Date
Attendees
Goals
- Discuss rebooted meeting format
- Discuss plans for EMU / POSSUM busy week in Oct 17
- Discuss continuum dataset processing plans
Discussion items
Time | Item | Who | Minutes |
---|---|---|---|
Introductory remarks | JC |
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Clarify direction of meetings over coming months | All |
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Continuum busy week | All |
CA - Community busy weeks — good for getting beginners' hands dirty at a basic level, but can sideline experienced users with needing to provide constant assistance, so not so good for work-shopping specific, advanced issues. Less of a problem these days most likely, since we already have 'pre-baked' data products that we can feed to people to move forward on more advanced topics. CA - Need to define expectations early and prepare for busy week to have it be successful. GH - discussion of busy week goals seems somewhat undirected. Need a roadmap of what remains to be done to be science-ready end-to-end, and a map of where people can usefully get involved. AH - so far, mainly been somewhat undirected investigations of specific datasets. This has been the model required to pick up on the many existing issues. GH - agree that this is valuable and crucial, but we also need to chart a course, thereby naturally highlighting critical tasks, and de-emphasising less critical tasks. Who’s job is it to set down specific goals and waypoints towards science-ready data processing? AH, GH: This group...? RN - sanity check on the early science model: ACES runs the processing, hands off data products to SSTs, SSTs provide assessment and feedback of data quality, at which point the two parties iterate through this procesdure. Is this correct? AH - In practice, ACES doesn’t have the manpower to do everyone's data crunching for them. Processing drudge-work needs to be somewhat SST-driven, with ACES providing expert feedback. GH - need expert users that come in and improve on pipeline, demonstrating inadequacies, demanding improvements be added in. Need to focus on iterative assessment and improvement of individual datasets, with a clear focus on specific, bite-size goals that directly map onto specific requirements to get science-ready. | |
Datasets for processing | JC, RN, AH |
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