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Exploitation of Dynamic Information Relations in the Service-Oriented AFRL
Information Management Systems
Andrzej Uszok, Larry Bunch, Jeffrey M. Bradshaw
James Hanna, Albert Frantz
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
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
Information Space Overview
During the previous KSCO we presented Federation Service for IMS.
Information Space
Information Catalogue
Stored Info. Index
Information Models
Client Status
Consumers Producers
Information Repository
Transient Info
Persistent Info
Archived Info
CAPI
CAPI
LocalInformation Space
Producer Producer
Consumer Consumer Consumer
Publisher Data(Access Control,
Information Preprocessing,QoS Enforcement,
Information Transformation)
Publisher Channel(Registration,
Advertisement,Feedback, RFIs)
Broker(Consumer Data)
Consumer Control (Registration, Subscription,
Search and Query Requests)
Quality of ServiceManagement
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
Current Assumptions of IMS
The type of information object used for publication, subscription and query has to be registered in the Information Type Service.
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
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
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.
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
Fragment of Document Ontology
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.org
– KAoS Java libraries for constructing OWL Relies on Jena http://jena.sourceforge.net
Office Mapping to Ontology
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
UCORE-SL
Military ontology associated with UCORE XML message format standard
Analysis of Information Relevance
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
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
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
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
Type ManagerType Manager
Types
Air Tasking Order
ID: ATO
Relations for Selected Type+ -
Creator: [email protected]
Weather Forecast
ID: WeatherForecastCreator: [email protected]
Original: schema/ATO.xsd
Part OfATO
Creator: [email protected]:
SITREP
Creator: [email protected]
Context: time within 10 minuteslocation within 1 km
Weather Report
ID: WeatherReportCreator: [email protected]
Original: schema/WForecast.xsd
Original: schema/WReport.xsd
http://afrl.af.mil/Model.owl#ATO
Subclass OfPeriodicReport
Creator: [email protected]
Contributes To
WeatherForecast
Creator: [email protected]: time within 30 minutes
location within coverageArea
+ -
Subject Search < > ResetObjectRelation Go
Dynamic Information Type Management GUI
List typesin the typerepository
List typesmatching
search criteria
Subject-Relation-Objecttype 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.
o weather typeso types with any relation to weathero types that contribute to a weather forecast
Hyperlink to type list
Select a type to view its relationsAdd a
new type inType Editor
Edit TypeEdit Type
TB
FL
TM
OV
UA
Original Property
Xsd:String
xsd:Integer
xsd:datetime
xsd:latlon
xsd:UUV
Original Range
turbulence
altitude
datetime
location
urgency
OWL Property
model:Turbulance
xsd:Integer
time:Instant
model:LatLon
model:UrgencyLevel
OWL Range
Weather ReportLabel
URI
External Type
http://afrl.af.mil/Model.owl#WeatherReport
Description of current weather conditionsDescription
XML Schema
0+
1
1
1
1
Cardinality
Property Mapping
2011-01-01 13:55:01.1
Date
User
Change History
Initial version
Description
http://afrl.af.mil/Model.owl#PeriodicReporthttp://afrl.af.mil/Model.owl#PointLocatedEntity
Superclasses+ -
Source
Browse
schema/Wreport.xsd
View
urgency
location
datetime
altitude
turbulence
External Type
Source
Database Table
AFRL Weather DB
Table FORECAST
Type Editor
Human-readable label
Unique type identifier (RDF)
Original type description
Human-readable description
Parent classes from the unified model
Mapping of original propertiesto OWL
Browse for an XSD, OWL, DDL file or
Office
Original properties are parsed from the source file
OWL properties
are editable
Edit Relation for WeatherReportEdit Relation for WeatherReport
Relation Type Contributes To
time of weatherReport within 30 minutes before startTime of weatherForecast andlocation of weatherReport within coverageArea of weatherForecast andproperty of weatherReport relates to property of weatherForecast +
Relation Context Expression
Related Class WeatherForecast
Browse Classes...
Relationship Editor
Subject class of the relationship
Object class of the relationship
Type of relationship
Context in which the relationshipapplies, expressed using the
SPARQL syntax for triple patterns and FILTER statements
Click forClass
Browser
Click for Date and Time
Editor
Click for Area Editor
SPARQL expression.created using hypertext
interface
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.
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
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