Arenas-Guerrero J., Chaves-Fraga D., Toledo J., Pérez M. S., Corcho O. (2024). Morph-KGC: Scalable knowledge graph materialization with mapping partitions. Semantic Web, 15(1), 1–20.
Asprino L., Daga E., Dowdy J., Gangemi A., Mulholland P. (2024). Materialisation approaches for façade-based data access with SPARQL. Semantic Web: – Interoperability, Usability, Applicability. Accepted
Blin I., Tiddi I., van Trijp R., ten Teije A. (2025). Chronographer: Event-centric knowledge graph construction via informed graph traversal. Semantic Web, 16(5), 22104968251377247. https://doi.org/10.1177/22104968251377247
Calvanese D., Cogrel B., Komla-Ebri S., Kontchakov R., Lanti D., Rezk M., Rodriguez-Muro M., Xiao G. (2017). Ontop: Answering SPARQL queries over relational databases. Semantic Web, 8(3), 471–487. https://doi.org/10.3233/SW-160217
Castedo C., Iglesias E., Lama M., Bugarín-Diz A., Vidal M. E., Chaves-Fraga D. (2026). BLINKG: A benchmark for LLM-integrated knowledge graph generation. Transactions on Graph Data and Knowledge. Accepted.
Chaves-Fraga D., Corcho O., Dimou A., Vidal M. E., Iglesias-Molina A., Van Assche D. (2024). Are knowledge graphs ready for the real world? Challenges and perspective. Dagstuhl Reports, 14(2), 1–70.
Chaves-Fraga D., Priyatna F., Cimmino A., Toledo J., Ruckhaus E., Corcho O. (2020). GTFS-Madrid-Bench: A benchmark for virtual knowledge graph access in the transport domain. Journal of Web Semantics, 65, 100596.
Daga E., Asprino L., Mulholland P., Gangemi A. (2021). Facade-X: An opinionated approach to SPARQL anything. In M. Alam, P. Groth, V. de Boer, T. Pellegrini, H. J. Pandit, E. Montiel-Ponsoda, V. Rodrı́guez-Doncel, B. McGillivray & A. Meroño-Peñuela (Eds.), Further with knowledge graphs—proceedings of the 17th international conference on semantic systems, SEMANTiCS 2021, Amsterdam, The Netherlands, September 6–9, 2021, studies on the semantic web (Vol. 53, pp. 58–73). IOS Press. https://doi.org/10.3233/SSW210035
Dang M. H., Pham T. H. T., Molli P., Skaf-Molli H., Gaignard A. (2025). LLM4Schema.org: Generating Schema.org markups with large language models. Semantic Web: – Interoperability, Usability, Applicability, 16(6). https://doi.org/10.1177/22104968251382172
Dimou A., Chaves-Fraga D. (2022). Declarative description of knowledge graphs construction automation: Status & challenges. In Proceedings of the 3rd international workshop on knowledge graph construction (KGCW 2022) co-located with 19th extended semantic web conference (ESWC 2022).
Dimou A., Vander Sande M., Colpaert P., Verborgh R., Mannens E., Van de Walle R. (2014). RML: A generic language for integrated RDF mappings of heterogeneous data. In C. Bizer, T. Heath, S. Auer, & T. Berners-Lee (Eds.), Proceedings of the workshop on linked data on the web co-located with the 23rd international world wide web conference (WWW 2014), Seoul, Korea, April 8, 2014, CEUR workshop proceedings (Vol. 1184). CEUR-WS.org. https://ceur-ws.org/Vol-1184/ldow2014_paper_01.pdf.
Elhalawati A., Van den Bussche J., Dimou A. (2025). A declarative formalization of R2RML using datalog and its efficient execution. In Companion proceedings of the 9th international joint conference on rules and reasoning (RuleML + RR 2025) also co-located with 21th reasoning web summer school (RW 2025) and 17th DecisionCAMP 2025 as part of declarative AI 2025, Istanbul, Türkiye, September 22–24, 2025, CEUR workshop proceedings (Vol. 4083). CEUR-WS.org. https://ceur-ws.org/Vol-4083/paper63.pdf.
Freund M., Dorsch R., Schmid S., Harth A. (2025). Mapping by example: Towards an RML mapping reverse engineering pipeline. In Proceedings of the 6th international workshop on knowledge graph construction (KGCW 2025) co-located with 22nd extended semantic web conference (ESWC 2025).
