ProvenanceCurious

Mohammad Rezwanul Huq, Peter M. G. Apers, Andreas Wombacher

2013 · 24 citations · 5 references

DOIFull text

Open access

Concepts

Abstract

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 successfully handling other scripts in different contexts.

References

5