The Center for Scientific Collaboration and Community Engagement (CSCCE) has quickly become the preeminent research and training center focused on promoting the essential role community managers play in the effective functioning of scientific communities and thus in the production and dissemination of scientific knowledge. Led by microbiologist Lou Woodley, CSCCE documents and disseminates best practices in scientific community management, designs online and in-person curricula, runs training seminars, and acts as an advocate among scientists for the professionalization and institutionalization of the community management role. Funds from this grant support the continued operation and expansion of the CSCCE, along with efforts to develop and implement a business sustainability plan that will allow the organization to continue providing services to the diverse community of an estimated 30,000 community managers inside STEM research organizations. Grant funds are being administered by Community Initiatives, Inc., acting as a fiscal sponsor for CSCCE.

Research by Vicky Rampin, Librarian for Research Data Management and Reproducibility at NYU's Division of Libraries, revealed that while there is widespread use of version control among academic researchers writing source code, there are limited approaches to its preservation. In response, Rampin, together with Martin Klein at Los Alamos National Laboratory, has developed an ambitious plan for CoSAI, Collaborative Software Archiving for Institutions, a project that will create a decentralized and federated platform that will knit together several existing archiving and software preservation tools. Decentralization means that no one institution can be a bottleneck or failure point for archiving workflows—a thorny problem on other platforms—while federation both shares costs among partners and implements one of the gold standards in archiving: ensuring the robustness of preservation through having multiple copies of files mirrored across independent sites. CoSAI will focus on research software and aims to archive not just the code developed on sites like GitHub, but the (currently) ephemeral record of supplementary material related to the code (e.g., discussion threads, issues, etc.). By leveraging existing open source tools like Memento Tracer and building on workflow engines such as OCCAM, CoSAI will be able to capture web resources from code repositories at high quality and in a reproducible manner.

This grant funds the continued development of the AI Model Share platform, a website and integrated open-source Python library where researchers can deploy and share versions of machine learning models they have created in their research, and which can then be subsequently downloaded, implemented, used, analyzed, and improved by other researchers. In addition to making new resources available to researchers of all kinds, AI Model Share’s careful attention to issues like requirements tracking, versions, and documentation is an important step towards creating standards, tools, and practices that will allow research using machine learning methods to be robustly replicated. Activities supported by grant funds include the beta launch of the platform, user training and feedback workshops, an expansion of the platform’s ability to submit, search for, and replicate stored AI models, and the development of a front end “portfolio page” interface for platform users.