Proposals For Second LINCC Frameworks Incubator Due June 15, 2023
LSSTC is excited to announce the call for proposals for the second round of the LINCC Frameworks Incubator program. 
The LINCC Frameworks team is working on robust open-source software tools to support analysis of LSST data at scale, and a key part of this effort is the formation of collaborations with the LSST science community. The Incubator program, which starts in the third quarter of 2023 with a deadline for short, stage-one proposals of 2023 June 15, will provide dedicated funding and collaborations with software engineers to proposal teams who pitch compelling projects to be carried out in collaboration with the LINCC Frameworks team. Incubator projects should be aimed at solving computational challenges to develop open-source software that will enable a near-term science project using simulations and precursor data, and that serves as a starting point towards eventual LSST data analysis. More information available here.
New Scialog in 2024: Early Science with the LSST
Research Corporation for Science Advancement and the Heising-Simons Foundation are co-sponsoring a new initiative, Scialog: Early Science with the LSST. With the goal of advancing foundational science needed to realize the full potential of the Vera C. Rubin Observatory’s upcoming Legacy Survey of Space and Time (LSST), the initiative will hold the first of its three annual meetings in May 2024 in Tucson, Arizona. These meetings are for Early Career Researchers to network across interdisciplinary boundaries, generate innovative ideas, and apply for catalyzing funding to pursue them. LSSTC plays an advisory role in this Scialog.
The LINCC Frameworks Team’s Python Project Template
The LINCC Frameworks Team’s Python Project Template provides a convenient mechanism for the astronomy community to set up new GitHub projects (repositories) or introduce functionality that enables more robust, collaborative development into existing projects. The goal is to reduce the manual effort needed in configuring projects to support development best practices. By answering a few text questions, the user can automatically generate a range of useful configurations for their project, including robust testing, formatting checks, and automatic documentation generation. The template is designed to be customizable and easily updatable as tooling changes. For more information see the Python Project Template tech talk or the github repository.
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