Chapman, A., Lauro, L., Missier, P., & Torlone, R. (2024). Supporting Better Insights of Data Science Pipelines with Fine-grained Provenance. ACM Transactions on Database Systems, 49(2), 1-42. https://doi.org/10.1145/3644385
ISO-690 (author-date, English)CHAPMAN, Adriane, LAURO, Luca, MISSIER, Paolo und TORLONE, Riccardo, 2024. Supporting Better Insights of Data Science Pipelines with Fine-grained Provenance. ACM Transactions on Database Systems. 1 Juni 2024. Vol. 49, no. 2, p. 1-42. DOI 10.1145/3644385.
Modern Language Association 9th editionChapman, A., L. Lauro, P. Missier, und R. Torlone. „Supporting Better Insights of Data Science Pipelines With Fine-Grained Provenance.“. ACM Transactions on Database Systems, Bd. 49, Nr. 2, Juni 2024, S. 1-42, https://doi.org/10.1145/3644385.
Mohr Siebeck - Recht (Deutsch - Österreich)Chapman, Adriane/Lauro, Luca/Missier, Paolo/Torlone, Riccardo: Supporting Better Insights of Data Science Pipelines with Fine-grained Provenance., ACM Transactions on Database Systems 2024, 1-42.
Emerald - HarvardChapman, A., Lauro, L., Missier, P. und Torlone, R. (2024), „Supporting Better Insights of Data Science Pipelines with Fine-grained Provenance.“, ACM Transactions on Database Systems, Vol. 49 No. 2, S. 1-42.