Abstract
The Data Web refers to the vast and rapidly increasing quantity of scientific, corporate, government and crowd-sourced data published in the form of Linked Open Data (LOD), encouraging the uniform representation of heterogeneous data items on the web and the creation of interlinks between them. The growing availability of open linked datasets has brought forth significant new challenges regarding their proper preservation and the management of evolving information within linked datasets. In this paper, we focus on the evolution and preservation challenges related to publishing and maintaining evolving linked data. We present several insights regarding their proper modelling and querying and provide an overview of our current efforts towards a framework for managing the preservation of LOD.
Work supported by the EU project DIACHRON.
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Papastefanatos, G. (2014). Challenges and Opportunities in the Evolving Data Web. In: Parsons, J., Chiu, D. (eds) Advances in Conceptual Modeling. ER 2013. Lecture Notes in Computer Science, vol 8697. Springer, Cham. https://doi.org/10.1007/978-3-319-14139-8_4
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DOI: https://doi.org/10.1007/978-3-319-14139-8_4
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14138-1
Online ISBN: 978-3-319-14139-8
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