695 research outputs found
OWL and Rules
The relationship between the Web Ontology Language OWL and rule-based formalisms has been the subject of many discussions and research investigations, some of them controversial. From the many attempts to reconcile the two paradigms, we present some of the newest developments. More precisely, we show which kind of rules can be modeled in the current version of OWL, and we show how OWL can be extended to incorporate rules. We finally give references to a large body of work on rules and OWL
From fuzzy to annotated semantic web languages
The aim of this chapter is to present a detailed, selfcontained 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
A survey of large-scale reasoning on the Web of data
As more and more data is being generated by sensor networks, social media and organizations, the Webinterlinking this wealth of information becomes more complex. This is particularly true for the so-calledWeb of Data, in which data is semantically enriched and interlinked using ontologies. In this large anduncoordinated environment, reasoning can be used to check the consistency of the data and of asso-ciated ontologies, or to infer logical consequences which, in turn, can be used to obtain new insightsfrom the data. However, reasoning approaches need to be scalable in order to enable reasoning over theentire Web of Data. To address this problem, several high-performance reasoning systems, whichmainly implement distributed or parallel algorithms, have been proposed in the last few years. Thesesystems differ significantly; for instance in terms of reasoning expressivity, computational propertiessuch as completeness, or reasoning objectives. In order to provide afirst complete overview of thefield,this paper reports a systematic review of such scalable reasoning approaches over various ontologicallanguages, reporting details about the methods and over the conducted experiments. We highlight theshortcomings of these approaches and discuss some of the open problems related to performing scalablereasoning
Defeasible RDFS via Rational Closure
In the field of non-monotonic logics, the notion of Rational Closure (RC) is
acknowledged as a prominent approach. In recent years, RC has gained even more
popularity in the context of Description Logics (DLs), the logic underpinning
the semantic web standard ontology language OWL 2, whose main ingredients are
classes and roles. In this work, we show how to integrate RC within the triple
language RDFS, which together with OWL2 are the two major standard semantic web
ontology languages. To do so, we start from , which is the logic
behind RDFS, and then extend it to , allowing to state that two
entities are incompatible. Eventually, we propose defeasible via
a typical RC construction. The main features of our approach are: (i) unlike
most other approaches that add an extra non-monotone rule layer on top of
monotone RDFS, defeasible remains syntactically a triple
language and is a simple extension of by introducing some new
predicate symbols with specific semantics. In particular, any RDFS
reasoner/store may handle them as ordinary terms if it does not want to take
account for the extra semantics of the new predicate symbols; (ii) the
defeasible entailment decision procedure is build on top of the
entailment decision procedure, which in turn is an extension of
the one for via some additional inference rules favouring an
potential implementation; and (iii) defeasible entailment can be
decided in polynomial time.Comment: 47 pages. Preprint versio
Linked Data Entity Summarization
On the Web, the amount of structured and Linked Data about entities is constantly growing. Descriptions of single entities often include thousands of statements and it becomes difficult to comprehend the data, unless a selection of the most relevant facts is provided. This doctoral thesis addresses the problem of Linked Data entity summarization. The contributions involve two entity summarization approaches, a common API for entity summarization, and an approach for entity data fusion
Ontology Evaluation
Ontology evaluation is the task of measuring the quality of an ontology. It enables us to answer the following main question: How to assess the quality of an ontology for the Web? In this thesis a theoretical framework and several methods breathing life into the framework are presented. The application to the above scenarios is explored, and the theoretical foundations are thoroughly grounded in the practical usage of the emerging Semantic Web
Proceedings of the Workshop on Models and Model-driven Methods for Enterprise Computing (3M4EC 2008)
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