Title
DataID: towards semantically rich metadata for complex datasets
Abstract
The constantly growing amount of Linked Open Data (LOD) datasets constitutes the need for rich metadata descriptions, enabling users to discover, understand and process the available data. This metadata is often created, maintained and stored in diverse data repositories featuring disparate data models that are often unable to provide the metadata necessary to automatically process the datasets described. This paper proposes DataID, a best-practice for LOD dataset descriptions which utilize RDF files hosted together with the datasets, under the same domain. We are describing the data model, which is based on the widely used DCAT and VoID vocabularies, as well as supporting tools to create and publish DataIDs and use cases that show the benefits of providing semantically rich metadata for complex datasets. As a proof of concept, we generated a DataID for the DBpedia dataset, which we will present in the paper.
Year
DOI
Venue
2014
10.1145/2660517.2660538
SEMANTICS
Keywords
DocType
Citations 
knowledge representation formalisms and methods,algorithms,design,experimentation,dbpedia,documentation,void,measurement,general,provenance,metadata,dcat,performance
Conference
16
PageRank 
References 
Authors
1.35
6
6
Name
Order
Citations
PageRank
Martin Brümmer123215.95
Ciro Baron2161.35
Ivan Ermilov39811.27
Markus Freudenberg4233.97
Dimitris Kontokostas549031.79
Sebastian Hellmann62007130.09