Datalift: A platform for Integrating big and linked data

Kepeklian, Gabriel; Troncy, Raphaël; Bihanic, Laurent
BIDS 2014, International Conference on Big Data from Space, November 12-14, 2014, Rome, Italy

In the space domain, all scientific and technological developments are accompanied by a growth of the number of data sources. More specifically, the world of observation knows
this very strong acceleration and the demand for information processing follows the same pace. To meet this demand, the problems associated with non-interoperability of data must be efficiently resolved upstream and without loss of information. We advocate the use of linked data technologies to integrate heterogeneous and schema-less data that we aim to publish in the 5 stars scale in order to foster their re-use. By proposing the 5 stars data model, Tim Berners-Lee drew the perfect roadmap for the production of high quality linked data. In this paper, we present a technological framework that allows to go from raw, scattered and heterogeneous data to structured data with a well-defined and agreed upon semantics, interlinked with other dataset for their common objects.

DOI
Type:
Poster / Demo
City:
Rome
Date:
2014-11-12
Department:
Data Science
Eurecom Ref:
4397
Copyright:
Copyright ESA. Personal use of this material is permitted. The definitive version of this paper was published in BIDS 2014, International Conference on Big Data from Space, November 12-14, 2014, Rome, Italy and is available at : http://dx.doi.org/10.2788/1823
See also:

PERMALINK : https://www.eurecom.fr/publication/4397