Semantic Web-Based Information Systems: State-of-the-Art ...

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Query ng the Web Recons dered 0 (Seaborne, 2004) do not even allow the construction of arbitrary RDF, but rather outputs only (n-ary) tuples of variable bindings. Answer ranking and top-k answers historically have rarely been provided by the core of Web query languages, but rather have been added as an extension (Amer- Yahia et al., 2004), a W3C initiative on adding full-text search and answer ranking to XPath and XQuery (Boag et al., 2004). In relational databases, on the other hand, top-k answers are a very common language feature. Query.Programs Declarativity and referential transparency have long been acknowledged as important design principles for any query language, as a declaratively specified query is more amenable to optimization while also easing query authoring in many cases. Most of the Web query languages claim to be declarative languages and, oftentimes claim to offer a referentially transparent syntax. In the case of XQuery (Boag et al., 2004), the referential transparency of the language is doubtful due to side effects during element construction. For instance, the XQuery let $x = return $x is $x, where is the XQuery node comparator (i.e., tests whether two nodes are identical, evaluates to true, whereas the query is evaluates to false, although it is obtained from the first query by replacing all occurrences of $x with its value. 1 The reason for this behavior lies in the way elements are constructed in XQuery: In the first query, a single (empty) a is created, which is, of course, identical to itself. However, in the second case, two a elements are constructed, which are not identical, and, therefore, the node identity comparison using is fails. Interestingly, this behavior is related to XQuery’s violation of design principle 2.4.4, that stipulates that querying and construction should be separated in a query language. In contrast to referential transparency, answer-closedness cannot be observed in many Web query languages. With the exception of Xcerpt (Schaffert & Bry, 2004), Web query languages provide, if at all, only a limited form of answer-closedness, where only certain answers also can be used as queries. Related to answer-closedness is the desire to be able to easily recognize the result of a query. This can be achieved by a strict separation of querying and construction, where the construction specifies a kind of form filled with data selected by the query. Such a strict separation is not used in most XML query languages but can be observed in many RDF query languages (e.g., RDF and SPARQL) due to the restricted form of construction considered in these languages (following a similar syntax as SQL, but restricting the SELECT clause to lists of variables, for example). Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
0 Bry, Koch, Furche, Schaffert, Badea, & Berger Section 2.4.3 proposes the use of (possibly recursive) rules for separation of concern, view specification. This has been a popular choice for Web query languages (e.g., XSLT [Clark, 1999], Algae [Prud’hommeaux, 2004]), in particular when combined with reasoning capabilities (e.g., in TRIPLE [Sintek, 2002], XPathLog [May, 2004]). Reasoning.Capabilities Reasoning capabilities, as discussed in Section 2.5, are very convenient means to handle and enrich heterogeneous Web data. Nevertheless, the number of XML query languages featuring built-in reasoning capabilities is rather limited, examples being XPathLog (May, 2004) and Xcerpt (Schaffert & Bry, 2004). In contrast, several RDF query languages provide at least limited forms of reasoning for computing the transitive closure of arbitrary relations (e.g., TRIPLE [Sintek, 2002], Algae [Prud’hommeaux, 2004]. Some RDF query languages also consider ontology-aware querying with RDFS (Brickley et al., 2004) as ontology language. For XML query languages, this has not been considered at length. Conclusion.and.Outlook In this chapter, design principles for (Semantic) Web query languages have been derived from the experience with previous conventional Web query language proposals from academia and industry as well as recent Semantic Web query activities. In contrast to most previous proposals, these design principles are focused on versatile query languages (i.e., query languages) able to query data in any of the heterogeneous representation formats used in both the standard and the Semantic Web. As argued in Section 3, most previous approaches to Web query languages fail to address the design principles discussed in this chapter; most notably, very few consider access to heterogeneous representation formats. Currently, the Web query language Xcerpt (Schaffert & Bry, 2004), which already reflects many of these design principles, is being further refined to a true versatile query language along the principles outlined in this chapter. We believe that versatile query languages will be essential for providing efficient and effective access to data on the Web of the future, effective as the use of data from different representation formats allows to serve better answers (e.g., by enriching, filtering, or ranking data with metadata available in other representation formats). Efficient as previous approaches suffer from the separation of data access by repre- Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
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Semantic Web-Based Information Syst
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Semantic Web-Based Information Syst
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Chapter.VIII Querying.the.Web.Recon
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the semantics in the Semantic Web.
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the conventional Web, and the emerg
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Chapter.I Semant cs for the Semant
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Semant cs for the Semant c Web and
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Semant cs for the Semant c Web •
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Semant cs for the Semant c Web reas
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Semant cs for the Semant c Web simi
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Semant cs for the Semant c Web in t
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Entity Identification/Disambiguatio
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Question Answering Systems Semant c
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Semant cs for the Semant c Web The
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Semant cs for the Semant c Web Dubo
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Semant cs for the Semant c Web Shet
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The Human Semant c Web tion between
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The Human Semant c Web Figure 2. Th
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• Databases with entry-portals
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The Human Semant c Web • Knowledg
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Conceptual.Modeling The Human Seman
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The Human Semant c Web in relations
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The Human Semant c Web along the di
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The Human Semant c Web Figure 7. Th
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The Human Semant c Web Figure 10. T
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Conceptual.Calibration The Human Se
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The Human Semant c Web Figure 12. T
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Figure 16. The present structure of
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The Human Semant c Web entire healt
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The Human Semant c Web If your answ
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The Human Semant c Web In the Knowl
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The Human Semant c Web ing Environm
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The Human Semant c Web Takeuchi, H.
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26 Between February 2001 and Februa
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Chapter.III General Adaptat on Fram
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General Adaptat on Framework Proact
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General Adaptat on Framework semant
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General Adaptation Framework 75 thr
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Pilot.Implementation.of.Semantic.Ad
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General Adaptat on Framework and co
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Figure 15. Template-based transform
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Conclusion General Adaptat on Frame
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General Adaptat on Framework Statis
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General Adaptat on Framework METEOR
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General Adaptat on Framework 8 Java
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Ontology Creat on Methodolog es obt
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Table 1. Ontology development 101 m
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Ontology Creat on Methodolog es A.C
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Table 5. TOVE methodology Ontology
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Ontology Creat on Methodolog es Nor
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Ontology Creat on Methodolog es dir
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Section III Ontology Creat on Metho
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A Tool for Work ng w th Web Ontolog
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OntoELAN implements the following a
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Chapter.XII Web Serv ce Messages Ar
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Web Serv ce Messages amination, or
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Web Serv ce Messages The full shara
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Web Serv ce Messages standards. For
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Web Serv ce Messages Figure 4 depic
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Web Serv ce Messages are stated as
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Figure 6. An example SimilarTo patt
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Figure 12. Target instance 8351-9
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Web Serv ce Messages 0 Brujin, J.,
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About.the.Authors About the Authors
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About the Authors 0 Veli. Bicer. is
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About the Authors 0 in refereed jou
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About the Authors 0 partment (1992)
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About the Authors Anton.Naumenko.is
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About the Authors Centre and head o
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consumer-centric business model 30
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semantic e-business 214 semantic in
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