Describing linked datasets with the VoID vocabulary
By Keith Alexander, Richard Cyganiak, Michael Hausenblas, Jun Zhao. 2011
302 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/52c1674917352958aec5c66a9c604f6df262791d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Christophe Dessimoz
- A. Sima
- A. Diehl
- Manuel Gil
- M. Lizio
- Tarcisio Mendes de Farias
- Maria Anisimova
- Kurt Stockinger
Citations in the corpus
- Binary RDF representation for publication and exchange (HDT) (2013, background): “VoiD [4]) to add provenance and other metadata (such as statistics or a content summary) when publishing RDF datasets, such information – which can be useful to guide consumers – is usually neither complete nor systematically published along with the dataset.”
- GERBIL - Benchmarking Named Entity Recognition and Linking consistently (2017, methodology): “35 http://www.w3.org/TR/json-ld/ G ERBIL uses the recently proposed DataID [3] ontology that combines VoID [1] and DCAT [36] metadata with Prov-O [33] provenance information and ODRL [30] licenses to describe datasets.”
- Enabling semantic queries across federated bioinformatics databases (2019, methodology): “…contributions: (i) a semantic model for gene expression; (ii) an extension and adaptation of the Vocabulary of Interlinked Datasets (VoID) (33); (iii) public SPARQL 1.1 (32) query endpoints for OMA and Bgee; and (iv) a user-friendly search interface based on an extensible catalogue of…”
- Gateways to the FANTOM5 promoter level mammalian expression atlas (2015, methodology): “Second, we composed RDF triples and used the Vocabulary of Inter-linked Datasets (VoID) [76] to create a ‘ naive ’ data model describing the data structure of the FANTOM5 entities.”