Towards a Scientific Model Management System
Computational models of biological systems aim at accurately simulating in vivo phenomena. They have become a very powerful tool enabling scientists to study complex behavior. A side effect of their success unfortunately exists and is observed as an increasing difficulty in managing data, metadata and a myriad of programs and tools used and produced during a research task. In this work we aim at supporting scientists during a research endeavour by using Scientific Models as a main guiding element for describing, searching and running computational models, as well as managing the corresponding results. We assume a data-oriented perspective for scientific model representation materialized into a data model with which users describe scientific models and corresponding computational models, and a query language with which a scientist specifies simulation queries. The model is grounded in XML and tightly related to domain ontologies, which provide formal domain descriptions and uniform terminology. Scientists may search for scientific models and run simulations that automatically invoke the underlying programs on provided inputs. The results of a simulation may generate complex data that can be queried in the context of the scientific model. Higher-level models can be specified through views that export a unified representation of underlying scientific models.
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- 1.Hunter, J.: Scientific Models – A User-oriented Approach to the Integration of Scientific Data and Digital Libraries. In: VALA 2006, Melbourne (February 2006)Google Scholar
- 4.Oinn, T., Greenwood, M., Addis, M.: Taverna: Lessons in creating a workflow envi-ronment for the life sciences. Concurrence Computation: Pract. Exper., 1–7 (2000)Google Scholar
- 5.Akram, A., Meredith, D., Allan, R.: Evaluation of BPEL for Scientific Workflows. Cluster Computing and the Grid, CCGRID V1(16-19) (2006)Google Scholar
- 7.Altintas, I., Berkley, C., Jaeger, E., Jones, M., Ludascher, B., Kepler, M.: An Extensible System for Design and Execution of Scientific Workflows. In: SSDBM (2004)Google Scholar
- 8.MATLAB (last access, 24/06/2008), http://en.wikipedia.org/wiki/Matlab
- 9.Neuron (last access, 24/06/2008), http://www.neuron.yale.edu
- 10.Roure, D., Goble, C., Stevens, R.: Designing the myExperiment Virtual Research Envi-ronment for the Social Sharing of Workflows. In: e-Science 2007 - Third IEEE Int. Conf. on e-Science and Grid Computing, Bangalore, India, December 10-13, 2007, pp. 603–610 (2007)Google Scholar
- 11.Porto, F., Tajmouati, O., Silva, V., Schulze, B., Ayres, F.: QEF - Supporting Complex Query Applications. In: CCGRID 2007, Rio de Janeiro, Brazil, pp. 846–851 (2007)Google Scholar
- 12.Kandel, E., Schwarts, J., Jessel, T.: Principles of NeuroScience, 4th edn. McGraw-Hill, New York (2000)Google Scholar
- 14.(last accessed, 26/04/2008), http://lsids.sourceforge.net/
- 15.Grosof, B., Horrocks, I., Volz, R., Decker, S.: Description Logic Programs: Combining Logic Programs with Description Logic. In: Proc. WWW 2003, Budapest (May 2003)Google Scholar
- 16.(last accessed, 26/04/2008), http://www.w3.org/TR/xpath
- 17.Elmasri, R., Navathe, S.: Fundamentals of Database Systems, 2nd edn. Benjamin/Cummings (1994)Google Scholar