Business analysts frequently use Cockpits or Dashboards as front ends to data warehouses for inspecting and comparing multi-dimensional data at various levels of detail. These tools, however, perform badly in supporting a business analyst in his or her business intelligence task of understanding and evaluating a business within its environmental context through comparative data analysis. With important business knowledge either unrepresented or represented in a form not processable by automatic reasoning, the analyst is limited in the analyses that can be formulated and she or he heavily suffers from information overload with the need to re-judge similar situations again and again, and to re-discriminate between already explained and novel relationships between data. The aim of the proposed research is to develop a Semantic Cockpit that, by exploiting and extending semantic technologies, intelligently assists and guides the business analyst in defining analysis tasks and in discriminating between usual phenomena and novel interesting situations to be followed up. The envisioned Semantic Cockpit is an intelligent partner of the business analyst due to reasoning about various kinds of knowledge, explicitly represented by machine-processable ontologies, such as organisation-internal knowledge, organisation external domain knowledge, the semantics of measures and scores, knowledge about insights gained from previous analysis, and knowledge about how to act upon unusually low or high comparison scores (judgment knowledge). The significance of the project is the development of a prototype of a Semantic Cockpit in the health domain, in which the project coordinator has business intelligence solutions in place. To develop the necessary semantic techniques for this prototype will also substantially advance the state-of-the-art in ontology languages, ontology design, and ontology reasoning, and the interaction between multidimensional databases, situation-condition-action rules, and ontologies. Among others, the following outcomes are envisioned: a multi-dimensional measure and score ontology language, a reasoner and an editor for this language, a multi-dimensional ontology-based rule language and associated rule engine for representing and executing judgment knowledge. The Semantic Cockpit will be demonstrated by a show case from health insurance partners.
|Duration||2011 - 2013|
|Funding||FIT-IT - Semantic Systems and Services under grant FFG-829594|