2nd try: this time text in the mail msg

From: Chris Smith (csmith@ctio.noao.edu)
Date: Wed Aug 07 2002 - 21:43:02 MST


MOSAIC TDDP PROJECT: IMPACT ANALYSIS

WHO DO WE IMPACT (OUTSIDE DPP) AND HOW?

* By providing automatically reduced Mosaic data to
   WHO:
   - survey program teams
   - general users
   - archive users

   HOW:
   - less burden on PIs/survey teams to produce uniform datasets
   - decreased time to archive availability
     - simply archivability in case of general users
   - more uniform data for archive and documented processing

* By providing near-real-time data quality assessment
   WHO:
   - observers
   - those responsible for reduction
   - archive users

   HOW:
   - providing some DQA in real time can enhance the data by providing
feedback to observers to improve their observing, e.g., telescope problems
(pointing, guiding), optical problems (focus, mirror support), and
problems with instrument (bias jumps, noise), etc.
   - DQA definitions and algorithms provide those involved in reduction
well defined contexts to decide on what data is "good" as well as how to
present it to the community
   - DQA is absolutely necessary in the archive so that those retrieving
the data have some idea about the quality

   DQA should include not only derived quantities but probably observer
comments (automated logging) and ancillary information (weather,
temperature, etc.)

* By providing Transient detection systems
   WHO & HOW:
   - enable general users to do transient science (NEW PROJECTS!)
   - optimization of processes (alignment, PSF match, subtraction,
detections)
     - makes current Survey programs more efficient
     - a TODO item called out by LSST Data Mgmt workgroup
   - generalized alert system
     - enable science based on multiple cuts on transients, including color
outliers

WHAT DO WE LEARN (IMPACT INSIDE DPP)?

* Basic pipeline development - gotta walk before you run
   - exploration of available new technologies (OPUS, Condor, etc.)
   - automation
   - robustness
   - operations

* Real-time analysis experience
   - software optimization
   - hardware experience (infrastructure issues)
   - operational issues (in addition to above)
   - infrastructure for alert system
     - mail systems
     - automated finding charts
     - methods of feedback from community (e.g., "I took a spectrum...")

* DQA
   - identification of metrics involved
   - automated derivation
   - how to provide meaningful feedback to observer and archive users



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