OWL and Rules

Krisnadhi, Adila; Maier, Frederick; Hitzler, Pascal

doi:10.1007/978-3-642-23032-5_7

Cited by 38 publications

(39 citation statements)

References 46 publications

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“…One way to do this is to use the DL-safe SWRL rule [59,72,85] R(x, y) ∧ R(y, x) → x = y, which expresses the same as irreflexivity, however its application is restricted to known individuals and is thus weaker than (first-order logic) irreflexivity. Another alternative is to use nominal schemas [72,73], e.g. by means of the axiom 5 {x} ∃R.∃R.…”

Section: Winston's Approach To Part-of Relationships-ontologized Augumentioning

confidence: 99%

Linked open data alignment & querying

Jain

2013

SIGWEB Newsl.

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Linked Open Data Alignment & Querying.The recent emergence of the Linked Data approach for publishing data represents a major step forward in realizing the original vision of a web that can "understand and satisfy the requests of people and machines to use the web content" i.e. the Semantic Web. This new approach has resulted in the Linked Open Data (LOD) Cloud, which includes more than 295 large datasets contributed by experts belonging to diverse communities such as geography, entertainment, and life sciences. However, the current interlinks between datasets in the LOD Cloud as we will illustrate are too shallow to realize much of the benefits promised. If this limitation is left unaddressed, then the LOD Cloud will merely be more data that suffers from the same kinds of problems, which plague the Web of Documents, and hence the vision of the Semantic Web will fall short.This thesis presents a comprehensive solution to address the issue of alignment and relationship identification using a bootstrapping based approach. By alignment we mean the process of determining correspondences between classes and properties of ontologies. We identify subsumption, equivalence and part-of relationship between classes. The work identifies part-of relationship between instances. Between properties we will establish subsumption and equivalence relationship. By bootstrapping we mean the process of being able to utilize the information which is contained within the datasets for improving the data within them. The work showcases use of bootstrapping based methods to identify and create richer relationships between LOD datasets. The BLOOMS project (http://wiki.knoesis.org/index.php/BLOOMS) and the PLATO project, both built as part of this research, have provided evidence to the feasibility and the applicability of the solution.

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Section: Winston's Approach To Part-of Relationships-ontologized Augumentioning

confidence: 99%

Linked open data alignment & querying

Jain

2013

SIGWEB Newsl.

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“…Therefore, these predicates do not need to be considered when we build the graph to know if a description logic rule R is expressible in SROIQ( ∃ ). This technique, called rolification, is presented in [11].…”

Section: Satisifiability Preserving Transformationsmentioning

confidence: 99%

“…An earlier translation of the rule reduces the number of statements that need to be added to the knowledge base. Recall, in particular, that rules with tree shaped graphs are directly expressible in DL [11,13].…”

Section: ∃E{a} ∃U({a} ∃Y{b})mentioning

confidence: 99%

“…We will refrain from introducing all formal details and refer the reader to [9,10,11,15] for this. While the semantic intuition behind nominal schemas is the same as that behind DL-safe variables, nominal schemas integrate seamlessly with DL syntax.…”

Section: Using Nominal Schemas and Sroiqv( ∃ )mentioning

confidence: 99%

“…Currently, the most prominent approaches for modeling this knowledge are description logics (DLs) [1] and rules based on the logic programming paradigm. Although both are based on classical logic, they differ significantly and the search for a satisfactory integration is still ongoing [4,11].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Extending Description Logic Rules

Martínez

Hitzler

2012

Lecture Notes in Computer Science

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Abstract. Description Logics -the logics underpinning the Web Ontology Language OWL -and rules are currently the most prominent paradigms used for modeling knowledge for the Semantic Web. While both of these approaches are based on classical logic, the paradigms also differ significantly, so that naive combinations result in undesirable properties such as undecidability. Recent work has shown that many rules can in fact be expressed in OWL. In this paper we extend this work to include some types of rules previously excluded. We formally define a set of first order logic rules, C-Rules, which can be expressed within OWL extended with role conjunction. We also show that the use of nominal schemas results in even broader coverage.

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Knowledge Representation on the Semantic Web

Hitzler¹

Social Networks and the Semantic Web

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OWL and Rules

Cited by 38 publications

References 46 publications

Linked open data alignment & querying

Linked open data alignment & querying

Extending Description Logic Rules

Knowledge Representation on the Semantic Web

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