Edinburgh Research Explorer

Diachronic Linked Data: Towards Long-term Preservation of Structured Interrelated Information

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Sören Auer
  • Theodore Dalamagas
  • Helen Parkinson
  • François Bancilhon
  • Giorgos Flouris
  • Dimitris Sacharidis
  • Peter Buneman
  • Dimitris Kotzinos
  • Yannis Stavrakas
  • Vassilis Christophides
  • George Papastefanatos
  • Kostas Thiveos

Related Edinburgh Organisations

Original languageEnglish
Title of host publicationProceedings of the First International Workshop on Open Data
Place of PublicationNew York, NY, USA
PublisherACM
Pages31-39
Number of pages9
ISBN (Print)978-1-4503-1404-6
DOIs
Publication statusPublished - 25 May 2012

Publication series

NameWOD '12
PublisherACM

Abstract

The Linked Data Paradigm is a promising technology for publishing, sharing, and connecting data on the Web, which provides new perspectives for data integration and interoperability. However, the proliferation of distributed, interconnected linked data sources on the Web poses significant new challenges for consistently managing the vast number of potentially large datasets and their interdependencies. In this article we focus on the key problem of preserving evolving structured interlinked data. We argue that a number of issues, which hinder applications and users, are related to the temporal aspect that is intrinsic in Linked Data. We present three use cases to motivate our approach, we discuss problems that occur, and propose a direction for a solution.

    Research areas

  • data evolution, data preservation, linked data lifecycle, data provenance

ID: 16426849