Semantically-Enhanced Model-Experiment-Evaluation Processes (SeMEEPs) within the Atmospheric Chemistry Community

Authors:
Chris Martin;Mohammed H. Haji;Peter Dew;Mike Pilling;Peter Jimack
Affiliations:
School of Chemistry, University of Leeds, Leeds, UK LS2 9JT;School of Computing, University of Leeds, Leeds, UK LS2 9JT;School of Computing, University of Leeds, Leeds, UK LS2 9JT;School of Chemistry, University of Leeds, Leeds, UK LS2 9JT;School of Computing, University of Leeds, Leeds, UK LS2 9JT
Venue:
Provenance and Annotation of Data and Processes
Year:
2008

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Abstract

The scientific model development process is often documented in an ad-hoc unstructured manner leading to difficulty in attributing provenance to data products. This can cause issues when the data owner or other interested stakeholder seeks to interpret the data at a later date. In this paper we discuss the design, development and evaluation of a Semantically-enhanced Electronic Lab-Notebook to facilitate the capture of provenance for the model development process, within the atmospheric chemistry community. We then proceed to consider the value of semantically enhanced provenance within the wider community processes, Semantically-enhanced Model-Experiment Evaluation Processes (SeMEEPs), that leverage data generated by experiments and computational models to conduct evaluations.