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ExSciTecH: Expanding Volunteer Computing
to Explore Science, Technology, and Health

    M.	
  Matheny1,	
  S.	
  Schlachter1,	
  L.M.	
  Crouse2,	
  E.T.	
  Kimmel2,	
  	
  
    T.	
  Estrada1,	
  M.	
  Schumann3,	
  R.	
  Armen3,	
  G.	
  ZoppeB2,	
  and	
  	
  
                                   M.	
  Taufer1	
  

                            1University	
  of	
  Delaware	
  
                           2University	
  of	
  Millersville	
  
                        3Thomas	
  Jefferson	
  University	
  
Volunteer Computing
            •    Volunteer Computing (VC) is a
                 form of distributed computing in
                 which volunteers donate
                 processing and storage resources
                 to computing projects.
            •    Every job represents a portion of a
                 larger problem whose
                 computation is divided into
                 smaller chunks and addressed in
                 parallel. 

            •    Applications suited for VC include
                 searches in very large spaces,
                 parameter tuning, and data
                 analysis.



                                                 1
Volunteers
•  Are not representative of the general population
    •  White males with a background in computers
•  Paradigm causes them to be passive
•  Lose interest in the project and uninstall the VC software within a few
   months of participation




                                                                             2
Main Contribution
•    Problem: Volunteer Computing appeals to a very narrow demographic
      –  We want to utilize intuitive technologies and user interfaces to appeal
         to historic minorities in Science, Technology, Engineering and
         Mathematics (STEM)
•    Problem: In VC participants are generally passive and not involved in the
     research process
      –  We want to get volunteers to help solve important research problems
         and make scientific discovery




                                                                                   3
Outline
                                         
•    Background
•    Motivation and Plan
•    Implementation
•    Game Testing
•    Conclusion and Future Work




                                             4
Outline
                                         
•    Background
•    Motivation and Plan
•    Implementation
•    Testing
•    Conclusion and Future Work




                                             5
Docking@Home
                                    




•  Docking@Home is powered by Berkley Infrastructure for Network Computing
   (BOINC)
                                                                             6
D@H Scientific Goals
                                          
•    Self-Docking
      –  Searching for protein inhibitors 
      –  Targeted diseases
           •  HIV
           •  Breast cancer (trypsin)
•    Cross-Docking
      –  Identifying drug side effects
      –  Look at proteins similar to the
      disease protein
      –  Naïve approach: all to all
           •  All proteins
           •  All ligands
      –  This is where we want to utilize volunteers to reduce search space


                                                                               7
Related Work
                                         
•    Fold.it
      –  Developed by the same team as Rosetta@Home
      –  Aims to use volunteers to fold proteins through puzzles
      –  Complements VC system, does not integrate with VC system
•    Bossa
      –  Developed by the BOINC team
      –  Volunteers use cognition, knowledge, and intelligence to solve
         problems
•    Luis von Ahn’s work
      –  Phetch – improving web accessibility
      –  Games with a purpose (GWAP)
      –  reCAPTCHA




                                                                          8
Outline
                                         
•    Background
•    Motivation and Plan
•    Implementation
•    Testing
•    Conclusion and Future Work




                                             9
Docking@Home: As it stands
                         




                             10
ExSciTecH: Learning Stage
                        




                            11
ExSciTecH: Engaging Stage
                        




                            12
ExSciTecH: Engaging Stage
                        




                            13
ExSciTecH: the full circle
                         




                             14
Outline
                                         
•    Background
•    Motivation and Plan
•    Implementation
•    Testing
•    Conclusion and Future Work




                                             15
BOINC Infrastructure
                                               
             C L I E N T"                               S E R V E R"
                                 Download"

                                       Upload"



                    BOINC"          CGI                  BOINC
                    Client"        BOINC"                                   Daemons"
                                                          DB"

Local File
 System"



                                                                           Back-end!
                     Client!      Front-end!



