1. Volunteer Thinking with Bossa David P. Anderson Space Sciences Laboratory University of California, Berkeley

2. Scientific workflows define goals volunteers? lab assistants post-docs Herr Professor analyze data write papers perform experiments theorize clean data computers grad students design experiments

3. Volunteer thinking Tasks that can be divided into lots of self- contained “jobs” Jobs can be performed over the Internet Jobs can be done by a significant fraction of the general public (possibly with training) Currently ~10 projects, 50K participants

4. Example The Stardust mission Where’s the dust? Stardust@home – 23K volunteers – 43M viewings – 64 tracks found

5. Lessons learned Motivation – Volunteers will do boring tasks; no need to play games – scientific goals – community, competition – keep volunteers informed Quantifiably high accuracy is possible – calibration jobs – replication

6. Fold It!

7. Space of applications 2D vision – pattern recognition (Stardust@home, GalaxyZoo, Clickworkers) – image analysis (ESP game) 3D manipulation (Fold It!) Natural language Real-world knowledge What else?

8. Middleware jobs middleware people or computers identity accounting queuing assignment validation

9. What’s different? People vary Jobs may not be well-defined aptitude training

10. Bossa Reduces the amount of programming and DB design needed to deploy a volunteer thinking project Policies – Bossa doesn’t provide them – but it provides mechanisms that make it easy to implement a range of policies

11. Bossa abstractions Project Application Instance Application Job User Job User Instance

12. The structure of Bossa Application Bossa callback functions job_show()‏ job_issued()‏ job_finished()‏ job_timed_out()‏ bossa_show_job.php bossa_job_finished.php Bossa API DB

13. Job and result representation Job parameters, results stored in “opaque” PHP structures Callback function to display a job: job_show($job, $inst) Types of jobs – single web page – sequence of pages – offline app

14. Job distribution policy Project A: few jobs, lots of volunteers – do all jobs once, then twice, etc. Project B: many jobs, limited volunteers – do first job N times, then 2 nd job, etc. Bossa: each job has “priority” – adjusted by callback functions Jobs Instances

15. Volunteer assessment How to assess? – training course – calibration tasks – correctness as determined by replication Representation – may be multidimensional – may change during session Bossa mechanisms – opaque data for user – calibration jobs – Bolt course prerequisite

16. Replication policy Examples – fixed replication – adaptive replication Bossa mechanism – job_finished() decides whether more instances are needed, sets priority

17. Use of “experts” Alternatives – experts do the same job, but better – experts do different jobs Bossa mechanisms – users are assigned a “level” (0, 1,...) – jobs have priority P(i) for each level i Example – experts resolve ambiguous jobs – job_finished(): if ambiguous, raise P(1)

18. Bossa integration Current: Soon: Drupal BOINC volunteer computing Bolt teaching, training Bossa volunteer thinking BOINC Basics accounts, groups, credit, communication

19. Projects in development Hominids@home (fossils, Ethiopia) Africa satellite image analysis (UC Berkeley) Mars satellite image analysis (U of Hawaii)

20. Conclusion Bossa: middleware for volunteer thinking You provide: – job representation and display – job distribution and replication policies – volunteer assessment Future directions – thinking/computing workflows – group jobs – jobs as multiplayer online games