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R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences OIC-2009 - ONTOLOGY FOR THE INTELLIGENCE COMMUNITY: Setting the Stage for High-level Knowledge Fusion Referent Tracking for Command & Control Messaging Systems Fairfax, VA - 21 -22 October 2009 Shahid MANZOOR, Werner CEUSTERS, Barry SMITH Center of Excellence in Bioinformatics and Life Sciences University at Buffalo, NY, USA http: //www. org. buffalo. edu/RTU

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Ultimate goal of Referent Tracking A digital copy of the world

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Requirements for this digital copy • R 1: • R 2 A faithful representation of reality … of everything that is digitally registered, what is generic scientific theories what is specific what individual entities exist and how they relate • R 3: • R 4 … throughout reality’s entire history, … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, . . .

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R 1: A faithful representation of reality … … recognizes three levels: 1. The (first order) reality which exists ‘as it is’ prior to a cognitive agent’s perception thereof; 2. the cognitive representations of this reality embodied in observations and interpretations on the part of cognitive agents; 3. the publicly accessible concretizations constructed through cognitive insights as artifacts representing first order reality of which ontologies, terminologies and data repositories are examples. Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Universal Core (UCORE) 2. 0 • Built to facilitate sharing of US Govt. related data. • Uses XML as a standard format for information exchange. • It provides consensus representations under the heading of Who, What, When and Where terms

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences UCORE Ontology

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences UCORE XML Message ucore-message ESS Army Net-Centric Data Strategy Center of Excellence

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Referent Tracking System

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Referent Tracking System Components • Referent Tracking Software Manipulation of statements about facts and beliefs • Referent Tracking Datastore: • IUI repository A collection of globally unique singular identifiers denoting particulars • Referent Tracking Database A collection of facts and beliefs about the particulars denoted in the IUI repository Manzoor S, Ceusters W, Rudnicki R. Implementation of a Referent Tracking System. International Journal of Healthcare Information Systems and Informatics 2007; 2(4): 41 -58.

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Elementary RTS tuple types Relationships between particulars taken from a realism-based relation ontology Instantiation of a universal Annotation using terms from a nonrealist terminology ‘Negative findings’ such as absences, missing parts, preventions, … Names for a particular

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Formalism includes management of changes 1. changes in the underlying reality: • Particulars come, change and go 2. changes in our (scientific) understanding: • The plant Vulcan does not exist 3. reassessments of what is considered to be relevant for inclusion (notion of purpose). 4. encoding mistakes introduced during data entry or ontology development.

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences RTS architecture

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Objectives • Parsing UCORE XML messages – Assert representations of message content in RTS • For the existence of entities – L 1/L 2/L 3 • for the relationships found between the entities. • for the entities instantiation relation with UCORE ontology universals. – Validation of XML messages on ontological grounds

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Message Transformation Flow UCORE Messages Ontology Rules Reasoner reads XML Message Middleware Communicate with RTS to assign IUI to entity referred to in XML message RTS

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Message Parsing into Triples (Step 1) • Iterates over the XML message through Depth First strategy – Treats each XML element as a relation between possible entities – At this moment middleware does not use any knowledge of ontology and RTS ESS Army Net-Centric Data Strategy Center of Excellence rts: 1002 rts: 1003 rts: 1006 rts: 1007 rts: 1008 ulex: Publish. Message Data. Submitter. Metadata System. Identifier System. Contact Organization name rts: 1003 rts: 1006 “ESS” rts: 1007 rts: 1008 “Army Net. Centric …

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences XML Transformation Into Triples Step 1 Triples Visualization

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Triples Transformation By Rules (Step 2) • Use rule to add or remove triples • A rule consists of triples divided into parts: – Head: Transformation Pattern – Body: Search pattern e. g. : ? x ulex: Publish. Message ? y -> ? x ro: instanceof uc: Document If two ‘potential entities’ are linked by the ulex: Publis. Message element, then the first one is a genuine entity of type UCore: document

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Output after the execution of step 2 (1)

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Output after the execution of step 2 (2)

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Tracking of Entities (Step 3) • Resolve whether an entity is already assigned an IUI or not. • Suppose that the middleware receives second message. The message refers to the 4 th Brigade. So during the execution of this step, reference to this military will be done through IUI #1011 which was already registered for it in the RTS.

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Message 2: After the processing of three steps

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences Reasoning validation • In the second message, unit #1011’s supplies level (#2019) concerning its equipment stock #9001 is ‘ 2’. • Implemented rule: if the supply level for this type of equipment is less then 3, then generate alert to the effect that the troops are not ready for the mission. (? x uct: has. Equipment. Supplies ? y) (? z uct: equipment. Supplies. Level. Of ? y) (? z readiness. reporting: Equipment. Supplies. Resource. Area. Level ? l) less. Than(? l, 3) -> print(“The unit ”, ? x, “ is not ready for mission”)

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences UCORE XML Message (1) ucoremessage 1 Executive Support System (ESS) Readiness Support

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences UCORE XML Message (2) Army Net-Centric Data Strategy Center of Excellence A military unit specified by a Unit Identification Code, UIC Name, and related readiness related properties.

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences UCORE XML Message (3) 4 th Brigade Represents a Readiness Report for a military unit. 1

R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences UCORE XML Message (4)