On code sharing and model documentation of published individual and agent-based models. (December 2020) - Janssen, Marco A.; Pritchard, Calvin; Lee, Allen
Abstract: Being able to replicate research results is the hallmark of science. Replication of research findings using computational models should, in principle, be possible. In this manuscript, we assess code sharing and model documentation practices of 7500 publications about individual-based and agent-based models. The code availability increased over the years, up to 18% in 2018. Model documentation does not include all the elements that could improve the transparency of the models, such as mathematical equations, flow charts, and pseudocode. We find that articles with equations and flow charts being cited more among other model papers, probably because the model documentation is more transparent. The practices of code sharing improve slowly over time, partly due to the emergence of more public repositories and archives, and code availability requirements by journals and sponsors. However, a significant change in norms and habits need to happen before computational modeling becomes a reproducible science. Highlights: Lack code sharing of computational science limits reuse and reproducibility. A database of 7500 articles of agent-based and individual-based models was created. Only 11% of articles shared code, although there is an upward trend. Better documentation practices increase the citations to model papers by other model papers. Major changes in practices are needed on code sharing within computational modeling research.