Garcı́a-González H., Boneva I., Staworko S., Gayo J. E. L., Lovelle J. M. C. (2020). ShExML: Improving the usability of heterogeneous data mapping languages for first-time users. PeerJ Computer Science, 6, e318. https://doi.org/10.7717/peerj-cs.318
García-González H. (2025). Optimising the ShExML engine through code profiling: From turtle’s pace to state-of-the-art performance. Semantic Web 16, (2), SW–243736. https://doi.org/10.3233/SW-243736
Geisler S., Cappiello C., Celino I., Chaves-Fraga D., Dimou A., Iglesias-Molina A., Lenzerini M., Rula A., Van Assche D., Welten S., Vidal M. E. (2025). From genesis to maturity: Managing knowledge graph ecosystems through life cycles. Proceedings of the VLDB Endowment, 18(5), 1390–1397.
Hogan A., Blomqvist E., Cochez M., d’Amato C., Melo G. D., Gutierrez C., Kirrane S., Gayo J. E. L., Navigli R., Neumaier S., Ngomo A. C., Polleres A., Rashid S. M., Rula A., Schmelzeisen L., Sequeda J., Staab S., Zimmermann A. (2021). Knowledge graphs. ACM Computing Surveys (Csur), 54(4), 1–37.
Iglesias E., Jozashoori S., Chaves-Fraga D., Collarana D., Vidal M. E. (2020). SDM-RDFizer: An RML interpreter for the efficient creation of RDF knowledge graphs. In Proceedings of the 29th ACM international conference on information & knowledge management (pp. 3039–3046). ACM.
Iglesias-Molina A., Van Assche D., Arenas-Guerrero J., De Meester B., Debruyne C., Jozashoori S., Maria P., Michel F., Chaves-Fraga D., Dimou A. (2023). The RML ontology: A community-driven modular redesign after a decade of experience in mapping heterogeneous data to RDF. In T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, & J. Li (Eds.), The semantic web—ISWC 2023—22nd international semantic web conference, Athens, Greece, November 6–10, 2023, proceedings, part II, lecture notes in computer science (Vol. 14266, pp. 152–175). Springer. https://doi.org/10.1007/978-3-031-47243-5_9
Moskvoretskii V., Neminova E., Lobanova A., Panchenko A., Nikishina I. (2025). Large language models for creation, enrichment and evaluation of taxonomic graphs. Semantic Web: – Interoperability, Usability, Applicability, 17(1). https://doi.org/10.1177/22104968251404186
Oo S. M., De Meester B., Taelman R., Colpaert P. (2025). Algebraic mapping operators for knowledge graph generation. Semantic Web, 16(5), 22104968251361350. https://doi.org/10.1177/22104968251361350
Oo S. M., Hartig O. (2025). An algebraic foundation for knowledge graph construction. In E. Curry, M. Acosta, M. Poveda-Villalón, M. van Erp, A. K. Ojo, K. Hose, C. Shimizu & P. Lisena (Eds.), The semantic web—22nd European semantic web conference, ESWC 2025, Portoroz, Slovenia, June 1–5, 2025, proceedings, part I, lecture notes in computer science (Vol. 15718, pp. 3–22). Springer. https://doi.org/10.1007/978-3-031-94575-5_1
Schmidt W. J., Grangel-González I., Huschle T., Wagner L., Kharlamov E., Paschke A. (2025). LLM-supported mapping generation for semantic manufacturing treasure hunting. In European semantic web conference (pp. 84–101). Springer.
Sequeda J. F., Miranker D. P. (2017). A pay-as-you-go methodology for ontology-based data access. IEEE Internet Computing, 21(2), 92–96.
Van Assche D., Chaves-Fraga D., Dimou A. (2024). KROWN: A benchmark for RDF graph materialisation. In International semantic web conference (pp. 20–39). Springer.
Van Assche D., Delva T., Haesendonck G., Heyvaert P., De Meester B., Dimou A. (2023). Declarative RDF graph generation from heterogeneous (semi-) structured data: A systematic literature review. Journal of Web Semantics, 75, 100753.
Van Assche D., Rojas J., De Meester B., Colpaert P. (2025). Incremental knowledge graph construction from heterogeneous data sources. Semantic Web: – Interoperability, Usability, Applicability, 17(2). https://doi.org/10.1177/22104968251412270
Zhang B., Meroño-Peñuela A., Simperl E. (2025). Towards explainable automated knowledge engineering with human-in-the-loop. Semantic Web, 16(5), 22104968251382171. https://doi.org/10.1177/22104968251382171
