Physics-based simulation provides a powerful framework for understanding biological form and function. Simulations help biomedical researchers understand the physical constraints on biological systems as they engineer novel drugs, new diagnostics, synthetic tissues, medical devices, and surgical interventions. Unfortunately, after individual investigators publish their work, the software, underlying models and simulation results are often inaccessible, limiting progress. In 2005, we launched Simtk.org, a website to develop and share biosimulation tools, models, and data, to address this issue. Simtk.org now supports over 23,000 researchers globally and over 600 projects. Members use Simtk.org to develop and build communities around their simulation tools, fulfill the data sharing responsibilities for their grants, and create new types of collaborations. Thus, Simtk.org is a model for how national infrastructure can be created for scientific subdisciplines. Our users have helped us identify key opportunities to further increase our impact: facilitating the faithful reproduction of simulation results across investigators, capturing the full nuances of a simulation study, and creating incentives for researchers to provide access to their data, models and software. Thus, we propose a plan to extend Simtk.org and build new ways for scientific data sharing. First, we will create prototype tools that enable others to easily reproduce and extend biosimulation results. Virtual machines and cloud computing services allow researchers to capture and share a snapshot of their complete computing environment, enabling unprecedented fidelity in sharing. We will explore how these could be used within Simtk.org to reproduce biosimulation studies. Second, we will dramatically increase the integration of simulation-based scientific publications with their supporting data. Working with the editors of major journals for biosimulation publications, we will extend Simtk.org to directly link published articles to the resources needed to understand, examine and replicate their results. Third, we will improve the robustness and usability of Simtk.org, so that the growing community who rely on the site can continue their work with full confidence in the availability and stability of the resource. Fourth, we will develop techniques using social networking to motivate and reward researchers who actively participate in the Simtk.org community. Simtk.org is a middle- sized social network with the key advantage of a specific focus and purpose. As such, it serves as a model for how to build a scientific resource for sharing and community building. The proposed enhancements to Simtk.org will significantly accelerate research in biosimulation and offer a new model for interactions between scientific researchers.
Simtk.org is a vibrant hub for the development and sharing of simulation software, models, and data of biological structures and processes. These technologies are being used to design medical devices and drugs, to generate new diagnostics, to create surgical interventions, and to provide greater insights into biology. The proposed enhancements to Simtk.org would dramatically accelerate progress in the field by providing novel insights into and mechanisms for researchers to collaborate with one another and build upon each other's research.
Mulugeta, Lealem; Drach, Andrew; Erdemir, Ahmet et al. (2018) Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience. Front Neuroinform 12:18 |
Erdemir, Ahmet; Hunter, Peter J; Holzapfel, Gerhard A et al. (2018) Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research. J Biomech Eng 140: |
Wulczyn, Ellery; West, Robert; Zia, Leila et al. (2016) Growing Wikipedia Across Languages via Recommendation. Proc Int World Wide Web Conf 2016:975-985 |
Paranjape, Ashwin; West, Robert; Zia, Leila et al. (2016) Improving Website Hyperlink Structure Using Server Logs. Proc Int Conf Web Search Data Min 2016:615-624 |
West, Robert; Paranjape, Ashwin; Leskovec, Jure (2015) Mining Missing Hyperlinks from Human Navigation Traces: A Case Study of Wikipedia. Proc Int World Wide Web Conf 2015:1242-1252 |