Well-Stratified Linked Data for Well-Behaved Data Citation

Dario De Nart, Dante Degl’Innocenti, Marco Peressotti

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

In this paper we analyse the functional requirements of linked data citation and identify a minimal set of operations and primitives needed to realize such task. Citing linked data implies solving a series of data provenance issues and finding a way to identify data subsets. Those two tasks can be handled defining a simple type system inside data and verifying it with a type checker, which is significantly less complex than interpreting reified RDF statements and can be implemented in a non data invasive way. Finally we suggest that data citation should be handled outside of the data, possibly with an ad-hoc language.
Original languageEnglish
Article number2
JournalBulletin of IEEE Technical Committee on Digital Libraries
Volume12
Issue number1
Pages (from-to)16-26
Publication statusPublished - 2016
Externally publishedYes

Keywords

  • Digital Libraries
  • Data citation
  • Data trust
  • RDF
  • Semantic publishing
  • Semantic web
  • Knowledge representation

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  • 1 Article in proceedings

  • Stratifying semantic data for citation and trust: An introduction to RDFDF

    De Nart, D., Degl’Innocenti, D., Peressotti, M. & Tasso, C., 8. Apr 2017, Digital Libraries and Multimedia Archives - 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Revised Selected Papers. Springer, p. 104-111 (Communications in Computer and Information Science, Vol. 701).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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