Enabling linked data publication with the Datalift platform

Scharffe, François; Atemezing, Ghislain; Troncy, Raphaël; Gandon, Fabien; Villata, Serena; Bucher, Bénédicte; Hamdi, Fayçl; Bihanic, Laurent; Képéklian, Gabriel; Cotton, Franck; Euzenat, Jérôme; Fan, Zhengjie; Vandenbussche, Pierre-Yves; Vatant, Bernard
AAAI 2012, 26th Conference on Artificial Intelligence, W10:Semantic Cities, July 22-26, 2012, Toronto, Canada

As many cities around the world provide access to raw public data along the Open Data movement, many questions arise concerning the accessibility of these data. Various data formats, duplicate identifiers, heterogeneous metadata schema descriptions, and diverse means to access or query the data exist. These factors make it difficult for consumers to reuse and integrate data sources to develop innovative applications. The Semantic Web provides a global solution to these problems by providing languages and protocols for describing and accessing datasets. This paper presents Datalift, a framework and a platform helping to lift raw data sources to semantic interlinked data sources.


HAL
Type:
Conference
City:
Toronto
Date:
2012-07-22
Department:
Data Science
Eurecom Ref:
3707
Copyright:
© AAAI. Personal use of this material is permitted. The definitive version of this paper was published in AAAI 2012, 26th Conference on Artificial Intelligence, W10:Semantic Cities, July 22-26, 2012, Toronto, Canada and is available at :

PERMALINK : https://www.eurecom.fr/publication/3707