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In this thesis, a validation framework is introduced that enables to consistently execute RDF-based constraint languages on RDF data and to formulate constraints of any type. The framework reduces the representation of constraints to the absolute minimum, is based on formal logics, consists of a small lightweight vocabulary, and ensures consistency regarding validation results and enables constraint transformations for each constraint type across RDF-based constraint languages.
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Recently, RDF validation as a research field gained speed due to common needs of data practitioners. A typical example is the library domain that co-developed and adopted Linked Data principles very early. Although, there are multiple constraint languages (having different syntaxes and semantics) which can be used to express RDF constraints such as cardinality restrictions, there is no constraint language which can be seen as the standard. The five most promising ones on being the standard are Description Set Profiles (DSP), Resource Shapes (ReSh), Shape Expressions (ShEx), the SPARQL Inferencing Notation (SPIN), and the Web Ontology Language (OWL 2). SPARQL is generally seen as the method of choice to validate RDF data according to certain constraints. We use SPIN, a SPARQL-based way to formulate and check constraints, as basis to define a validation environment (available at http://purl.org/net/rdfval-demo) to validate RDF data according to constraints expressed by arbitrary constraint languages. Additionally, the RDF Validator can be used to validate RDF data to ensure correct syntax and intended semantics of vocabularies such as Disco, Data Cube, DCAT, and SKOS. We present how to express typical RDF constraints by multiple constraint languages and how to actually validate RDF data conforming to these constraints using the RDF Validator. The workshop participants are encouraged to use the RDF Validator during this session (only an internet browser is needed) in order to express RDF constraints they need for their individual purposes.
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2012.10 - Workshop on Semantic Statistics - 2
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How to Infer
an Ontology of the Data Documentation Initiative? Workshop on Semantic Statistics 15.10.2012 – 19.10.2012 Thomas Bosch M.Sc. (TUM) postgraduate student http://boschthomas.blogspot.com GESIS - Leibniz Institute for the Social Sciences
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