مدیریت و سیر تکاملی هستی شناسی برای هوش کسب و کار(هوش تجاری)

The amount of heterogeneous data that is available to organizations nowadays has made information management a seriously complicated task, yet crucial since this data can be a valuable asset for business intelligence. Ontologies can act as a semantically rich knowledge base in systems that specialize in information management. The present work investigates the potential of ontologies in supporting the information lifecycle within a corporate environment for business intelligence. The paper demonstrates the use of Heraclitus II, a framework that employs ontology management and evolution in the context of information management systems. The capabilities of the framework in facilitating information management and business intelligence are evaluated through a real-life case study from the life sciences industry.

The rate of growth in the amount of information available nowadays within a corporate environment poses major difficulties as well as challenges in decision making. Business intelligence (BI) consists of a collection of techniques and tools, aiming at providing businesses with the necessary support for decision making. Examples of simple BI services that already exist are various search and filtering services, as well as various content providers and aggregators that deliver semi-custom information bundles to particular users. On a more sophisticated level, information management (IM) can assist a manager in monitoring specific organizations, technologies, or areas of research, as well as being able to analyze primary data in order to draw conclusions at the level of the company's competition, sector or industry. Ontologies are a key enabling technology for IM, as they offer information a common representation and semantics. They constitute “a shared and common understanding of a domain that can be communicated between people and application systems” (Davies, Fensel, & Harmelen, 2003). An ontology comprises a formal description of a certain domain, by defining the ontology objects (or entities) that characterise the domain, namely concepts (or classes), as well as their instances and relations. Ontologies express information in a machine-processable form, thus allowing for its efficient manipulation by software agents. They are commonly represented with the use of XML-based languages, such as RDFS (www.w3.org/TR/rdf-schema) and OWL (www.w3.org/TR/owl-features). Ontologies provide to IM systems a semantically rich knowledge base for interpretation of unstructured content. Based on the semantics encoded within ontologies, information can be extracted from natural language texts and, on a further level of processing, knowledge can be discovered that will assist BI. Nevertheless, the way ontologies are usually managed within IM systems is unsophisticated and disregard important factors. Ontology layering or integration is rarely used and the dynamic aspect of ontologies, which requires appropriate evolution mechanisms, is often neglected. Overall, the potential of ontologies in IM and BI has yet to be fully realized and put to practical use.

The Heraclitus II framework employs bitemporal modelling and a layering architecture for the management and evolution of ontologies within IM systems. A practical application of the framework on a case study from the life sciences industry has provided us with an insight of the problems and challenges related with BI. Heraclitus II provides solutions in ontology construction, integration, and maintenance. In addition, the proposed bitemporal evolution model aims at enhancing the temporal expressivity of ontologies, thus having a direct positive impact on BI. Heraclitus II offers various opportunities for further research. One interesting direction to follow would be towards establishing OWL extensions based on the Heraclitus II bitemporal modelling. Work in this area so far (W3c, 2006) has proposed only basic temporal OWL structures, such as interval and duration. The Heraclitus II bitemporal ontology model can offer additional, more expressive structures, regarding the two time dimensions as well as the lifespan and history of ontology objects. Another addition to Heraclitus II that is worth pursuing is related to the collaborative aspects. In particular, offering the ability of managing the knowledge base in a concurrent fashion, improving the users privilege scheme, as well as working on the scalability of the framework, are important areas for further investigation. Exploring additional domains and applying the framework in more case studies can offer a better understanding of issues related to IM and BI. A potential area for further research is the construction and maintenance of the ontology pyramid, through the incorporation of Social Web technologies, such as folksonomies. Heraclitus II could in this way function as a testbed toward building a Social Semantic Web (Mikroyannidis, 2007).