                                                                  BOINC"
                     Web
                    Browser"
        BOINC!                                   Web Interface!
                                                                                       16
BOINC + ExSciTecH
             C L I E N T"                               S E R V E R"
                                 Download"

                                       Upload"



                    BOINC"          CGI                  BOINC
                    Client"        BOINC"                                   Daemons"
                                                          DB"

Local File           Learn"          CGI
 System"             Game"          Learn"
                     VMD"                                                      ExSciTecH"
                                                        Game DB"               Daemons"
                    Engage          CGI
                     Game"         Engage"
                                                                           Back-end!
                     Client!     Front-end!



        Player!                     Player"        Teacher"       BOINC"
                     Web
        Teacher!
                    Browser"
        BOINC!                                   Web Interface!
                                                                                            17
ExSciTecH Client
                                         




•    Modularly designed – each game is a separate program and the client
     acts as a manager
                                                                           18
Learning Games
                                                  
•    Teach volunteers about science without intimidating them
•    Several levels available:
      –    High school student
      –    Under graduate student
      –    Graduate student
      –    Pharmaceutical student
      –    Professional chemist
•    As players progress through the levels the game becomes more
     challenging
•    Familiarize volunteers with the science
•    Give D@H more exposure
      –  Students in classrooms




                                                                    19
Molecule Flashcards
                                           




•    Players must identify or categorize a 3D molecule as it flies towards them
•    If the player incorrectly identifies the molecule they’re given access to
     additional information about it
                                                                                  20
Engaging Games
                                           
•    Volunteers have been trained by the learning stage
•    Building a job
      –  Short game
      –  Game objects correlate to job input parameters
          •    Protein (disease)
          •    Ligand (drug)
          •    Ligand Confirmation
          •    Ligand Rotation
•    Submitting a job
      –  Game submits these parameters to the server
      –  Server builds a job based on these parameters
•    Getting results
      –  Good results  More games!
      –  Volunteering CPU time  More games!

                                                           21
Drag’n’Dock
                                           
•    Volunteers rotate a
     protein and select a
     ligand
•    Then they fly a
     spaceship over the
     protein with the ligand
     in tow
•    They attempt to dock
     the ligand in the protein
     with the space ship
•    The game submits data
     to the server to build a
     D@H work unit




                                               22
Drag’n’Dock
                                           
•    Volunteers rotate a
     protein and select a
     ligand
•    Then they fly a
     spaceship over the
     protein with the ligand
     in tow
•    They attempt to dock
     the ligand in the protein
     with the space ship
•    The game submits data
     to the server to build a
     D@H work unit




                                               23
Drag’n’Dock
                                           
•    Volunteers rotate a
     protein and select a
     ligand
•    Then they fly a
     spaceship over the
     protein with the ligand
     in tow
•    They attempt to dock
     the ligand in the protein
     with the space ship
•    The game submits data
     to the server to build a
     D@H work unit




                                               24
Outline
                                         
•    Background
•    Motivation and Plan
•    Implementation
•    Testing
•    Conclusion and Future Work




                                             25
Testing the Molecule Flashcard Game
                                             
•    What we want to learn:
      –  Do people learn more with the game than they do with a paper test?
      –  Do they enjoy our game more than a paper test?
      –  What improvements can we make to the game?
•    How we tested:
      –  We took a group of students and had half of them attempt to identify
         molecules with our flashcard game and half of them attempt to identify
         molecules on a paper test
•    What we measured:
      –  Time to complete the game/test
      –  Number of molecules correctly identified
      –  Survey with level of enjoyment and comments




                                                                                 26
Testing Setup
•    24 computer science students
      •  10-minute introduction
      –  14 undergraduate students
     •  Students split into two groups
      –  10 graduate students 
             –  Paper test
                                            –  Molecule flashcard game




                                  Vs.




