The goal of this 2-day workshop is to bring together experts across disciplines and domains to develop an open knowledge base with tools to support and evaluate team learning in the interdisciplinary groups who produce scientific software.
Click here to go to the workshop site.
Location: Institute for Simulation and Training, Univerity of Central Florida, Orlando, FL, USA
Date: November 4-5, 2024
Background: Interdisciplinary group work in scientific software development is increasingly common as institutional initiatives aim to advance science through collaboration and technological innovation. These collaborations are created with the goal of solving problems that are complex in nature and thus benefit from the integration of varied forms of expertise and perspectives to produce software. Team learning has been identified as a key process for the performance and collaboration effectiveness of scientific teams. At the same time, facilitating this form of learning remains a challenge given the breadth of expertise that must be synthesized to effectively build knowledge. The products of the workshop will contribute to collective understanding of collaborative learning in scientific software development, and also will be made open and usable to all in service of better scientific software.
Travel, lodging, and meals for the workshop will be covered by the organizer for approximately 20 invited participants. Limited space for self-funded participants is available.
Workshop topics include, but are not limited to:
Invitees will be asked to submit a short position paper (no more than 2 pages) prior to the workshop. The position paper submission deadline Friday, October 18, 2024 11:59 AoE.
Feel free to contact the organizer: olivia.newton[at]ucf.edu.
Acknowledgement: This workshop is supported by the Better Scientific Software Fellowship Program, a collaborative effort of the U.S. Department of Energy (DOE), Office of Advanced Scientific Research via ANL under Contract DE-AC02-06CH11357 and the National Nuclear Security Administration Advanced Simulation and Computing Program via LLNL under Contract DE-AC52-07NA27344; and by the National Science Foundation (NSF) via SHI under Grant No. 2327079.