SSSC Sprint 2 Day 2: unconference sessions on alerts and funding

We had two simulatenous unconference sessions, one on Alerts and one on Funding. We learned that the alerts are relatively well defined with existing examples that are similar to what will be produced (e.g., the Zwicky Transient Facility alert stream).

For funding, we identified some challenges with getting funding for the preparatory work that will enable the first LSST science. Typical PI-led science-focused grants (e.g., NASA ROSES SSO and SSW) are often so small that, especially in the LSST-scale era, they will need to be quite narrowly focused, although they could develop tools along the way that will be generally applicable and sharable. Until LSST data is available, these will need to heavily include other existing datasets. NASA ROSES PDART is a mechanism for getting funding for software tool development (without an explicit science goal) and there is one example that we’re aware of that went in to the 2019 call. NSF AAG is less restrictive on grant content, but potentially a harder sell. Ideally, there would be a specific set of LSST preparation funding either from NSF or possibly private donors through the LSST Corporation, but this is looking less likely and, so far, unclear, especially given the short timeframe from now until start of science. We’ll likely need to distill all the work into proposal-sized chunks. The time frame for this is actually short: applying for grants now, getting rejected once, then getting accepted, then getting the money, then starting the work takes ~2.5 years and there’s only ~3 years until full LSST data (and only ~4 years until an order-of-magnitude increase in the number of known solar system objects)! There was discussion that LSST SSSC Sprint 3 in summer 2020 would have a strong proposal-writing component. (And LSST SSSC Sprint 4 could be a hack week on real data from commissioning!) The SSSC should be a resource to develop collaborations that will result in great science and, ideally, shared tools.

The group generally over the day worked on better understanding metrics, populations, collaboration, etc.


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