Open issues in semantic query optimization in relational DBMS

After two decades of research into Semantic Query Optimization (SQO) there is clear agreement as to the efficacy of SQO. However, although there are some experimental implementations there are still no commercial implementations. We first present a thorough analysis of research into SQO. We identify three problems which inhibit the effective use of SQO in Relational Database Management Systems(RDBMS). We then propose solutions to these problems and describe first steps towards the implementation of an effective semantic query optimizer for relational databases

Towards Analytics Aware Ontology Based Access to Static and Streaming Data (Extended Version)

Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data

Implementation of Combat Simulation Through Expert Support Systems

The battlefield simulation is often faced with a bewildering array of conflicting stresses and challenges. Communication is currently slower and more costly than computation. Expert System technologies such as production rule systems allow one to acquire and represent the collection of heuristic rules in computer compatible form. The system also include master control programs that determine the order in which these rules should be applied against the monitored system performance to arrive at appropriate system control. These expert systems are used in two nodes, both as an intelligence assistant to the expert, amplifying the capacity and quality of his work, and as a surrogate for an expert when he is not available. An Expert support System (ESS) designed and developed for combat simulation has been enumerated in this article. The quality and the reliability of the inferred tactical situation is improved by using PROLOG. This formal AI language is used for validating and checking sensor detections for consistency and logical plausibility. The supremacy of PROLOG for creating and interrogating a data base helps maintaining a reasonably coherent feature of the tactical situation. The perils and pitfalls of tackling with expert systems have also been underscored

Expert Systems and Artificial Neural Networks for Spatial Analysis and Modelling: Essential Components for Knowledge-Based Geographical Information Systems

Series: Discussion Papers of the Institute for Economic Geography and GIScienc