Model and Data Sharing Working Group
Model and Data Sharing Working Group
Goals and Objectives:
The specific goals of this Working Group are to:
- Develop and promote
- modeling standards
- software for authoring, visualisation and simulation of models
- repositories of models and experimental data to facilitate model reproducibility, model sharing, and model enhancement
- Foster the pairing of models with data. Models accompanied by data that provide evidence of validity will serve as milestones of scientific progress.
- Archive data and models in forms convenient to potential users, and develop archives that will have permanence.
The group will provide an interface to international efforts on model sharing by the SBML consortium, the European VPH community, the IUPS Physiome community, the NeuroML project and the synthetic biology data exchange group.
Recognizing that the interpretation of DATA and the integration of knowledge about real biological systems is the prime purpose of the IMAG working groups and the consortium as a whole, this working group is also dedicated to encouraging the development, use, and maintenance of repositories of experimental data together with the associated models that illuminate the data. In particular, the goal is to facilitate the free exchange of data and models. The philosophical view is that good data are the basic treasures of science; such treasures should be made freely available.
Thursday January 24, 2013 3pm EST
A status update on COMBINE standardization activities, with a focus on SBML.
Michael Hucka, Caltech
A vast number of modeling and simulation software tools are available today for research in computational systems biology. This wealth of resources is a boon to researchers, but it also presents interoperability problems. Different software tools for systems biology are implemented in different programming languages, run on different operating systems, express models using different mathematical frameworks, provide different analysis methods, present different user interfaces, and support different data formats. Despite working with different tools, researchers want to disseminate their work widely, as well as reuse and extend the models of other researchers. They do not want to hardcode their models as software programs, nor assume everyone uses the same computing environment; they need common exchange formats for representing their models in such a way that a variety of software systems can read and write them.
There exist a number of standardization efforts today with the goal of developing and evolving exchange formats for computational systems biology; they differ along dimensions such as domain of specialization and medium of communication. Many of these efforts are engaged in COMBINE (the COmputational Modeling in BIology NEtwork; http://co.mbine.org), an organization whose main goal is to help coordinate community standardization activities. In this presentation, I will summarize the goals of the core standards represented in COMBINE, and provide details about recent developments in certain ones with probable relevance to multiscale modeling, particularly SBML (Systems Biology Markup Language), as well as SED-ML (Simulation Experiment Description Markup Language) and SBGN (the Systems Biology Graphical Notation).
Friday March 8, 2013 2pm EST
- Adobe Connect: https://webmeeting.nih.gov/r52744030/
- Call-in: 800-369-2110, passcode: 60782
Modular Modeling: Standards and Tools. Lucian Smith, Caltech
Model exchange and re-use has been greatly enhanced over the last decade by the emergence of standard model exchange languages such as SBML and CellML. Model design and re-use becomes even more tractable with modularity: larger, more complex models can be built using well-understood smaller models. CellML has long been modular, and SBML now has a modularity 'package' which allows modular model construction. We will present an overview of the capabilities of the modeling standards and tools that facilitate modular modeling. (http://antimony.sf.net).
Model Sharing Myths
1. Models are easily reproducible
This is common myth. One takes a model, enters it into a piece of software and the expectation is that one will get the same answer as published in the literature. Not necessarily true. Different tools implement numerical analysis methods differently, random number generators may have bias or different time steps or scale are used resulting in different simulation outcomes.
2. Extracting working models from the literature is trivial
This is a myth perpetrated by those who have never tried to extract a model from a published paper. Experience from the BioModels database project at EBI shows that at least 9 out of 10 of all models curated by EBI cannot be made to work from the published paper itself. This represents a huge waste of resources since models must be painstakingly recreated. One would assume this is especially true for multiscale models which are generally more complex than subcellular models. However no data is available on the creation of multiscale models from the literature. Developing systematic methods to share models is one way to make the above myths come true. On the one hand standards such as SBML or CellML can be used to unambiguously describe a model but we have currently no way to unambiguously specify how to reproduce the results of simulating a model. It as if an experimentalists had no easy way to reproduce a published experiment.
Tuesday October 24, 2012 IMAG Meeting
Discussion topic: Progress in the last 12 months in the standards community
Thursday January 19, 2012 12-1pm EDT - Working Group Leads will moderate a discussion
- TITLE: Project files: Reproducible Scientific Units.
- ABSTRACT -
In this we would address the essential close relationships amongst hypotheses (models), data, model verification (for mathematical accuracy), validity testing of model against data, parameter estimation and confidence ranges, and open sourcing of models, data, and data analyses for widespread dissemination. The JSim project file, by including data storage, the platform for model design, the technologies for the modeling analysis of data and the displays of results, is an exemplary unit for the exchange of reproducible science.
Wednesday October 19, 2011 4-5pm ET
Discussion topic: Model reproducibility and component/parts repositories
Friday February 25, 2011 3-4pm EDT - Working Group Leads will moderate a discussion
- TITLE: Data Sharing within the MSM Community - Is it Desirable? Feasible?
--MoodyG 16:27, 23 January 2013 (EST)