Auge, Tanja (2020) Extended Provenance Management for Data Science Applications. In: PhD@VLDB 2020, 31 Aug 2020, Tokyo.
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Abstract
Research data management deals with tracking and archiving of data collected during scientific projects, experiments or observations. The path from data collection to publication should thus be kept comprehensible, reconstructable and plausible. The continuous growth of data, frequent schema changes as well as the varied evaluation of the data makes the storage of every possible database state a very complicated and lengthy task. With the help of data provenance, however, we can determine which part of the primary research data must be stored long-term in order to ensure the reproducibility of the evaluations. It should also be possible to recalculate changes to data and schemata so that old data records do not have to be archived completely. In addition, the stored data must not conflict with existing privacy guidelines.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Autorenart > DBIS-Publikationen Forschungsthemen > Forschungsdatenmanagement Rahmenprojekte > METIS Rahmenprojekte > PArADISE Forschungsthemen > Provenance Management Forschungsthemen > Schemaevolution |
| Depositing User: | Dbis Admin |
| Date Deposited: | 03 Sep 2020 10:23 |
| Last Modified: | 10 Sep 2020 06:27 |
| URI: | https://eprints.dbis.informatik.uni-rostock.de/id/eprint/1028 |
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