptions – contexts in which certain information type relationships hold – combination definition for a resulting product

20. Dynamic Information Type Management GUI List types in the type repository List types matching search criteria Subject-Relation-Object type search Hyperlink to OWL (text or graph) Hyperlink to original type definition file (XSD,OWL,DDL) Partial text match of type ID’s Default values indicate open-ended search, e.g. oweather types otypes with any relation to weather otypes that contribute to a weather forecast Hyperlink to type list Select a type to view its relations Add a new type in Type Editor

21. Human-readable label Unique type identifier (RDF) Original type description Human-readable description Parent classes from the unified model Mapping of original properties to OWL Browse for an XSD, OWL, DDL file or Office Original properties are parsed from the source file OWL properties are editable

22. Relationship Editor Subject class of the relationship Object class of the relationship Type of relationship Context in which the relationship applies, expressed using the SPARQL syntax for triple patterns and FILTER statements Click for Class Browser Click for Date and Time Editor Click for Area Editor SPARQL expression. created using hypertext interface

23. Dynamic Publication When a publication is made, additional publications are generated based on relationships to other types. The information itself is also extended with additional related available information from the persistence information repository. Information groups are precomputed, based on existing subscriptions, with related persistent information facilitating semantic dissemination.

24. Dynamic Subscription and Query LARQ - Free Text Indexing for SPARQL; ability to perform free text searches combined with structured search Relation based Result enhancement – Searches for related information have their expression generated based on the original expression and the values in the current result under consideration

25. Combination of semantic with natural language and human annotation of documents provides rich space for discovering relations between information. Flexible model for information allow for greater adaptability of IMS for coalition information sharing Performance demand for the new semantic information mechanisms need to be controlled by policies and addressed by more computing power – cloud computing Conclusion