Ontologies for situation-based crime scene identities
| Autor: | William Nick, Emma Sloan, Marguerite McDaniel, Albert Esterline, James Mayes |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
Process ontology Ontology-based data integration 02 engineering and technology computer.file_format Ontology (information science) Computer security computer.software_genre Semantics Data science 020204 information systems 0202 electrical engineering electronic engineering information engineering Identity (object-oriented programming) Crime scene Upper ontology 020201 artificial intelligence & image processing RDF computer |
| Zdroj: | SoutheastCon 2017. |
| DOI: | 10.1109/secon.2017.7925329 |
| Popis: | Our interests are in establishing the identity of agents in physical and cyber environments and determining how evidence in cases support identity judgments. Current work centers on physical evidence from a crime scene; however, what is presented is a computational framework that expands to the cyber world. Part of the project's foundation is based on Barwise's situation theory because it joins semantics for utterances and accounts of perceptions. Situations both support items of information and carry information about other situations. Specifically, an utterance situation contains information about a described situation. We provide an account of the support for an identity judgment (in an id-situation) that essentially builds cases (aligned to legal cases) called id-cases, because significant cases of identity can lead to various situations that impact the value of evidence. Our framework includes a situation ontology, upon which an id-situation ontology is built. While focusing on physical evidence, we also developed a physical biometrics ontology, which the physical features ontology supports. Additionally, there is a law enforcement ontology and several supporting stubs. We show how a specific case is encoded in RDF in alignment with our ontologies, and complement our id-situation ontology with SWRL rules to infer a culprit in a crime scene. |
| Databáze: | OpenAIRE |
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