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

Slides:



Advertisements
Similar presentations
Dr. Leo Obrst MITRE Information Semantics Information Discovery & Understanding Command & Control Center February 6, 2014February 6, 2014February 6, 2014.
Advertisements

1 Ontolog OOR Use Case Review Todd Schneider 1 April 2010 (v 1.2)
Improving Learning Object Description Mechanisms to Support an Integrated Framework for Ubiquitous Learning Scenarios María Felisa Verdejo Carlos Celorrio.
CH-4 Ontologies, Querying and Data Integration. Introduction to RDF(S) RDF stands for Resource Description Framework. RDF is a standard for describing.
XML: Extensible Markup Language
A Stepwise Modeling Approach for Individual Media Semantics Annett Mitschick, Klaus Meißner TU Dresden, Department of Computer Science, Multimedia Technology.
A. Grigorov, A. Georgiev, M. Petrov, S. Varbanov, K. Stefanov Building a Knowledge Repository for Life-long Competence Development.
Connect. Communicate. Collaborate Click to edit Master title style MODULE 1: perfSONAR TECHNICAL OVERVIEW.
1 Introduction to XML. XML eXtensible implies that users define tag content Markup implies it is a coded document Language implies it is a metalanguage.
Xyleme A Dynamic Warehouse for XML Data of the Web.
Visual Web Information Extraction With Lixto Robert Baumgartner Sergio Flesca Georg Gottlob.
Supervised by Prof. LYU, Rung Tsong Michael Department of Computer Science & Engineering The Chinese University of Hong Kong Prepared by: Chan Pik Wah,
COMP 6703 eScience Project Semantic Web for Museums Student : Lei Junran Client/Technical Supervisor : Tom Worthington Academic Supervisor : Peter Strazdins.
An Architecture for Creating Collaborative Semantically Capable Scientific Data Sharing Infrastructures Anuj R. Jaiswal, C. Lee Giles, Prasenjit Mitra,
ReQuest (Validating Semantic Searches) Norman Piedade de Noronha 16 th July, 2004.
The RDF meta model: a closer look Basic ideas of the RDF Resource instance descriptions in the RDF format Application-specific RDF schemas Limitations.
Cloud based linked data platform for Structural Engineering Experiment Xiaohui Zhang
System Design/Implementation and Support for Build 2 PDS Management Council Face-to-Face Mountain View, CA Nov 30 - Dec 1, 2011 Sean Hardman.
Presented to: By: Date: Federal Aviation Administration Enterprise Information Management SOA Brown Bag #2 Sam Ceccola – SOA Architect November 17, 2010.
Ontologies: Making Computers Smarter to Deal with Data Kei Cheung, PhD Yale Center for Medical Informatics CBB752, February 9, 2015, Yale University.
Overview for IHE The MITRE Corporation. Overview hData was originally developed by The MITRE Corporation – Internal R&D – Focus on simplifying Continuity.
Semantic Publishing Update Second TUC meeting Munich 22/23 April 2013 Barry Bishop, Ontotext.
The Semantic Web Service Shuying Wang Outline Semantic Web vision Core technologies XML, RDF, Ontology, Agent… Web services DAML-S.
Building Search Portals With SP2013 Search. 2 SharePoint 2013 Search  Introduction  Changes in the Architecture  Result Sources  Query Rules/Result.
OASIS ebXML Registry Standard Open Forum 2003 on Metadata Registries 10:30 – 11:15 January 20, 2003 Kathryn Breininger The Boeing Company Chair, OASIS.
1 XML as a preservation strategy Experiences with the DiVA document format Eva Müller, Uwe Klosa Electronic Publishing Centre Uppsala University Library,
MPEG-21 : Overview MUMT 611 Doug Van Nort. Introduction Rather than audiovisual content, purpose is set of standards to deliver multimedia in secure environment.
Introduction to MDA (Model Driven Architecture) CYT.
Marcel Casado NCAR/RAP WEATHER WARNING TOOL NCAR.
Metadata and Geographical Information Systems Adrian Moss KINDS project, Manchester Metropolitan University, UK
XML Registries Source: Java TM API for XML Registries Specification.
Ontologies and Lexical Semantic Networks, Their Editing and Browsing Pavel Smrž and Martin Povolný Faculty of Informatics,
Aude Dufresne and Mohamed Rouatbi University of Montreal LICEF – CIRTA – MATI CANADA Learning Object Repositories Network (CRSNG) Ontologies, Applications.
1 Schema Registries Steven Hughes, Lou Reich, Dan Crichton NASA 21 October 2015.
