[](https://doi.org/10.5281/zenodo.7110221) **The LUBM4OBDA Benchmark** is an extension of the popular **[LUBM Benchmark](http://swat.cse.lehigh.edu/projects/lubm/)** to evaluate Ontology-Based Data Access (OBDA) engines over relational databases. In addition, LUBM4OBDA considers meta knowledge (also called reification or statement-level metadata) benchmarking. The main characteristics of LUBM4OBDA are: - SQL data dumps for **[MySQL](https://www.mysql.com/)** and **[PostgreSQL](https://www.postgresql.org/)**. - Data generator for custom scaling factors. - Original **[LUBM query set](http://swat.cse.lehigh.edu/projects/lubm/queries-sparql.txt)** (queries 1-14). - Meta knowledge query set for [_standard reification_](https://www.w3.org/TR/rdf-primer/#reification), [_singleton property_](https://dl.acm.org/doi/pdf/10.1145/2566486.2567973) and [_SPARQL-star_](https://w3c.github.io/rdf-star/cg-spec/2021-12-17.html#sparql-star) (queries 15-18). - **[R2RML](https://www.w3.org/TR/r2rml/)** and **[RML](http://w3id.org/rml/portal/)** mappings. **Citing LUBM4OBDA**: please cite the **[JWE paper](https://journals.riverpublishers.com/index.php/JWE/article/view/18845)**: ```bib @article{arenas2024lubm4obda, title = {{LUBM4OBDA: Benchmarking OBDA Systems with Inference and Meta Knowledge}}, author = {Arenas-Guerrero, Julián and Pérez, María S. and Corcho, Oscar}, journal = {Journal of Web Engineering}, publisher = {River Publishers}, issn = {1544-5976}, year = {2024}, volume = {22}, number = {8}, pages = {1163–1186}, doi = {10.13052/jwe1540-9589.2284} } ``` ## Data There are two options to obtain the SQL data dumps: - Download the SQL data dumps for scaling factors 1, 10, 100 and 1000 from **[Zenodo](https://doi.org/10.5281/zenodo.7110221)**. - Use the **[Docker](https://github.com/oeg-upm/lubm4obda/tree/main/generator#build-and-run-the-data-generator-image-locally)** container with the data generator to produce the data with **custom** scaling factors. ## Mappings The **[mappings](https://github.com/oeg-upm/lubm4obda/tree/main/mappings)** directory of this GitHub repository contains all the R2RML and RML documents. The following mappings are provided: - **[R2RML](https://github.com/oeg-upm/lubm4obda/tree/main/mappings/r2rml)**: - [Original](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/r2rml/lubm4obda.r2rml.ttl), without meta knowledge. - [Standard reification](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/r2rml/lubm4obda-reification.r2rml.ttl). - [Singleton property](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/r2rml/lubm4obda-singleton-property.r2rml.ttl). - [R2RML-star](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/r2rml/lubm4obda-star.r2rml.ttl). - **[RML](https://github.com/oeg-upm/lubm4obda/tree/main/mappings/rml)**: - [Original](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/rml/lubm4obda.rml.ttl), without meta knowledge. - [Standard reification](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/rml/lubm4obda-reification.rml.ttl). - [Singleton property](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/rml/lubm4obda-singleton-property.rml.ttl). - [RML-star](https://github.com/oeg-upm/lubm4obda/blob/main/mappings/rml/lubm4obda-star.rml.ttl). ## Ontology The **Univ-Bench ontology** is available in the **[ontology](https://github.com/oeg-upm/lubm4obda/blob/main/ontology/univ-bench.owl)** directory of this GitHub repository. ## Queries The queries are available in the **[queries](https://github.com/oeg-upm/lubm4obda/tree/main/queries)** directory of this GitHub repository. Keep in mind that **original** mappings should be used for **queries 1-14**. There are three different versions of **queries 15-18**, one for each meta knowledge approach (standard reification, singleton property or RDF-star), with each approach having its corresponding mapping. ## CSV & Apache Parquet It is also possible to run the benchmark with **CSV** and **Apache Parquet** files. The resources for these data sources are available in [Zenodo](https://zenodo.org/doi/10.5281/zenodo.7389704) and they have been described in an **[ESWC paper](https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Arenas-Guerrero_2023_Boosting.pdf)**.