Working Group Lead: Jake Vanderplas
Data-intensive science and data-driven discovery requires an ecosystem of software tools that are openly available, easy to use, and translatable across domains. How can the development, hardening, sustaining, sharing, and integration of techniques into a reusable software infrastructure be recognized and incentivized? There are known obstacles to the development of software tools, including the fact that domain scientists are specifically trained to develop and deliver the advanced software they require and that computer scientists and engineers have little incentive to harden, sustain, share, and integrate novel techniques into a reusable software infrastructure. We are working to remove these obstacles both within the Data Science Environments and in the broader academic community.
Specific goals around this theme include the following:
- Deliver high-impact, usable, and generalizable software for science that does not “reinvent the wheel”
- Promote open source software practices
- Create, strengthen, and deepen connections between tool developers and investigators in data-driven domains
- Promote “matchmaking” between methods/tools and substantive domains