TY  - BOOK
AB  - Reproducibility of scientific research data has been error-prone for  contextually sensitive studies like Psychology with pharmaceutical clinical trials having lower success rates. However, “analytical reproducibility” of a statistical analysis is mathematically achievable when the research data artifacts are public.

The DFG-funded Conquaire project at Bielefeld University is developing a generic architecture based on GitLab to support computational reproducibility of research data. 

One aspect of the project is to examine and develop solutions to track released versions of research data and corresponding source code in institutional repositories for proper persistent identification, dissemination and visibility of computational research artefacts.

In this respect, the presentation will focus on usage scenarios with Conquaire pilot partners which inform the functional requirements on deposition, ingestion and publication workflows of the institutional repository platform LibreCat.
DA  - 2017
KW  - analytical reproducibility
KW  - research data quality control
KW  - continuous integration
KW  - research data repository
LA  - eng
PY  - 2017
TI  - Enabling Git based research data quality control for institutional repositories
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-29161886
Y2  - 2024-11-21T22:54:27
ER  -