Well-Stratified Linked Data for Well-Behaved Data Citation

Autor:	De Nart, Dario, Degl'Innocenti, Dante, Peressotti, Marco
Rok vydání:	2015
Předmět:	Computer Science - Digital Libraries
Druh dokumentu:	Working Paper
Popis:	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. Comment: in Bulletin of IEEE Technical Committee on Digital Libraries, Volume 12 Issue 1, May 2016
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1512.02898 Zobrazit plný text záznamu View this record from Arxiv