# Better support for collaborations preparing for large-scale projects:   the case study of the LSST Science Collaborations Astro2020 APC White Paper

**Authors:** Federica B. Bianco (University of Delaware, LSST SCs Coordinator, LSST, Transients & Variable Stars SC co-chair), Manda Banerji (University of, Cambridge, LSST Galaxies SC co-chair), John Bochanski (Rider University,, LSST Stars, Milky Way, and Local Volume SC co-chair), William N. Brandt, (Penn State University, LSST AGN SC chair), Patricia Burchat (Stanford, University, LSST Dark Energy SC Deputy Spokesperson), John Gizis, (University of Delaware, LSST Stars, Milky Way, and Local Volume SC co-chair), and Zeljko Ivezi\'c (LSST Project Scientist), Charles Keaton (Rutgers, University, outgoing LSST Strong Lensing SC co-chair), Sugata Kaviraj, (University of Hertfordshire, LSST Galaxies SC co-chair), Tom Loredo, (Cornell University, LSST Informatics, Statistics co-chair), Rachel, Mandelbaum (Carnegie Mellon University, LSST Dark Energy SC Spokesperson) and, Phil Marshall (SLAC, LSST, Past Dark Energy SC Spokesperson), Peregrine, McGehee (College of the Canyons, LSST Stars, Milky Way, and Local Volume SC, co-chair), Chad Schafer (Carnegie Mellon University, LSST Informatics and, Statistics SC co-chair), Megan E. Schwamb (Gemini Observatory, LSST Solar, System SC co-chair), Jennifer L Sokoloski (LSST Corporation Director for, Science), Michael A. Strauss (Princeton, LSST Science Advisory Committee), and Rachel Street (Las Cumbres Observatory, LSST Transients & Variable Stars, SC co-chair), David Trilling (Northern Arizona University, LSST Solar, System SC co-chair), Aprajita Verma (University of Oxford, UK, LSST Strong, Lensing SC co-chair)

arXiv: 1907.09027 · 2019-07-23

## TL;DR

This paper discusses the need for improved funding and support mechanisms for large-scale scientific collaborations, using LSST Science Collaborations as a case study, to enhance research and infrastructure for peta-scale surveys.

## Contribution

It proposes new funding models and support programs tailored for large, complex collaborations at the intersection of data science and astrophysics.

## Key findings

- Identifies gaps in current funding for large collaborations.
- Recommends establishing dedicated support programs.
- Highlights the importance of infrastructure for big data surveys.

## Abstract

Through the lens of the LSST Science Collaborations' experience, this paper advocates for new and improved ways to fund large, complex collaborations at the interface of data science and astrophysics as they work in preparation for and on peta-scale, complex surveys, of which LSST is a prime example. We advocate for the establishment of programs to support both research and infrastructure development that enables innovative collaborative research on such scales.

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Source: https://tomesphere.com/paper/1907.09027