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English Information

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Authors
# Name
1 Fabio Porto (fporto@lncc.br)
2 Patrick Valduriez(Patrick.Valduriez@inria.fr)
3 Gabriela Moraes(gabrielamoraesmat@gmail.com)
4 Bernardo Gonçalves(bgoncalves1@gmail.com)
5 Federico Ulliana(federico.ulliana@inria.fr)
6 Jean-François Baget(jean-francois.baget@lirmm.fr)
7 Pierre Bisquert(pierre.bisquert@inrae.fr)
8 Michel Leclère(michel.leclere@lirmm.fr)

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Reference
# Reference
1 Angles, R., Thakkar, H., and Tomaszuk, D. (2020). Directly mapping rdf databases to property graph databases. IEEE Access, 8:90844–90861.
2 Baget, J.-F., Bisquert, P., Leclère, M., Mugnier, M.-L., Pérution-Kihli, G., Tornil, F., and Ulliana, F. (2023). Integraal: a tool for data-integration and reasoning on heterogeneous and federated sources. In BDA 2023 - 39e Conférence sur la Gestion de Données – Principes, Technologies et Applications, Montpellier, France.
3 Boehm, M., Dusenberry, M. W., Eriksson, D., Evfimievski, A. V., Manshadi, F. M., Pansare, N., Reinwald, B., Reiss, F. R., Sen, P., Surve, A. C., and Tatikonda, S. (2016). Systemml: Declarative machine learning on spark. Proceedings of the VLDB Endowment, 9(13):1425–1436. 12 pages.
4 Chen, A., Chow, A., Davidson, A., DCunha, A., Ghodsi, A., Hong, S. A., Konwinski, A., Mewald, C., Murching, S., Nykodym, T., Ogilvie, P., Parkhe, M., Singh, A., Xie, F., Zaharia, M., Zang, R., Zheng, J., and Zumar, C. (2020). Developments in mlflow: A system to accelerate the machine learning lifecycle. In Proceedings of the Fourth International Workshop on Data Management for End-to-End Machine Learning, DEEM ’20, New York, NY, USA. Association for Computing Machinery.
5 da Silva, D. N. R., Simões, A., Cardoso, C., de Oliveira, D. E. M., Rittmeyer, J. N., Wehmuth, K., Lustosa, H., Pereira, R. S., Souto, Y. M., Vignoli, L. E. G., Salles, R., de S. C. Jr, H., Ziviani, A., Ogasawara, E. S., Delicato, F. C., de Figueiredo Pires, P., da C. Pereira Pinto, H. L., Maia, L., and Porto, F. (2019). A conceptual vision toward the management of machine learning models. In Panach, J. I., Guizzardi, R. S. S., and Claro, D. B., editors, Proceedings of the ER Forum and Poster & Demos Session 2019 on Publishing Papers with CEUR-WS co-located with 38th International Conference on Conceptual Modeling (ER 2019), Salvador, Brazil, November 4, 2019, volume 2469 of CEUR Workshop Proceedings, pages 15–27. CEUR-WS.org.
6 Hogan, A., Blomqvist, E., Cochez, M., d’Amato, C., de Melo, G., Gutiérrez, C., Kirrane, S., Labra Gayo, J. E., Navigli, R., Neumaier, S., Ngonga Ngomo, A.-C., Polleres, A., Rashid, S. M., Rula, A., Schmelzeisen, L., Sequeda, J. F., Staab, S., and Zimmermann, A. (2021). Knowledge Graphs. Number 22 in Synthesis Lectures on Data, Semantics, and Knowledge. Springer.
7 Kim, J., Kwon, Y., Jo, Y., and Choi, E. (2023). Kg-gpt: A general framework for reasoning on knowledge graphs using large language models. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 9410–9421, Singapore. Association for Computational Linguistics.
8 Moraes, G. (2024). Integrando observações e predições em grafos de conhecimento ontologicamente fundamentados. Master’s thesis, Laboratório Nacional de Computação Científica, Petrópolis-RJ, Brazil.
9 Nigenda, D., Karnin, Z., Zafar, M. B., Ramesha, R., Tan, A., Donini, M., and Kenthapadi, K. (2022). Amazon sagemaker model monitor: A system for real-time insights into deployed machine learning models. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD ’22, page 3671–3681, New York, NY, USA. Association for Computing Machinery.
10 Porto, F. and Valduriez, P. (2022). Data and machine learning model management with gypscie. In CARLA 2022 - Workshop on HPC and Data Sciences meet Scientific Computing, pages 1–2, Porto Alegre, Brazil. SCALAC.
11 Schlegel, M. and Sattler, K.-U. (2023). Management of machine learning lifecycle artifacts: A survey. SIGMOD Rec., 51(4):18–35.
12 Toma, T. R. and Bezemer, C.-P. (2024). An exploratory study of dataset and model management in open source machine learning applications. In Proceedings of the ACM Conference. Association for Computing Machinery.
13 Ulliana, F. (2021). Rule-based Languages for Reasoning on Data: Analysis, Design and Applications. PhD thesis, Université de Montpellier, Montpellier, France.
14 Zhang, B., He, Y., Pintscher, L., Peñuela, A. M., and Simperl, E. (2025). Schema generation for large knowledge graphs using large language models. CoRR, abs/2506.04512.
15 Zhao, Z., Liu, W., French, T., and Stewart, M. (2023). Rel2graph: Automated mapping from relational databases to a unified property knowledge graph. CoRR, abs/2310.01080.