                                                                            27
Results and Discussion
                                    




•  Make more errors, but enjoy the game more
•  Tend to be faster – less reflection


                                               28
Results and Discussion
                                     




•  Learning Curve
•  Confusing 3D representations




                                         29
Outline
                                         
•    Background
•    Motivation and Plan
•    Implementation
•    Testing
•    Conclusion and Future Work




                                             30
Conclusions and Future Work
                                           
•    We can transform the way volunteers participate in VC projects
      –  More accessible
      –  More exciting
•    We show students had a higher level of enthusiasm when using ExSciTecH
     rather than traditional learning tools
•    We identified improvements that could be made to the flashcard game:
      –  Variable speed
      –  Pause
      –  Skip and come back
•    We are moving forward with the ExSciTecH development by continuing
     development of engaging games




                                                                              31
Acknowledgments
                                                       
Thanks	
  to:	
                                    GCLab	
  group	
  
M.	
  Matheny	
  (UD)	
  
S.	
  Schlachter	
  (UD)	
  	
  
L.M.	
  Crouse	
  (U.	
  Millersville)	
  
E.T.	
  Kimmel	
  (U.	
  Millersville)	
  
T.	
  Estrada	
  (UD)	
  
M.	
  Schumann	
  (TJU)	
  
R.	
  Armen	
  (TJU)	
  
G.	
  ZoppeB	
  (U.	
  Millersville)	
  

                                                    Sponsors:           Contact:	
  
                                                                        taufer@udel.edu	
  


                                             IIS #0968350/#0968368                            32

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ExSciTecH: Expanding Volunteer Computing to Explore Science, Technology, and Health