Ocean Observatories Initiative Data Management (DM) Subsystem Overview Michael Meisinger September 29, 2009.
STASIS Technical Innovations - Simplifying e-Business Collaboration by providing a Semantic Mapping Platform - Dr. Sven Abels - TIE -
Oracle Database 11g Semantics Overview Xavier Lopez, Ph.D., Dir. Of Product Mgt., Spatial & Semantic Technologies Souripriya Das, Ph.D., Consultant Member.
Efficient RDF Storage and Retrieval in Jena2 Written by: Kevin Wilkinson, Craig Sayers, Harumi Kuno, Dave Reynolds Presented by: Umer Fareed 파리드.
Presented by Scientific Annotation Middleware Software infrastructure to support rich scientific records and the processes that produce them Jens Schwidder.
Personalized Interaction With Semantic Information Portals Eric Schwarzkopf DFKI
© Geodise Project, University of Southampton, Knowledge Management in Geodise Geodise Knowledge Management Team Barry Tao, Colin Puleston, Liming.
Copyright © 2006 Pilothouse Consulting Inc. All rights reserved. Search Overview Search Features: WSS and Office Search Architecture Content Sources and.
OWL Representing Information Using the Web Ontology Language.
Introduction to the Semantic Web and Linked Data Module 1 - Unit 2 The Semantic Web and Linked Data Concepts 1-1 Library of Congress BIBFRAME Pilot Training.
Introduction to the Semantic Web and Linked Data
User Profiling using Semantic Web Group members: Ashwin Somaiah Asha Stephen Charlie Sudharshan Reddy.
Of 33 lecture 1: introduction. of 33 the semantic web vision today’s web (1) web content – for human consumption (no structural information) people search.
Data Integration Hanna Zhong Department of Computer Science University of Illinois, Urbana-Champaign 11/12/2009.
Scalable Hybrid Keyword Search on Distributed Database Jungkee Kim Florida State University Community Grids Laboratory, Indiana University Workshop on.
Issues in Ontology-based Information integration By Zhan Cui, Dean Jones and Paul O’Brien.
Dictionary based interchanges for iSURF -An Interoperability Service Utility for Collaborative Supply Chain Planning across Multiple Domains David Webber.
Ontology Resource Discussion
Search Engine using Web Mining COMS E Web Enhanced Information Mgmt Prof. Gail Kaiser Presented By: Rupal Shah (UNI: rrs2146)
JISC/NSF PI Meeting, June Archon - A Digital Library that Federates Physics Collections with Varying Degrees of Metadata Richness Department of Computer.
1 Ontolog OOR-BioPortal Comparative Analysis Todd Schneider 15 October 2009.
Personalized Recommendation of Related Content Based on Automatic Metadata Extraction Andreas Nauerz 1, Fedor Bakalov 2, Birgitta.
1 Open Ontology Repository initiative - Planning Meeting - Thu Co-conveners: PeterYim, LeoObrst & MikeDean ref.:
A Technical Overview Bill Branan DuraCloud Technical Lead.
Providing web services to mobile users: The architecture design of an m-service portal Minder Chen - Dongsong Zhang - Lina Zhou Presented by: Juan M. Cubillos.
A Portrait of the Semantic Web in Action Jeff Heflin and James Hendler IEEE Intelligent Systems December 6, 2010 Hyewon Lim.
OASIS ebXML Registry Standard Open Forum 2003 on Metadata Registries 10:30 – 11:15 January 20, 2003 Kathryn Breininger The Boeing Company Chair, OASIS.
Selected Semantic Web UMBC CoBrA – Context Broker Architecture  Using OWL to define ontologies for context modeling and reasoning  Taking.
Abstract MarkLogic Database – Only Enterprise NoSQL DB Aashi Rastogi, Sanket V. Patel Department of Computer Science University of Bridgeport, Bridgeport,
The Palantir Platform… …Changes in 2.3
Cloud based linked data platform for Structural Engineering Experiment
Grid Computing 7700 Fall 2005 Lecture 18: Semantic Grid
Grid Computing 7700 Fall 2005 Lecture 18: Semantic Grid
Session 2: Metadata and Catalogues
HingX Project Overview
LOD reference architecture
Presentation transcript:

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.

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 – KAoS Java libraries for constructing OWL Relies on Jena 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

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

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

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

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