@inproceedings{01J1YD9J9RBMKM1YC7VSSPASHM,
  abstract     = {{Although the W3C Community Group on Knowledge Graph Construction (KGC)’s work on the modular
RDF Mapping Language (RML) specification has taken great strides, open issues and respective solution
proposals remain. Some of these issues are (i) inability to handle hierarchy in nested data, (ii) limited
join functionality, and (iii) inability to handle mixed data formats. To combat these issues, the RML
Logical Views module is proposed. However, proper but efficient validation of this module requires
an implementation that allows short development cycles. In this workshop paper, we propose a proofof-concept RML Logical Views implementation, independent of and complementary to existing RML
mapping engines. Our proof-of-concept covers three important features of the new RML Logical
Views module: (i) flattening of nested data, (ii) extended joining of data sources, and (iii) handling
mixed data formats. Our implementation supports one nested source format (JSON) and one tabular
source format (CSV), and can be used independently, as preprocessor, by any RML Engine. With this
implementation, we successfully executed the available relevant test cases of the RML Logical Views
module. Additionally, we measured the knowledge graph construction times on GTFS-Madrid-Bench.
To accomplish this we added an option to our implementation that replaces referencing object maps
with joins in RML Logical Views. When we included our implementation in the knowledge graph
construction pipeline, we noticed considerable execution time reductions. We conclude that the RML
Logical Views specification can be implemented, and can solve needs that were not yet solvable by RML.
The current implementation can already be realized as a modular part of a knowledge graph construction
process. Although boosting performance was not the aim of our work, our implementation reduces the
execution time of GTFS-Madrid-Bench scale 100 by 16%, 33%, and 39% when combined respectively with
SMD-Rdfizer or RPT/Sansa, Morph-KGC, and Carml. RMLStreamer, when used alone, times out after
two hours on this task, but, in conjunction with our implementation, completes it in 236 seconds. We
hope this proof-of-concept inspires the developers of existing RML engines to integrate the RML Logical
Views module and benefit from its features.}},
  author       = {{de Vleeschauwer, Els and Maria, P. and De Meester, Ben and Colpaert, Pieter}},
  booktitle    = {{KGCW 2024 : Knowledge Graph Construction 2024 : Proceedings of the 5th International Workshop on Knowledge Graph Construction co-located with 21th Extended Semantic Web Conference (ESWC 2024)}},
  issn         = {{1613-0073}},
  language     = {{eng}},
  location     = {{Hersonissos, Greece}},
  pages        = {{14}},
  title        = {{RML-view-to-CSV : a proof-of-concept Implementation for RML Logical Views}},
  url          = {{https://ceur-ws.org/Vol-3718/}},
  volume       = {{3718}},
  year         = {{2024}},
}