This paper presents a new approach, in handling data (encoding, managing and retrieving) in secure sensitive and classified organisations (such as Law Enforcement Agencies (LEAs)), that utilises Web 3.0 technologies as well as knowledge management techniques and pushing of information. This approach signals a departure from current use of databases and pulling of information technologies as well as allowing separation of concerns between how data are organised/structured and how data are manipulated/processed. Such an approach utilises an adaptive knowledge management platform capable of supporting organisational operations of LEAs using data aggregated from assorted, heterogeneous and online sources. Such knowledge is then pushed to the users, using recommenders, in an effortless manner addressing the needs of the organisation. Moreover, the system is designed to afford easier change of operational needs through the addition and removal of multiple folksonomies (representing changes in focus or new trends). These changes are further enriched with semantics providing specialised domain-specific content recommendations and semantically enriched search capabilities. This approach to knowledge retrieval has been applied to the domain of homemade explosives and counter-terrorism efforts as part of the HOMER project, where data are aggregated from sources such as police databases, online forums and explosives wikis. Data are stored in an unstructured manner and annotated by the users, ultimately being categorised as per the knowledge retrieval needs of the organisation, which in this case is to carry out efficient and effective investigations regarding homemade explosives. We describe the architecture of a system that can efficiently and effectively support related investigatory activities, and we also present an evaluation from the perspective of the end-users.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)