An evolutionary approach to the representation of adverse events

One way to detect, monitor and prevent adverse events with the help of Information Technology is by using ontologies capable of representing three levels of reality: what is the case, what is believed about reality, and what is represented. We report on how Basic Formal Ontology and Referent Tracking exhibit this capability and how they are used to develop an adverse event ontology and related data annotation scheme for the European ReMINE project

An Ontology-Based Assistant For Analyzing Agents\u27 Activities

This thesis reports on work in progress on software that helps an analyst identify and analyze activities of actors (such as vehicles) in an intelligence-relevant scenario. A system is being developed to aid intelligence analysts, IAGOA ((Intelligence Analyst’s Geospatial and Ontological Assistant). Analysis may be accomplished by retrieving simulated satellite data of ground vehicles and interacting with software modules that allow the analyst to conjecture the activities in which the actor is engaged along with the (largely geospatial and temporal) features of the area of operation relevant to the natures of those activities. Activities are conceptualized by ontologies. The research relies on natural language components (semantic frames) gathered from the FrameNet lexical database, which captures the semantics of lexical items with an ontology using OWL. The software has two components, one for the analyst, and one for a modeler who produces HTML and parameterized KML documents used by the analyst. The most significant input to the modeler software is the FrameNet OWL file, and the interface for the analyst and, to some extent, the modeler is provided by the Google Earth API

An Analyst’s Geospatial and Ontological Assistant

We discuss an Intelligence Analyst’s Geospatial and Ontological Assistant (IAGOA) under development that associates an intelligence analyst’s understanding of an agent’s activities with the geospatial features of the area of operation where they take place. Activities are identified with frames for the corresponding verbs from the FrameNet lexical database. A modeler, using the FrameNet OWL distribution, produces software used by the analyst to update a KML file with annotations identifying instantiations of the frames elements of the relevant frames. The Google Earth API is used for rendering KML files and scripting. The agent is tracked and the analyst’s conjecture of its activity is simulated; the analyst can redo her conjecture if need be. IAGOA’s FrameNet-based approach instantiates concepts inherent in language, making explicit the activities and the constellation of role-fillers involved in these activities

Uncertainty in Ontologies: Dempster-Shafer Theory for Data Fusion Applications

Nowadays ontologies present a growing interest in Data Fusion applications. As a matter of fact, the ontologies are seen as a semantic tool for describing and reasoning about sensor data, objects, relations and general domain theories. In addition, uncertainty is perhaps one of the most important characteristics of the data and information handled by Data Fusion. However, the fundamental nature of ontologies implies that ontologies describe only asserted and veracious facts of the world. Different probabilistic, fuzzy and evidential approaches already exist to fill this gap; this paper recaps the most popular tools. However none of the tools meets exactly our purposes. Therefore, we constructed a Dempster-Shafer ontology that can be imported into any specific domain ontology and that enables us to instantiate it in an uncertain manner. We also developed a Java application that enables reasoning about these uncertain ontological instances.Comment: Workshop on Theory of Belief Functions, Brest: France (2010

Collecting Open Source Intelligence via Tailored Information Delivery Systems

The Internet offers a plethora of freely available information for possible use in Open Source Intelligence (OSINT) operations. However, along with this information come challenges in finding relevant information and overcoming information overload. This paper presents the results of an ongoing research in a Tailored Information Delivery Services (TIDS) system that aids users in retrieving relevant information through various open intelligence sources. The TIDS provides a semantics-based query constructor that operates in a “What You Get is What You Need (WYGIWYNTM)” fashion and builds ontology based information tagging, theme extractor, and contextual model

Warranted Diagnosis

A diagnostic process is an investigative process that takes a clinical picture as input and outputs a diagnosis. We propose a method for distinguishing diagnoses that are warranted from those that are not, based on the cognitive processes of which they are the outputs. Processes designed and vetted to reliably produce correct diagnoses will output what we shall call ‘warranted diagnoses’. The latter are diagnoses that should be trusted even if they later turn out to have been wrong. Our work is based on the recently developed Cognitive Process Ontology and further develops the Ontology of General Medical Science. It also has applications in fields such as intelligence, forensics, and predictive maintenance, all of which rely on vetted processes designed to secure the reliability of their outputs

Barry Smith an sich

Festschrift in Honor of Barry Smith on the occasion of his 65th Birthday. Published as issue 4:4 of the journal Cosmos + Taxis: Studies in Emergent Order and Organization. Includes contributions by Wolfgang Grassl, Nicola Guarino, John T. Kearns, Rudolf Lüthe, Luc Schneider, Peter Simons, Wojciech Żełaniec, and Jan Woleński

Semantic Query Reasoning in Distributed Environment

Master's thesis in Computer scienceSemantic Web aims to elevate simple data in WWW to semantic layer, so that knowledge, processed by machine, can be shared more easily. Ontology is one of the key technologies to realize Semantic Web. Semantic reasoning is an important step in Semantic technology. For Ontology developers, semantic reasoning finds out collisions in Ontology definition, and optimizes it; for Ontology users, semantic reasoning retrieves implicit knowledge from known knowledge. The main research of this thesis is reasoning of semantic data querying in distributed environment, which tries to get correct results of semantic data querying, given Ontology definition and data. This research studied two methods: data materialization and query rewriting. Using Amazon cloud computing service and LUBM, we compared these two methods, and have concluded that when size of data to be queried scales up, query rewriting is more feasible than data materialization. Also, based on the conclusion, we developed an application, which manages and queries semantic data in a distributed environment. This application can be used as a prototype of similar applications, and a tool for other Semantic Web researches as well