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

  • Chris Martin
  • Mohammed H. Haji
  • Peter Dew
  • Mike Pilling
  • Peter Jimack
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5272)

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.

Keywords

Semantic Metadata Provenance Atmospheric Chemistry Model Development 

References

  1. 1.
    Simmhan, Y., Plale, B., Gannon, D.: A Framework for Collecting Provenance in Data-Centric Scientific Workflows. In: Proceedings of the IEEE International Conference on Web Services. IEEE Computer Society, Los Alamitos (2006)Google Scholar
  2. 2.
    Saunders, S.M., Jenkin, M.E., Derwent, R.G., Pilling, M.J.: Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part A): tropospheric degradation of non-aromatic volatile organic compounds. Atmos. Chem. Phys. 3, 161–180 (2003)CrossRefGoogle Scholar
  3. 3.
    Frey, J., Hughes, G., Mills, H.: schraefel, m.c., Smith, G., De Roure, D.: Less is More: Lightweight Ontologies and User Interfaces for Smart Labs. The UK e-Science All Hands Meeting 2004. EPSRC, Nottingham, UK (2004) Google Scholar
  4. 4.
    Sommariva, R., Haggerstone, A.L., Carpenter, L.J., Carslaw, N., Creasey, D.J., Heard, D.E., Lee, J.D., Lewis, A.C., Pilling, M.J., ZÃ!dor, J.: OH and HO2 chemistry in clean marine air during SOAPEX-2. Atmos. Chem. Phys. 4, 839–856 (2004)CrossRefGoogle Scholar
  5. 5.
    Hughes, G., Mills, H., Roure, D.D., Frey, J.G., Moreau, L., Schraefel, m., Smith, G., Zaluska, E.: The Semantic Smart Laboratory: A system for supporting the chemical eScientist. Org. Biomol. Chem. 2, 1–10 (2004)CrossRefGoogle Scholar
  6. 6.
    Carroll, J.J., Dickinson, I., Dollin, C., Reynolds, D., Seaborne, A., Wilkinson, K.: Jena: implementing the semantic web recommendations. In: Proceedings of the 13th international World Wide Web conference on Alternate track papers \& posters. ACM, New York (2004)Google Scholar
  7. 7.
    Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF, vol. 2008 (2005) Google Scholar
  8. 8.
    Rosson, M.B., Carroll, J.M.: Usability Engineering: Scenario-Based Development of Human-Computer Interaction. Morgan Kaufmann, San Francisco (2002)Google Scholar
  9. 9.
    Scriven, M.: Types of Evaluation and Types of Evaluator. American Journal of Evaluation 17, 151–161 (1996)CrossRefGoogle Scholar
  10. 10.
    Taylor, K.R., Essex, J.W., Frey, J.G., Mills, H.R., Hughes, G., Zaluska, E.J.: The Semantic Grid and chemistry: Experiences with CombeChem. Web Semantics: Science, Services and Agents on the World Wide Web 4, 84–101 (2006)CrossRefGoogle Scholar
  11. 11.
    Schraefel, m.c., Hughes, G., Mills, H., Smith, G., Frey, J.: Making tea: iterative design through analogy. In: Proceedings of the 5th conference on Designing interactive systems: processes, practices, methods, and techniques. ACM, Cambridge (2004)Google Scholar
  12. 12.
    Miles, S., Deelman, E., Groth, P., Vahi, K., Mehta, G., Moreau, L.: Connecting Scientific Data to Scientific Experiments with Provenance. In: Proceedings of the Third IEEE International Conference on e-Science and Grid Computing. IEEE Computer Society, Los Alamitos (2007)Google Scholar
  13. 13.
    Deelman, E., Singh, G., Su, M.-H., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Vahi, K., Berriman, G.B., Good, J., Laity, A., Jacob, J.C., Katz, D.S.: Pegasus: A framework for mapping complex scientific workflows onto distributed systems. Scientific Programming 13, 219–237 (2005)CrossRefGoogle Scholar
  14. 14.
    Simmhan, Y., Plale, B., Gannon, D.: A survey of data provenance in e-science. ACM SIGMOD Record 34, 31–36 (2005)CrossRefGoogle Scholar
  15. 15.
    Myers, J., Allison, T., Bittner, S., Didier, B., Frenklach, M., Green, W., Ho, Y.-L., Hewson, J., Koegler, W., Lansing, C., Leahy, D., Lee, M., McCoy, R., Minkoff, M., Nijsure, S., Laszewski, G., Montoya, D., Oluwole, L., Pancerella, C., Pinzon, R., Pitz, W., Rahn, L., Ruscic, B., Schuchardt, K., Stephan, E., Wagner, A., Windus, T., Yang, C.: A Collaborative Informatics Infrastructure for Multi-Scale Science. Cluster Computing 8, 243–253 (2005)CrossRefGoogle Scholar
  16. 16.
    Radenkovic, M., Wietrzyk, B.: Life Science Grid Middleware in a More Dynamic Environment. In: On the Move to Meaningful Internet Systems 2005: OTM Workshops, pp. 264–273 (2005)Google Scholar
  17. 17.
    Missier, P., Turi, D., Goble, C., Oinn, T., De Roure, D.: Taverna Workflows: Syntax and Semantics. In: eScience 2007. IEEE Press, Bangalore (2007)Google Scholar
  18. 18.
    Watson, P., Watson, P.: e-Science in the Cloud with CARMEN e-Science in the Cloud with CARMEN. Parallel and Distributed Computing, Applications and Technologies. In: Eighth International Conference on Parallel and Distributed Computing, Applications and Technologies, 2007. PDCAT 2007, p. 5 (2007) Google Scholar
  19. 19.
    Miles, S., Groth, P., Branco, M., Moreau, L.: The Requirements of Using Provenance in e-Science Experiments. Journal of Grid Computing 5, 1–25 (2007)CrossRefGoogle Scholar
  20. 20.
    Missier, P., Preece, A., Embury, S., Jin, B., Greenwood, M., Stead, D., Brown, A.: Managing Information Quality in e-Science: A Case Study in Proteomics. Perspectives in Conceptual Modeling, 423–432 (2005)Google Scholar
  21. 21.
    De Roure, D., De Roure, D., Goble, C., Stevens, R.: Designing the myExperiment Virtual Research Environment for the Social Sharing of Workflows Designing the myExperiment Virtual Research Environment for the Social Sharing of Workflows. In: Goble, C. (ed.) IEEE International Conference on e-Science and Grid Computing, pp. 603–610 (2007)Google Scholar
  22. 22.
    Gao, Y., Kinoshita, J., Wu, E., Miller, E., Lee, R., Seaborne, A., Cayzer, S., Clark, T.: SWAN: A distributed knowledge infrastructure for Alzheimer disease research. Web Semantics: Science, Services and Agents on the World Wide Web 4, 222–228 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Chris Martin
    • 1
  • Mohammed H. Haji
    • 2
  • Peter Dew
    • 2
  • Mike Pilling
    • 1
  • Peter Jimack
    • 2
  1. 1.School of ChemistryUniversity of LeedsLeedsUK
  2. 2.School of ComputingUniversity of LeedsLeedsUK

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