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Reasoning Web International Summer School

Reasoning Web 2016: Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering pp 203–240Cite as

From Fuzzy to Annotated Semantic Web Languages

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9885))

Abstract

The aim of this chapter is to present a detailed, self-contained and comprehensive account of the state of the art in representing and reasoning with fuzzy knowledge in Semantic Web Languages such as triple languages RDF/RDFS, conceptual languages of the OWL 2 family and rule languages. We further show how one may generalise them to so-called annotation domains, that cover also e.g. temporal and provenance extensions.

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Notes

  1. 1.

    More concretely, the intensity of precipitation is expressed in terms of a precipitation rate R: volume flux of precipitation through a horizontal surface, i.e. \(\text {m}^3/ \text {m}^2 \text {s} = \text {ms}^{-1}\). It is usually expressed in mm/h.

  2. 2.

    http://usatoday30.usatoday.com/weather/wds8.htm.

  3. 3.

    The function \(\mathcal {I} _{x}^{a}\) is as \(\mathcal {I} \) except that x is interpreted as a.

  4. 4.

    We use the symbol “,” to denote conjunction in the rule body.

  5. 5.

    The readers familiar with the annotated logic programming framework [35], will notice the similarity of the approaches.

  6. 6.

    Note that one may use XML decimals in [0, 1] in place of real numbers for the fuzzy domain.

  7. 7.

    For a fuzzy DL formula \(\varphi \) we consider a variable \(x_{\varphi }\) with intended meaning: the degree of truth of \(\varphi \) is greater or equal to \(x_{\varphi }\).

  8. 8.

    The list of references is by no means intended to be all-inclusive. The author apologises both to the authors and with the readers for all the relevant works, which are not cited here.

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  1. ISTI - CNR, Area Della Ricerca di Pisa, Pisa, Italy

    Umberto Straccia

  2. Department of Computer Science and Systems Engineering, Universidad de Zaragoza, Zaragoza, Spain

    Fernando Bobillo

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    Jeff Z. Pan

  2. Free University of Bozen-Bolzano , Bolzano, Italy

    Diego Calvanese

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    Michael Kifer

  6. University of Science and Technology , Hong Kong, China

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  7. University of Aberdeen , Aberdeen, United Kingdom

    Yuting Zhao

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Straccia, U., Bobillo, F. (2017). From Fuzzy to Annotated Semantic Web Languages. In: Pan, J., et al. Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering. Reasoning Web 2016. Lecture Notes in Computer Science(), vol 9885. Springer, Cham. https://doi.org/10.1007/978-3-319-49493-7_6

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