Semantically-enhanced Model-Experiment-Evaluation Processes (SeMEEPs) within the atmospheric chemistry community

Martin, Chris; Haji, Mohammed H.; Dew, Peter; Pilling, Mike and Jimack, Peter (2008). Semantically-enhanced Model-Experiment-Evaluation Processes (SeMEEPs) within the atmospheric chemistry community. In: Provenance and Annotation of Data and Processes, Lecture Notes in Computer Science, Springer, pp. 293–308.

DOI: https://doi.org/10.1007/978-3-540-89965-5_29

URL: http://link.springer.com/chapter/10.1007/978-3-540...

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.

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About

  • Item ORO ID
  • 40079
  • Item Type
  • Conference or Workshop Item
  • ISBN
  • 3-540-89964-2, 978-3-540-89964-8
  • ISSN
  • 0302-9743
  • Keywords
  • semantic metadata; provenance; atmospheric chemistry; model development
  • Academic Unit or School
  • Faculty of Business and Law (FBL)
  • Copyright Holders
  • © 2008 Springer-Verlag
  • Depositing User
  • Chris Martin
CORE (COnnecting REpositories)

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