Tracing the History of the Baltic Sea Oxygen Level
| dc.contributor.author | Auge, Tanja | |
| dc.contributor.author | Heuer, Andreas | |
| dc.contributor.editor | Kai-Uwe Sattler | |
| dc.contributor.editor | Melanie Herschel | |
| dc.contributor.editor | Wolfgang Lehner | |
| dc.date.accessioned | 2021-03-16T07:57:10Z | |
| dc.date.available | 2021-03-16T07:57:10Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | In order to guarantee the reproducibility of research results, large research communities, conferences and journals increasingly demand the provision of original research data. Since this is often not possible or desired, a certain tact and sensitivity is needed. With our method, combining provenance and evolution, we can identify the source tuples necessary for the reconstruction of a query result also in temporal databases. To avoid dirty data caused by the inverse evolution, we introduced the what-provenance, which remembers the data types of the source relation. | en |
| dc.identifier.doi | 10.18420/btw2021-18 | |
| dc.identifier.isbn | 978-3-88579-705-0 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/35801 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | BTW 2021 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-311 | |
| dc.subject | Long-term Data | |
| dc.subject | Schema Evolution | |
| dc.subject | Provenance | |
| dc.subject | Research Data Management | |
| dc.subject | CHASE | |
| dc.title | Tracing the History of the Baltic Sea Oxygen Level | en |
| gi.citation.endPage | 348 | |
| gi.citation.startPage | 337 | |
| gi.conference.date | 13.-17. September 2021 | |
| gi.conference.location | Dresden | |
| gi.conference.sessiontitle | Data Integration, Semantic Data Management, Streaming |
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