Around this time last year, in May 2020, West Hub affiliate Michael Barton and colleagues published an open letter in Science that urged worldwide scientists to share their COVID-19 models and openly publish their code so that it was Findable, Accessible, Interoperable, and Reusable (FAIR). While it’s difficult to prove that this letter stimulated epidemiologists to make their work more transparent, the year 2020 brought more than 56,000 unique visitors to Barton’s social and ecological model gateway (the Network for Computational Modeling in Social and Ecological Sciences, or CoMSES.Net) and around 40,000 model downloads in spite of the COVID-19 pandemic’s disruptions. The response was so overwhelmingly positive that it even surpassed the author’s expectations.
An example CoMSES Computational Model is “JuSt-Social COVID-19” (Version 1.2.0), which was published by Jennifer Badham, Pete Barbrook-Johnson, Camila Caiado, and Brian Castellani earlier this year in a journal article entitled Justified Stories with Agent-Based Modelling for Local COVID-19 Planning in the Journal of Artificial Societies and Social Simulation.
“After this letter was published, we were a bit surprised by the increased traffic on our gateway, which currently has nearly 900 models – varying from societal and ecological systems to pathogens in epidemiology,” said Barton, a professor in the School of Human Evolution and Social Change and School of Complex Adaptive Systems at Arizona State University. “It’s been a long, slow process building up the model library on CoMSES.Net, since our first discussions with National Science Foundation (NSF) colleagues more than 15 years ago.”
Barton is making reference to an NSF workshop that discussed software improvements for modeling as well as better communication between researchers doing similar work. Though the workshop took place in 2007, Barton said it wasn’t until 2009 that he and several like-minded social scientists started building the modelling gateway, with new NSF support, that eventually led to the creation of CoMSES.Net.
“The first iteration of the CoMSES.Net was fairly simple – we allowed the source code for models of social-ecological systems to be uploaded to the site,” explained Barton. “As time went on, we started working on also requiring explicit instructions on how to use the models and eventually added a section for publications of agent-based and individual-based models.”
With support from the NSF Big Data Hub and Spoke program, CoMSES.Net now maintains a curated database of more than 7500 such publications (all papers since 1990 on research using agent-based or individual-based models listed in ISI Web of Science), with topics ranging from a program that simulates human colon cancer initiation, therapy and prevention to a modelling system that compares the effectiveness of multiple volcanic disaster evacuation plans. This database has allowed CoMSES.Net to track how well scientists make their model code FAIR so that others can build on and learn from it. While this has improved over the years, the code used in over 80 percent of even the most recent modeling publications is still inaccessible, something that needs to change for science to advance and the public to benefit.
Barton said that the next step with CoMSES.Net is to work with the West Hub team on ways to increase the number of models openly available, and better package them so that they are easier to download and use. He also plans for more online tools, training, and hopes to soon expand these efforts through the Open Modeling Foundation (OMF).
“The Open Modeling Foundation initiative is setting up an international cooperation among organizations supporting modeling science to globally democratize access to this critical technology we need to confront the social and environmental challenges that humanity faces in the coming decades,” said Barton. “Computation has become ubiquitous and essential across science – modeling in particular is increasingly used to understand the complex interconnections between society and nature, and plan better for the future – CoMSES.Net is pioneering a digital platform connecting thousands of scientists around the world and enabling them to openly share knowledge of computational modeling with each other and society in general.”
CoMSES.Net is funded by NSF Award Number 1636796.
About the West Big Data Innovation Hub:
The West Big Data Innovation Hub is one of four regional hubs funded by the National Science Foundation (NSF) to build and strengthen strategic partnerships across industry, academia, nonprofits, and government. The West Hub community aims to catalyze and scale data science for societal needs – connecting research, education, and practice in thematic areas such as natural resources and hazards, metro data science, health, and data-enabled discovery and learning. Coordinated by UC Berkeley’s Division of Computing, Data Science, and Society, the San Diego Supercomputer Center, and the University of Washington, the West Hub region includes contributors and data enthusiasts from Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming, and a global network of partners.
West Big Data Innovation Hub: westbigdatahub.org
National Science Foundation: www.nsf.gov/
The Big Data Innovation Hubs: bigdatahubs.org