  • 1. ExSciTecH: Expanding Volunteer Computing to Explore Science, Technology, and Health M.  Matheny1,  S.  Schlachter1,  L.M.  Crouse2,  E.T.  Kimmel2,     T.  Estrada1,  M.  Schumann3,  R.  Armen3,  G.  ZoppeB2,  and     M.  Taufer1   1University  of  Delaware   2University  of  Millersville   3Thomas  Jefferson  University  
  • 2. Volunteer Computing •  Volunteer Computing (VC) is a form of distributed computing in which volunteers donate processing and storage resources to computing projects. •  Every job represents a portion of a larger problem whose computation is divided into smaller chunks and addressed in parallel. •  Applications suited for VC include searches in very large spaces, parameter tuning, and data analysis. 1
  • 3. Volunteers •  Are not representative of the general population •  White males with a background in computers •  Paradigm causes them to be passive •  Lose interest in the project and uninstall the VC software within a few months of participation 2
  • 4. Main Contribution •  Problem: Volunteer Computing appeals to a very narrow demographic –  We want to utilize intuitive technologies and user interfaces to appeal to historic minorities in Science, Technology, Engineering and Mathematics (STEM) •  Problem: In VC participants are generally passive and not involved in the research process –  We want to get volunteers to help solve important research problems and make scientific discovery 3
  • 5. Outline •  Background •  Motivation and Plan •  Implementation •  Game Testing •  Conclusion and Future Work 4
  • 6. Outline •  Background •  Motivation and Plan •  Implementation •  Testing •  Conclusion and Future Work 5
  • 7. Docking@Home •  Docking@Home is powered by Berkley Infrastructure for Network Computing (BOINC) 6
  • 8. D@H Scientific Goals •  Self-Docking –  Searching for protein inhibitors –  Targeted diseases •  HIV •  Breast cancer (trypsin) •  Cross-Docking –  Identifying drug side effects –  Look at proteins similar to the disease protein –  Naïve approach: all to all •  All proteins •  All ligands –  This is where we want to utilize volunteers to reduce search space 7
  • 9. Related Work •  Fold.it –  Developed by the same team as Rosetta@Home –  Aims to use volunteers to fold proteins through puzzles –  Complements VC system, does not integrate with VC system •  Bossa –  Developed by the BOINC team –  Volunteers use cognition, knowledge, and intelligence to solve problems •  Luis von Ahn’s work –  Phetch – improving web accessibility –  Games with a purpose (GWAP) –  reCAPTCHA 8
  • 10. Outline •  Background •  Motivation and Plan •  Implementation •  Testing •  Conclusion and Future Work 9
  • 11. Docking@Home: As it stands 10
  • 15. ExSciTecH: the full circle 14
  • 16. Outline •  Background •  Motivation and Plan •  Implementation •  Testing •  Conclusion and Future Work 15
  • 17. BOINC Infrastructure C L I E N T" S E R V E R" Download" Upload" BOINC" CGI BOINC Client" BOINC" Daemons" DB" Local File System" Back-end! Client! Front-end! BOINC" Web Browser" BOINC! Web Interface! 16
  • 18. BOINC + ExSciTecH C L I E N T" S E R V E R" Download" Upload" BOINC" CGI BOINC Client" BOINC" Daemons" DB" Local File Learn" CGI System" Game" Learn" VMD" ExSciTecH" Game DB" Daemons" Engage CGI Game" Engage" Back-end! Client! Front-end! Player! Player" Teacher" BOINC" Web Teacher! Browser" BOINC! Web Interface! 17
  • 19. ExSciTecH Client •  Modularly designed – each game is a separate program and the client acts as a manager 18
  • 20. Learning Games •  Teach volunteers about science without intimidating them •  Several levels available: –  High school student –  Under graduate student –  Graduate student –  Pharmaceutical student –  Professional chemist •  As players progress through the levels the game becomes more challenging •  Familiarize volunteers with the science •  Give D@H more exposure –  Students in classrooms 19
  • 21. Molecule Flashcards •  Players must identify or categorize a 3D molecule as it flies towards them •  If the player incorrectly identifies the molecule they’re given access to additional information about it 20
  • 22. Engaging Games •  Volunteers have been trained by the learning stage •  Building a job –  Short game –  Game objects correlate to job input parameters •  Protein (disease) •  Ligand (drug) •  Ligand Confirmation •  Ligand Rotation •  Submitting a job –  Game submits these parameters to the server –  Server builds a job based on these parameters •  Getting results –  Good results  More games! –  Volunteering CPU time  More games! 21
  • 23. Drag’n’Dock •  Volunteers rotate a protein and select a ligand •  Then they fly a spaceship over the protein with the ligand in tow •  They attempt to dock the ligand in the protein with the space ship •  The game submits data to the server to build a D@H work unit 22
  • 24. Drag’n’Dock •  Volunteers rotate a protein and select a ligand •  Then they fly a spaceship over the protein with the ligand in tow •  They attempt to dock the ligand in the protein with the space ship •  The game submits data to the server to build a D@H work unit 23
  • 25. Drag’n’Dock •  Volunteers rotate a protein and select a ligand •  Then they fly a spaceship over the protein with the ligand in tow •  They attempt to dock the ligand in the protein with the space ship •  The game submits data to the server to build a D@H work unit 24
  • 26. Outline •  Background •  Motivation and Plan •  Implementation •  Testing •  Conclusion and Future Work 25
  • 27. Testing the Molecule Flashcard Game •  What we want to learn: –  Do people learn more with the game than they do with a paper test? –  Do they enjoy our game more than a paper test? –  What improvements can we make to the game? •  How we tested: –  We took a group of students and had half of them attempt to identify molecules with our flashcard game and half of them attempt to identify molecules on a paper test •  What we measured: –  Time to complete the game/test –  Number of molecules correctly identified –  Survey with level of enjoyment and comments 26
  • 28. Testing Setup •  24 computer science students •  10-minute introduction –  14 undergraduate students •  Students split into two groups –  10 graduate students –  Paper test –  Molecule flashcard game Vs. 27
  • 29. Results and Discussion •  Make more errors, but enjoy the game more •  Tend to be faster – less reflection 28
  • 30. Results and Discussion •  Learning Curve •  Confusing 3D representations 29
  • 31. Outline •  Background •  Motivation and Plan •  Implementation •  Testing •  Conclusion and Future Work 30
  • 32. Conclusions and Future Work •  We can transform the way volunteers participate in VC projects –  More accessible –  More exciting •  We show students had a higher level of enthusiasm when using ExSciTecH rather than traditional learning tools •  We identified improvements that could be made to the flashcard game: –  Variable speed –  Pause –  Skip and come back •  We are moving forward with the ExSciTecH development by continuing development of engaging games 31
  • 33. Acknowledgments Thanks  to:   GCLab  group   M.  Matheny  (UD)   S.  Schlachter  (UD)     L.M.  Crouse  (U.  Millersville)   E.T.  Kimmel  (U.  Millersville)   T.  Estrada  (UD)   M.  Schumann  (TJU)   R.  Armen  (TJU)   G.  ZoppeB  (U.  Millersville)   Sponsors: Contact:   taufer@udel.edu   IIS #0968350/#0968368 32