StarVers - Versioning and Timestamping RDF data by means of RDF* - An Approach based on Annotated Triples

Tracking #: 3097-4311

This paper is currently under review
Filip Kovacevic
Fajar J. Ekaputra
Tomasz Miksa1
Andreas Rauber

Responsible editor: 
Harald Sack

Submission type: 
Full Paper
Abstract. To foster reproducible and verifiable research results the RDA Data Citation Working Group issued a set of 14 recommendations. The core of these recommendations revolves around preparing data storages so that arbitrary subsets of any evolving data set can be efficiently identified and cited at any specific state or point in time. Based on these recommendations we identified an efficient solution for RDF/triple stores which so far have only used cumbersome mechanisms to aforementioned ends. Our solution employs RDF* and SPARQL* to annotate data triples with temporal metadata and thereby allows for retrieval of datasets as they were at a specific point in time. It furthermore solely relies on triple stores with RDF* and SPARQL* support, such as Jena TDB, GraphDB, Stardog and others and thus does not require any Git-like versioning systems. We evaluate our work by employing the BEAR framework where we use specific components, such as the BEAR-B dataset (hourly DBPedia snapshots), its corresponding queries, Jena TDB as triple store and the quads-based timestamp-based approach. We also extend the java implementation of this framework by methods and functions for handling RDF* queries and GraphDB as additional triple store. Our BEAR extension is publicly available on Github [1] . [1]
Full PDF Version: 
Under Review