New R2RML implementation report
We are excited to announce that a new version of the R2RML implementation report is available as of today! This report lists different R2RML processors and whether they pass or fail the R2RML test cases.
In the last few months, the W3C Knowledge Graph Construction Community Group has been working on reviving the original R2RML implementation report. We believe that this is a valuable resource for our community as it allows users to easily determine which processors are best suited for their use cases. Before we have a look at the details, we would like to thank everybody who contributed to this effort, especially Jhon Toledo, Dylan Van Assche, Benjamin Cogrel and Guohui Xiao!
So what can you find in the report? The most important component is the table that lists the different R2RML test cases in the left column and the different processors in the top row. At the time of writing the included processors are Ontop, Morph-RDB, Db2triples, R2RML-F, and the RMLMapper.
How the implementation report is generated is different from the original report. Each processor’s developer executes the R2RML test cases and hosts the corresponding knowledge graph with the results. The report is then dynamically built based on these different knowledge graphs, through the use of Walder. If developers in the future update their processors and the test case results, then the report is automatically updated by using the updated information in the knowledge graph. Adding a new processor is also easy: we only need to add the link to the knowledge graph to our configuration of Walder. Check out the code on Github.
We also provide a script to ease the execution of the test cases if they are not integrated in your development setup. The scripts automatically generate an EARL report with the results for your processor. Currently, there is support for MySQL and PostgreSQL, and more RDBMS will be added in the future. Any feedback is welcome!
Please do not hesitate to contact us with questions or remarks. If you would be interested in further advancing the state of mapping heterogeneous data to RDF, you can join our Community Group. You are certainly welcome!
