Conceptual information processing: A robust approach to KBS-DBMS integration

Integrating the respective functionality and architectural features of knowledge base and data base management systems is a topic of considerable interest. Several aspects of this topic and associated issues are addressed. The significance of integration and the problems associated with accomplishing that integration are discussed. The shortcomings of current approaches to integration and the need to fuse the capabilities of both knowledge base and data base management systems motivates the investigation of information processing paradigms. One such paradigm is concept based processing, i.e., processing based on concepts and conceptual relations. An approach to robust knowledge and data base system integration is discussed by addressing progress made in the development of an experimental model for conceptual information processing

Kolmogorov Complexity in perspective. Part II: Classification, Information Processing and Duality

We survey diverse approaches to the notion of information: from Shannon entropy to Kolmogorov complexity. Two of the main applications of Kolmogorov complexity are presented: randomness and classification. The survey is divided in two parts published in a same volume. Part II is dedicated to the relation between logic and information system, within the scope of Kolmogorov algorithmic information theory. We present a recent application of Kolmogorov complexity: classification using compression, an idea with provocative implementation by authors such as Bennett, Vitanyi and Cilibrasi. This stresses how Kolmogorov complexity, besides being a foundation to randomness, is also related to classification. Another approach to classification is also considered: the so-called "Google classification". It uses another original and attractive idea which is connected to the classification using compression and to Kolmogorov complexity from a conceptual point of view. We present and unify these different approaches to classification in terms of Bottom-Up versus Top-Down operational modes, of which we point the fundamental principles and the underlying duality. We look at the way these two dual modes are used in different approaches to information system, particularly the relational model for database introduced by Codd in the 70's. This allows to point out diverse forms of a fundamental duality. These operational modes are also reinterpreted in the context of the comprehension schema of axiomatic set theory ZF. This leads us to develop how Kolmogorov's complexity is linked to intensionality, abstraction, classification and information system.Comment: 43 page

Automatic Verification of Transactions on an Object-Oriented Database

In the context of the object-oriented data model, a compiletime approach is given that provides for a significant reduction of the amount of run-time transaction overhead due to integrity constraint checking. The higher-order logic Isabelle theorem prover is used to automatically prove which constraints might, or might not be violated by a given transaction in a manner analogous to the one used by Sheard and Stemple (1989) for the relational data model. A prototype transaction verification tool has been implemented, which automates the semantic mappings and generates proof goals for Isabelle. Test results are discussed to illustrate the effectiveness of our approach

Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

Dynamic Integration of Evolving Distributed Databases using Services

This thesis investigates the integration of many separate existing heterogeneous and distributed databases which, due to organizational changes, must be merged and appear as one database. A solution to some database evolution problems is presented. It presents an Evolution Adaptive Service-Oriented Data Integration Architecture (EA-SODIA) to dynamically integrate heterogeneous and distributed source databases, aiming to minimize the cost of the maintenance caused by database evolution. An algorithm, named Relational Schema Mapping by Views (RSMV), is designed to integrate source databases that are exposed as services into a pre-designed global schema that is in a data integrator service. Instead of producing hard-coded programs, views are built using relational algebra operations to eliminate the heterogeneities among the source databases. More importantly, the definitions of those views are represented and stored in the meta-database with some constraints to test their validity. Consequently, the method, called Evolution Detection, is then able to identify in the meta-database the views affected by evolutions and then modify them automatically. An evaluation is presented using case study. Firstly, it is shown that most types of heterogeneity defined in this thesis can be eliminated by RSMV, except semantic conflict. Secondly, it presents that few manual modification on the system is required as long as the evolutions follow the rules. For only three types of database evolutions, human intervention is required and some existing views are discarded. Thirdly, the computational cost of the automatic modification shows a slow linear growth in the number of source database. Other characteristics addressed include EA-SODIA’ scalability, domain independence, autonomy of source databases, and potential of involving other data sources (e.g.XML). Finally, the descriptive comparison with other data integration approaches is presented. It shows that although other approaches may provide better performance of query processing in some circumstances, the service-oriented architecture provide better autonomy, flexibility and capability of evolution