The increasing data volume and highly complex models used in different domains make it difficult to debug models in cases of anomalies. Data provenance provides scientists sufficient information to investigate their models. In this paper, we propose a tool which can infer fine-grained data provenance based on a given script. The tool is demonstrated using a hydrological model. The tool is also tested success-fully handling other scripts in different contexts.
|Conference||16th International Conference on Extending Database Technology, EDBT 2013|
|Period||18/03/13 → 22/03/13|
|Other||18-22 March 2013|
- Data Provenance