Templates as a method for provenance capture


Project homepage

Data provenance is a way of automatically capturing the trace of a research task and its resulting data, thereby facilitating trust and the principles of reproducible research. While computational domains have started to embrace this technology through provenance-enabled execution middlewares, traditionally non-computational disciplines, such as medical research, that do not rely on a single software platform, are still struggling with its adoption. In order to address these issues, we introduce provenance templates – abstract provenance fragments representing meaningful domain actions. Templates can be used to generate a model-driven service interface for domain software tools to routinely capture the provenance of their data and tasks.


Vasa Curcin (2017) Embedding data provenance into the Learning Health System to facilitate reproducible research, Learning Health Systems 1(2), url, doi:10.1002/lrh2.10019

Vasa Curcin, Elliot Fairweather, Roxana Danger, Derek Corrigan (2017) Templates as a method for implementing data provenance in decision support systems, Journal of Biomedical Informatics 65, p. 1-21, url, doi:10.1016/j.jbi.2016.10.022


Department of Population Health Sciences
King’s College London
5th Floor Addison House
Guy’s Campus