1. Data Mining - Opportunity and Challenge Chair - Al Holm Scribe - Steve Beckwith.ppt - Chuck Pullen Fly on Wall - Lee Anne Willson John Good Bill Dillon

2. Concept Summary b Organized data mining may offer a new way for AAVSO to serve the professional astronomy community while encouraging new membership and new life for some existing members. b Some changes to existing data collection and management would be needed. b Entwined with entire concept of data quality of visual observations.

3. The Promise of Data Mining b Activity for beginner to advanced member b Requires no telescope or observations b Analysis desperately needed, in both AAVSO and other data sets b May appeal to new types of observers

4. The Peril of Data Mining b Requires infrastructure b Infrastructure = $ b Requires Training b Training = $ b Requires evaluation of AAVSO data quality b Evaluation = pain!

5. Concept Overview- Data Enhancement b Existing data base needs to be upgraded to validated b Rapid, machine-based screening of data necessary to keep interest b Some measure of data quality necessary, on both visual, PEP and CCD data. b Vol. archival of FITS CCD frames, with pro level header data, important for NVO (more later).

6. Concept Overview - Infrastructure b Cross platform, free to user, validated software, from simple educational level to high quality analytical. b Multi level query b Rapid access to new data, perhaps with quality flags b In depth training - quantum enhancement of HOA

7. Concept Overview- Marketing b Who are the miners? b Recruit via the web, non-astronomy based technology media, Sci. Amer., SETI@HOME example b Be inclusive of diverse levels, 4th graders to PhDs, but be wary of results. b Define goals and recognize work.

8. Concept Overview - Clients b Who uses the output? b Members b Scientific Community b Educators b The curious...

9. What about the mass of unevaluated survey data? b Data analysis starts at home b If we build it - they will come b Perfect our system in house first, then invite others to join us.

10. Potholes on the Info. Super Hwy. b Interest? b Funding (NVO funds possible) b Sociopolitical b Data flow constrictions (CCD Images) b Automation of data quality evaluation

11. Recommendations b Develop working group to consult. b Combine efforts with overall NVO participation. b Update HOA to reflect new opportunities b Prepare for change…

12. Conclusion AAVSOs mission to promote the science of variable stars requires, in addition to the collection of data, using an integrated suite of database design/upgrade, software, and training for data analysis.

13. CCD/film Data Archival b Important future contribution b Well within goals of AAVSO b Separate but related with data mining b Address as part of NVO