Uniform management of heterogeneous semi-structured information sources

Nowadays, data can be represented and stored by using different formats ranging from non structured data, typical of file systems, to semi-structured data, typical of Web sources, to highly structured data, typical of relational database systems. Therefore, the necessity arises to define new tools and models for uniformly handling all these heterogeneous information sources. In this paper we propose both a framework and a conceptual model which aim at uniformly managing information sources having different nature and structure for obtaining a global, integrated and uniform representation. We show also how the proposed framework and the conceptual model can be useful in many application contexts

Survey: Models and Prototypes of Schema Matching

Schema matching is critical problem within many applications to integration of data/information, to achieve interoperability, and other cases caused by schematic heterogeneity. Schema matching evolved from manual way on a specific domain, leading to a new models and methods that are semi-automatic and more general, so it is able to effectively direct the user within generate a mapping among elements of two the schema or ontologies better. This paper is a summary of literature review on models and prototypes on schema matching within the last 25 years to describe the progress of and research chalenge and opportunities on a new models, methods, and/or prototypes

An Ontology Based Approach To The Integration Of Heterogeneous Information Systems Supporting Integrated Provincial Administration In Khon Kaen, Thailand

Information systems are a necessity to the administration of organizations. In a recent reform to the Thai administration, the governor of each province is entrusted with the full responsibility for the strategic planning and execution of the Integrated Provincial Administration (IPA). This presents a big challenge and many difficult problems for a potentially fast growing, both economically and demographically, province, such as Khon Kaen. To provide the administrator of the province with reliable and up to date information, the Provincial Operation Centre (POC) has been set up and assigned the task of collecting all required information from disparate information systems, many of which are legacy systems. This information lacks interoperability and integration of data due to many different structures and semantic heterogeneity encountered in many information systems. This research is a part of a collaborative data sources community development project. It attempts to aid high-level decision makers by using ontology to resolve heterogeneities among many disparate data sources. After relevant data sources are identified, they are analysed to reveal important and corresponding concepts, attributes and relations. They are then used in the creation of ontologies to resolve schematic and semantic conflicts in the data sources. The integration of many heterogeneous information systems will provide a unified view of information facilitating the provincial administrator in his decision making

Information exchange between medical databases through automated identification of concept equivalence

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2002."February 2002."Includes bibliographical references (p. 123-127).The difficulty of exchanging information between heterogeneous medical databases remains one of the chief obstacles in achieving a unified patient medical record. Although methods have been developed to address differences in data formats, system software, and communication protocols, automated data exchange between disparate systems still remains an elusive goal. The Medical Information Acquisition and Transmission Enabler (MEDIATE) system identifies semantically equivalent concepts between databases to facilitate information exchange. MEDIATE employs a semantic network representation to model underlying native databases and to serve as an interface for database queries. This representation generates a semantic context for data concepts that can subsequently be exploited to perform automated concept matching between disparate databases. To test the feasibility of this system, medical laboratory databases from two different institutions were represented within MEDIATE and automated concept matching was performed. The experimental results show that concepts that existed in both laboratory databases were always correctly recognized as candidate matches.(cont.) In addition, concepts which existed in only one database could often be matched with more "generalized" concepts in the other database that could still provide useful information. The architecture of MEDIATE offers advantages in system scalability and robustness. Since concept matching is performed automatically, the only work required to enable data exchange is construction of the semantic network representation. No pre-negotiation is required between institutions to identify data that is compatible for exchange, and there is no additional overhead to add more databases to the exchange network. Because the concept matching occurs dynamically at the time of information exchange, the system is robust to modifications in the underlying native databases as long as the semantic network representations are appropriately updated.by Yao Sun.Ph.D