Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/80965
Title: | Tracing where and who provenance in Linked Data: A calculus | Authors: | Dezani-Ciancaglini, Mariangiola Horne, Ross Sassone, Vladimiro |
Keywords: | Operational semantics Type systems Linked Data |
Issue Date: | 2012 | Source: | Dezani-Ciancaglini, M., Horne, R., & Sassone, V. (2012). Tracing where and who provenance in Linked Data: A calculus. Theoretical Computer Science, 464, 113-129. | Series/Report no.: | Theoretical Computer Science | Abstract: | Linked Data provides some sensible guidelines for publishing and consuming data on the Web. Data published on the Web has no inherent truth, yet its quality can often be assessed based on its provenance. This work introduces a new approach to provenance for Linked Data. The simplest notion of provenance–viz., a named graph indicating where the data is now–is extended with a richer provenance format. The format reflects the behaviour of processes interacting with Linked Data, tracing where the data has been published and who published it. An executable model is presented based on abstract syntax and operational semantics, providing a proof of concept and the means to statically evaluate provenance driven access control using a type system. | URI: | https://hdl.handle.net/10356/80965 http://hdl.handle.net/10220/39002 |
ISSN: | 0304-3975 | DOI: | 10.1016/j.tcs.2012.06.020 | Rights: | © 2012 Elsevier B.V. This is the author created version of a work that has been peer reviewed and accepted for publication by Theoretical Computer Science, Elsevier B.V. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.tcs.2012.06.020]. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
SCOPUSTM
Citations
20
17
Updated on Jan 20, 2023
Web of ScienceTM
Citations
20
14
Updated on Jan 24, 2023
Page view(s)
309
Updated on Feb 4, 2023
Download(s) 50
112
Updated on Feb 4, 2023
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.