DocumentCode
1909750
Title
Capturing the Age of Linked Open Data: Towards a Dataset-Independent Framework
Author
Rula, Anisa ; Palmonari, Matteo ; Maurino, Andrea
Author_Institution
Univ. of Milano Bicocca, Milan, Italy
fYear
2012
fDate
19-21 Sept. 2012
Firstpage
218
Lastpage
225
Abstract
An increasing amount of data are published and consumed on the Web according to the Linked Data paradigm. In such scenario, understanding if the data consumed are up-to-date is crucial. Outdated data are usually considered inappropriate for many crucial tasks, such as make the consumer confident that answers returned to a query are still valid at the time the query is formulated. In this paper we present a first dataset-independent framework for assessing currency of Linked Open Data (LOD) graphs. Starting from the analysis of the 8,713,282 triples containing temporal metadata in the billion triple challenge 2011, we investigate which vocabularies are used to represent versioning metadata, we defined Onto Currency, an ontology that integrates the most frequent properties used in this domain, and supports the collection of metadata from datasets that use different vocabularies. The proposed framework uses this ontology to assess the currency of an RDF graph/statement, by extrapolating it from the currency of the documents that describe the resources occurring in the graphs (statement). The approach has been implemented and evaluated in two different scenarios.
Keywords
Internet; data handling; graph theory; meta data; ontologies (artificial intelligence); LOD; RDF graph; RDF statement; dataset independent framework; linked data paradigm; linked open data; onto currency; ontology; outdated data; temporal metadata; Data mining; Data models; Information services; Ontologies; Resource description framework; Time measurement; Vocabulary; age; data quality; linked data; ontologies; semantic Web; timeliness;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing (ICSC), 2012 IEEE Sixth International Conference on
Conference_Location
Palermo
Print_ISBN
978-1-4673-4433-3
Type
conf
DOI
10.1109/ICSC.2012.17
Filename
6337107
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