1,059 research outputs found

    Uniform management of heterogeneous semi-structured information sources

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    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

    Electronic Medical Records

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    Electronic Medical Record (EMR) relational database is considered to be a major component of any medical care information system. A major problem for researchers in medical informatics is finding the best way to use these databases to extract valued useful information to and about the patient’s diseases and treatments. Integrating different EMR databases is a great achievement that will improve health care systems. This paper presents an AI approach to extract generic EMR from different resources and transfer them to clinical cases. The utilized approach is based on retrieving different relationships between patients’ different data tables (files) and automatically generating EMRs in XML format, then building frame based medical cases to form a case repository that can be used in medical diagnostic systems

    Context knowledge representation and reasoning in the context interchange system

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    "October, 1999."Includes bibliographical references (p. 13-14).Stephane Bressan ... [et al.

    On the Foundations of Data Interoperability and Semantic Search on the Web

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    This dissertation studies the problem of facilitating semantic search across disparate ontologies that are developed by different organizations. There is tremendous potential in enabling users to search independent ontologies and discover knowledge in a serendipitous fashion, i.e., often completely unintended by the developers of the ontologies. The main difficulty with such search is that users generally do not have any control over the naming conventions and content of the ontologies. Thus terms must be appropriately mapped across ontologies based on their meaning. The meaning-based search of data is referred to as semantic search, and its facilitation (aka semantic interoperability) then requires mapping between ontologies. In relational databases, searching across organizational boundaries currently involves the difficult task of setting up a rigid information integration system. Linked Data representations more flexibly tackle the problem of searching across organizational boundaries on the Web. However, there exists no consensus on how ontology mapping should be performed for this scenario, and the problem is open. We lay out the foundations of semantic search on the Web of Data by comparing it to keyword search in the relational model and by providing effective mechanisms to facilitate data interoperability across organizational boundaries. We identify two sharply distinct goals for ontology mapping based on real-world use cases. These goals are: (i) ontology development, and (ii) facilitating interoperability. We systematically analyze these goals, side-by-side, and contrast them. Our analysis demonstrates the implications of the goals on how to perform ontology mapping and how to represent the mappings. We rigorously compare facilitating interoperability between ontologies to information integration in databases. Based on the comparison, class matching is emphasized as a critical part of facilitating interoperability. For class matching, various class similarity metrics are formalized and an algorithm that utilizes these metrics is designed. We also experimentally evaluate the effectiveness of the class similarity metrics on real-world ontologies. In order to encode the correspondences between ontologies for interoperability, we develop a novel W3C-compliant representation, named skeleton

    Viewpoints on emergent semantics

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    Authors include:Philippe Cudr´e-Mauroux, and Karl Aberer (editors), Alia I. Abdelmoty, Tiziana Catarci, Ernesto Damiani, Arantxa Illaramendi, Robert Meersman, Erich J. Neuhold, Christine Parent, Kai-Uwe Sattler, Monica Scannapieco, Stefano Spaccapietra, Peter Spyns, and Guy De Tr´eWe introduce a novel view on how to deal with the problems of semantic interoperability in distributed systems. This view is based on the concept of emergent semantics, which sees both the representation of semantics and the discovery of the proper interpretation of symbols as the result of a self-organizing process performed by distributed agents exchanging symbols and having utilities dependent on the proper interpretation of the symbols. This is a complex systems perspective on the problem of dealing with semantics. We highlight some of the distinctive features of our vision and point out preliminary examples of its applicatio

    A semantic and agent-based approach to support information retrieval, interoperability and multi-lateral viewpoints for heterogeneous environmental databases

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    PhDData stored in individual autonomous databases often needs to be combined and interrelated. For example, in the Inland Water (IW) environment monitoring domain, the spatial and temporal variation of measurements of different water quality indicators stored in different databases are of interest. Data from multiple data sources is more complex to combine when there is a lack of metadata in a computation forin and when the syntax and semantics of the stored data models are heterogeneous. The main types of information retrieval (IR) requirements are query transparency and data harmonisation for data interoperability and support for multiple user views. A combined Semantic Web based and Agent based distributed system framework has been developed to support the above IR requirements. It has been implemented using the Jena ontology and JADE agent toolkits. The semantic part supports the interoperability of autonomous data sources by merging their intensional data, using a Global-As-View or GAV approach, into a global semantic model, represented in DAML+OIL and in OWL. This is used to mediate between different local database views. The agent part provides the semantic services to import, align and parse semantic metadata instances, to support data mediation and to reason about data mappings during alignment. The framework has applied to support information retrieval, interoperability and multi-lateral viewpoints for four European environmental agency databases. An extended GAV approach has been developed and applied to handle queries that can be reformulated over multiple user views of the stored data. This allows users to retrieve data in a conceptualisation that is better suited to them rather than to have to understand the entire detailed global view conceptualisation. User viewpoints are derived from the global ontology or existing viewpoints of it. This has the advantage that it reduces the number of potential conceptualisations and their associated mappings to be more computationally manageable. Whereas an ad hoc framework based upon conventional distributed programming language and a rule framework could be used to support user views and adaptation to user views, a more formal framework has the benefit in that it can support reasoning about the consistency, equivalence, containment and conflict resolution when traversing data models. A preliminary formulation of the formal model has been undertaken and is based upon extending a Datalog type algebra with hierarchical, attribute and instance value operators. These operators can be applied to support compositional mapping and consistency checking of data views. The multiple viewpoint system was implemented as a Java-based application consisting of two sub-systems, one for viewpoint adaptation and management, the other for query processing and query result adjustment

    A Survey of the State of Dataspaces

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    Published in International Journal of Computer and Information Technology.This paper presents a survey of the state of dataspaces. With dataspaces becoming the modern technique of systems integration, the achievement of complete dataspace development is a critical issue. This has led to the design and implementation of dataspace systems using various approaches. Dataspaces are data integration approaches that target for data coexistence in the spatial domain. Unlike traditional data integration techniques, they do not require up front semantic integration of data. In this paper, we outline and compare the properties and implementations of dataspaces including the approaches of optimizing dataspace development. We finally present actual dataspace development recommendations to provide a global overview of this significant research topic.This paper presents a survey of the state of dataspaces . With dataspaces becoming the modern technique of systems integration, the ach ievement of complete dataspace development is a critical issue. This has led to the design and implementation of dataspace systems using various approaches. Dataspaces are data integration approaches that target for data coexistence in the spatial domain. Unlike traditional data integration techniques, they do not require up front semantic integration of data. In this paper, we outline and compare the properties and implementations of dataspaces including the approaches of optimizing dataspace development. We finally present actual dataspace development recommendations to provide a global overview of this significant research topic
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