Improving data quality through effective use of data semantics
Data & Knowledge Engineering - Special issue: WIDM 2004
Contextual alignment of ontologies in the eCOIN semantic interoperability framework
Information Technology and Management
Implementing the COntext INterchange (COIN) Approach through Use of Semantic Web Tools
Semantic Web, Ontologies and Databases
Scalable interoperability through the use of COIN lightweight ontology
ODBIS'05/06 Proceedings of the First and Second VLDB conference on Ontologies-based databases and information systems
TES'04 Proceedings of the 5th international conference on Technologies for E-Services
Information aggregation using the caméléon# web wrapper
EC-Web'05 Proceedings of the 6th international conference on E-Commerce and Web Technologies
Representation and reasoning about changing semantics in heterogeneous data sources
SWDB'04 Proceedings of the Second international conference on Semantic Web and Databases
SWDB'04 Proceedings of the Second international conference on Semantic Web and Databases
A context model for semantic mediation in web services composition
ER'06 Proceedings of the 25th international conference on Conceptual Modeling
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With the advances in telecommunications, and the introduction of the Internet, information systems achieved physical connectivity, but have yet to establish logical connectivity. Lack of logical connectivity is often inviting disaster as in the case of Mars Orbiter, which was lost because one team used metric units, the other English while exchanging a critical maneuver data. In this Thesis, we focus on the two intertwined sub problems of logical connectivity, namely data extraction and data interpretation in the domain of heterogeneous information systems. The first challenge, data extraction, is about making it possible to easily exchange data among semi-structured and structured information systems. We describe the design and implementation of a general purpose, regular expression based Caméléon wrapper engine with an integrated capabilities-aware planner/optimizer/executioner. The second challenge, data interpretation, deals with the existence of heterogeneous contexts, whereby each source of information and potential receiver of that information may operate with a different context, leading to large-scale semantic heterogeneity. We extend the existing formalization of the COIN framework with new logical formalisms and features to handle larger set of heterogeneities between data sources. This extension, named Extended Context Interchange (ECOIN), is motivated by our analysis of financial information systems that indicates that there are three fundamental types of heterogeneities in data sources: contextual, ontological, and temporal. While COIN framework was able to deal with the contextual heterogeneities, ECOIN framework expands the scope to include ontological heterogeneities as well. In particular, we are able to deal with equational ontological conflicts (EOC), which refer to the heterogeneity in the way data items are calculated from other data items in terms of definitional equations. ECOIN provides a context-based solution to the EOC problem based on a novel approach that integrates abductive reasoning and symbolic equation solving techniques in a unified framework. Furthermore, we address the merging of independently built ECOIN applications, which involves merging disparate ontologies and contextual knowledge. The relationship between ECOIN and the Semantic Web is also discussed. Finally, we demonstrate the feasibility and features of our integration approach with a prototype implementation that provides mediated access to heterogeneous information systems. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)