Conformance Test Cases for the RDF Mapping Language (RML)

@InProceedings{heyvaert2019testcases,
    author = {Heyvaert, Pieter and Chaves-Fraga, David and Freddy, Piyatna and Corcho, Oscar and Mannens, Erik and Verborgh, Ruben and Dimou, Anastasia},
    title = {{ Conformance Test Cases for the RDF Mapping Language (RML) }},
    booktitle = {Knowledge Graphs and Semantic Web (KGSWC 2019)},
    year = {2019},
    abstract = {Knowledge graphs are often generated using rules that apply
	semantic annotations to data sources. Software tools then execute these
	rules and generate or virtualize the corresponding RDF-based knowledge graph. RML is an extension of the W3C-recommended R2RML
	language, extending support from relational databases to other data
	sources, such as data in CSV, XML, and JSON format. As part of the
	R2RML standardization process, a set of test cases was created to assess
	tool conformance the specification. In this work, we generated an initial
	set of reusable test cases to assess RML conformance. These test cases
	are based on R2RML test cases and can be used by any tool, regardless of the programming language. We tested the conformance of two
	RML processors: the RMLMapper and CARML. The results show that
	the RMLMapper passes all CSV, XML, and JSON test cases, and most
	test cases for relational databases. CARML passes most CSV, XML,
	and JSON test cases regarding. Developers can determine the degree of
	conformance of their tools, and users determine based on conformance
	results to determine the most suitable tool for their use cases.
	},
    year = {2019},
    pages = {162--173},
    publisher = "Springer International Publishing",
    doi = {10.1007/978-3-030-21395-4_12},
    url = {https://doi.org/10.1007/978-3-030-21395-4_12},

    pdf = {https://pieterheyvaert.com/publications/heyvaert2019testcases/paper.pdf}
}