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Version Control and Change Validation for RDF Datasets

Part of the Communications in Computer and Information Science book series (CCIS,volume 755)

Abstract

The dynamic and distributed nature of the Semantic Web demands for methodologies and systems fostering collective participation to the evolution of datasets. In collaborative and iterative processes for dataset development, it is important to keep track of individual changes for provenance. Different scenarios may require mechanisms to foster consensus, resolve conflicts between competing changes, reversing or ignoring changes etc. In this paper, we perform a landscape analysis of version control for RDF datasets, emphasizing the importance of change reversion to support validation. Firstly, we discuss different representations of changes in RDF datasets and introduce higher-level perspectives on change. Secondly, we analyze diverse approaches to version control. We conclude by focusing on validation, characterizing it as a separate need from the mere preservation of different versions of a dataset.

Keywords

  • Change management
  • Version control
  • Change validation
  • Collaborative editing
  • RDF
  • Knowledge bases
  • Metadata

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Acknowledgments

This work has been funded by the European Commission ISA2 programme, supporting development of the collaborative RDF editing platform Vocbench 3 [23].

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Correspondence to Manuel Fiorelli .

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Fiorelli, M., Pazienza, M.T., Stellato, A., Turbati, A. (2017). Version Control and Change Validation for RDF Datasets. In: Garoufallou, E., Virkus, S., Siatri, R., Koutsomiha, D. (eds) Metadata and Semantic Research. MTSR 2017. Communications in Computer and Information Science, vol 755. Springer, Cham. https://doi.org/10.1007/978-3-319-70863-8_1

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  • DOI: https://doi.org/10.1007/978-3-319-70863-8_1

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