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  • 1.
    Hartig, Olaf
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Perez, Jorge
    University of Chile, Chile; Chilean Centre Semant Web Research, Chile.
    LDQL: A query language for the Web of Linked Data2016Inngår i: Journal of Web Semantics, ISSN 1570-8268, E-ISSN 1873-7749, Vol. 41Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The Web of Linked Data is composed of tons of RDF documents interlinked to each other forming a huge repository of distributed semantic data. Effectively querying this distributed data source is an important open problem in the Semantic Web area. In this paper, we propose LDQL, a declarative language to query Linked Data on the Web. One of the novelties of LDQL is that it expresses separately (i) patterns that describe the expected query result, and (ii) Web navigation paths that select the data sources to be used for computing the result. We present a formal syntax and semantics, prove equivalence rules, and study the expressiveness of the language. In particular, we show that LDQL is strictly more expressive than all the query formalisms that have been proposed previously for Linked Data on the Web. We also study some computability issues regarding LDQL. We first prove that when considering the Web of Linked Data as a fully accessible graph, the evaluation problem for LDQL can be solved in polynomial time. Nevertheless, when the limited data access capabilities of Web clients are considered, the scenario changes drastically; there are LDQL queries for which a complete execution is not possible in practice. We formally study this issue and provide a sufficient syntactic condition to avoid this problem; queries satisfying this condition are ensured to have a procedure to be effectively evaluated over the Web of Linked Data. (C) 2016 Elsevier B.V. All rights reserved.

  • 2.
    Ivanova, Valentina
    et al.
    RISE Research Institutes of Sweden.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Lohmann, Steffen
    Fraunhofer IAIS, Germany.
    Pesquita, Catia
    University of Lisbon, Portugal.
    Visualization and interaction for ontologies and linked data - Editorial2019Inngår i: Journal of Web Semantics, ISSN 1570-8268, E-ISSN 1873-7749, Vol. 55, s. 145-149Artikkel i tidsskrift (Annet vitenskapelig)
    Fulltekst tilgjengelig fra 2020-10-20 08:26
  • 3.
    Lambrix, Patrick
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan.
    Tan, He
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan.
    SAMBO – A System for Aligning and Merging Biomedical Ontologies2006Inngår i: Journal of Web Semantics, ISSN 1570-8268, E-ISSN 1873-7749, Vol. 4, nr 3, s. 196-206Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Due to the recent explosion of the amount of on-line accessible biomedical data and tools, finding and retrieving the relevant information is not an easy task. The vision of a Semantic Web for life sciences alleviates these difficulties. A key technology for the Semantic Web is ontologies. In recent years many biomedical ontologies have been developed and many of these ontologies contain overlapping information. To be able to use multiple ontologies they have to be aligned or merged. In this paper we propose a framework for aligning and merging ontologies. Further, we developed a system for aligning and merging biomedical ontologies (SAMBO) based on this framework. The framework is also a first step towards a general framework that can be used for comparative evaluations of alignment strategies and their combinations. In this paper we evaluated different strategies and their combinations in terms of quality and processing time and compared SAMBO with two other systems.

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