Efficient Federated Debugging of Lightweight Ontologies

For data practitioners embracing the world of RDF and Linked Data, the openness and flexibility is a mixed blessing. For them, data validation according to predefined constraints is a much sought-after feature, particularly as this is taken for granted in the XML world. Based on our work in the DCMI RDF Application Profiles Task Group and in cooperation with the W3C Data Shapes Working Group, we published by today 81 types of constraints that are required by various stakeholders for data applications. These constraint types form the basis to investigate the role that reasoning and different semantics play in practical data validation, why reasoning is beneficial for RDF validation, and how to overcome the major shortcomings when validating RDF data by performing reasoning prior to validation. For each constraint type, we examine (1) if reasoning may improve data quality, (2) how efficient in terms of runtime validation is performed with and without reasoning, and (3) if validation results depend on underlying semantics which differs between reasoning and validation. Using these findings, we determine for the most common constraint languages which constraint types they enable to express and give directions for the further development of constraint languages.

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“…The first solution is applied on local knowledge bases whereas the second is more appropriate for federative environments like in [12,13].…”

Section: Related Workmentioning

confidence: 99%