Ontologies for situation-based crime scene identities

McDaniel, Marguerite; Sloan, Emma; Nick, William; Mayes, James; Esterline, Albert

doi:10.1109/secon.2017.7925329

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…In [30] is presented a computational framework that focuses on physical evidence from a crime scene. This framework has three main components: -a physical biometrics ontology, a law enforcement ontology and several supporting stubs.…”

Section: Related Workmentioning

confidence: 99%

Towards Designing a Knowledge Graph-Based Framework for Investigating and Preventing Crime on Online Social Networks

Elezaj

Yayilgan

Kalemi

et al. 2019

Communications in Computer and Information Science

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Online Social Networks (OSNs) have fundamentally and permanently altered the arena of digital and classical crime. Recently, law enforcement agencies (LEAs) have been using OSNs as a data source to collect Open Source Intelligence for fighting and preventing crime. However, most existing technological developments for LEAs to fight and prevent crime rely on conventional database technology, which poses problems. As social network usage is increasing rapidly, storing and querying data for information retrieval is critical because of the characteristics of social networks, such as unstructured nature, high volumes, velocity, and data interconnectivity. This paper presents a knowledge graph-based framework, an outline of a framework designed to support crime investigators solve and prevent crime, from data collection to inferring digital evidence admissible in court. The main component of the proposed framework is a hybrid ontology linked to a graph database, which provides LEAs with the possibility to process unstructured data and identify hidden patterns and relationships in the interconnected data of OSNs.

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Section: Related Workmentioning

confidence: 99%

Towards Designing a Knowledge Graph-Based Framework for Investigating and Preventing Crime on Online Social Networks

Elezaj

Yayilgan

Kalemi

et al. 2019

Communications in Computer and Information Science

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“…Our framework consists of OWL ontologies that are used to encode information on a case in an RDF triple store. We use the query language SPARQL (SPARQL Protocol and RDF Query Language) to execute queries per each case [8], [9]. RDF expresses simple propositions as triples of the form subject property object, stating that subject and object are related by binary relation property.…”

Section: Our Ontologiesmentioning

confidence: 99%

A Computational Framework for Identity Based on Situation Theory

Mason

Kyei

Long

et al. 2018

ISASE

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This paper presents a computational framework for identity (initially about the culprit in a crime scene) based on Barwise's situation theory. Situations support information and can carry information about other situations. An utterance situation carries information about a described situation thanks to the constraints imposed by natural language. We are concerned with utterance situations in which identity judgments are made about the culprit in a crime scene, which is the corresponding described situation. The id-situation and crime scene along with various resource situations make up a case in the legal sense. We have developed OWL ontologies to provide concepts and principled vocabularies for encoding our scenarios in RDF, and we present an example of a SPARQL query of one of our encodings that spans situations. To follow how evidence supports hypotheses on the identity of the culprit in a crime scene, we use Dempster-Shafer theory. We tightly integrate it with our ontologies by having the representation of a case per our ontologies present a network containing situations and stitched together by objects; evidence "flows" along this network, diminishing and combining. We review the modifications of Dempster-Shafer theory required when one goes from a closed-world assumption to an open-world assumption. We review our plans regarding equational reasoning based on identities established in our id-cases, and we review the related issues regarding the meanings of URIs.

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