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Declarative Generation of RDF-star Datasets from Heterogeneous Data

Tracking #: 3602-4816

Authors: 
Julián Arenas-Guerrero
Ana Iglesias-Molina
David Chaves-Fraga
Daniel Garijo
Oscar Corcho
Anastasia Dimou

Responsible editor: 
Guest Editors Tools Systems 2022

Submission type: 
Tool/System Report
Abstract: 
RDF-star has been proposed as an extension of RDF to make statements about statements. Libraries and graph stores have started adopting RDF-star, but the generation of RDF-star data remains largely unexplored. To allow generating RDF-star from heterogeneous data, RML-star was proposed as an extension of RML. However, no system has been developed so far that implements the RML-star specification. In this work, we present Morph-KGCstar , which extends the Morph-KGC materialization engine to generate RDF-star datasets. We validate Morph-KGCstar by running test cases derived from the N-Triples-star syntax tests and we apply it to two real-world use cases from the biomedical and open science domains. We compare the performance of our approach against other RDF-star generation methods (SPARQL-Anything), showing that Morph-KGCstar scales better for large input datasets, but it is slower when processing multiple smaller files.
Full PDF Version: 
Tags: 
Reviewed

Decision/Status: 
Accept

Solicited Reviews:

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Review #1
By Sebastián Ferrada submitted on 02/Jan/2024
Suggestion:
Accept
Review Comment:

I thank the authors for addressing Pierre-Antoine's comment in this revised version. I do not have further comments of my own, and I recommend this paper to be accepted, per the reasons given in my previous two reviews.

Review #2
By Pierre-Antoine Champin submitted on 29/Jan/2024
Suggestion:
Accept
Review Comment:

This paper presents RML-star, an extension of RML (RDF Mapping Language) to support the new features introduced by RDF-star in RDF. The paper also presents Morph-KGC^star, an implementation of RML-star, and compares it with other implementations of mapping languages supporting RDF-star.

The paper is clear and pleasant to read, and the proposed approach is convincing. An open-source implementation is available on github, with a healthy continuous-integration process in place, and Zenodo DOI for each releases.

I have a few minor changes to suggest, which are not blocking to accept the paper.

* p1 "the RDF-Star Working Group has recently been created"
→ not so recently anymore

* p5 "<#jumpTM> (...) produce triples annotated with :date."
→ this is a bit confusing, as the annotation with :date is not produced by <#jumpTM>. I suggest to reword as:
... produce triples that are annotated with :date by the triples map <#dateTM>

* p8 and p9 "have no effect" / "has no effect"
→ what I guess you mean is that the returned m_joint is the same as m_parent. This should be more explicit. "have no effect" seems to imply that nothing is assigned in m_joint, which makes no sense.