KROWN 👑 is a benchmark for materialization systems to construct Knowledge Graphs from (semi-)heterogeneous data sources using declarative mappings such as RML.
Many benchmarks already exist for virtualization systems e.g. GTFS-Madrid-Bench, NPD, BSBM which focus on complex queries with a single declarative mapping. However, materialization systems are unaffected by complex queries since their input is the dataset and the mappings to generate a Knowledge Graph. Some specialized datasets exist to benchmark specific limitations of materialization systems such as duplicated or empty values in datasets e.g. GENOMICS, but they do not cover all aspects of materialization systems. Therefore, it is hard to compare materialization systems among each other in general which is where KROWN 👑 comes in!
Used by
KROWN 👑 has been used in publications and challenges:
- Knowledge Graph Construction Workshop Challenge 2023
- Knowledge Graph Construction Workshop Challenge 2024
- Incremental mapping with IncRML
Source code and code documentation
KROWN 👑's data generator and execution framework code is fully documented to ease their extension and re-usability for developers. You can find the documentation inside the code or you can have a look at their HTML versions:
KROWN 👑's source code is available on the W3C Community Group on Knowledge Graph Construction GitHub under MIT license: https://github.com/kg-construct/KROWN.
Results
KROWN 👑 has been used to benchmark materialization systems, the results are available on Zenodo under DOI 10.5281/zenodo.10973892.