1. Reality-based Interfaces for
Collaborative Discovery
Liberact 2013

2. How reality-based interaction can enhance
collaborative learning and discovery?
Frameworks
&Tools
Interactive
Systems
Evaluation
Liberact 2013

3. Renaissance Team as Methodology

4. Outline
G-nome Surfer
Collaborative Exploration of
Genomic Data
MoClo Planner
A Collaborative Tool for Designing and
specifying biological constructs
Liberact 2013

5. ATabletop Interface for Collaborative Exploration of
Genomics
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6. Preliminary User Studies
Position #
PIs 9
Postdocs 6
Industry Researchers 2
Student Researchers 12
Research Assistant 2
Master Student 1
Total 32
Goal
Design requirements for
synthetic biologists
Interview
Procedure
1 hour interviews in
laboratories
Interview
Questions
 Procedure walk-through
 Research goals
 Work practices
 Computational tools
 Future of the field
Data
Collection
 Video
 Voice recordings
 Screenshots
 Observations
Qualitative
Methods
• Affinity diagrams
• Iterative coding
Institutions
• Boston University
• Harvard Medical School
• MIT
• WellesleyCollege
• Wyss Institute

7. Heterogeneous Data

8. 8
Design Goals

9. Locate
Learn Retrieve
Annotate
Compare
O. Shaer, M. Strait, C. Valdes, T. Feng, M. Lintz and H. Wang, Enhancing Genomic
Learning through Tabletop Interaction, Proc. ACM CHI 2011.

11. 1. Microscopic:
Usability of concrete interaction techniques
2. Macroscopic:
Usefulness for real-world tasks
3. Holistic:
Impact on collaborative learning
Evaluation
Liberact 2013

12. Experimental task:
Identify the molecular basis of an unclassified motor mutation in mice
Existing web-based bioinformatics tools G-nome Surfer with multi-mouseGUI G-nome Surfer
Macroscopic Evaluation:
Comparative study with 48 students
Liberact 2013

13. Liberact 2013
Holistic evaluation
Intermediate college-level Neuroscience laboratory
Synthetic biology lab at BU

14. Evaluating Collaborative Problem Solving
• Quantitative measures
– Number and value of
insights
– time per activity
– subjective workload
– attitude
– physical and verbal
participation
– equality of participation
• Qualitative indicators
– collaboration style
– problem-solving strategy
– nature of discussion
Liberact 2013

15. Findings
• G-nome Surfer improves students performance,
reduces workload, and increases enjoyment
(compare to current state-of-the-art bioinformatics
tools)
• The tabletop prototype (compare to multi-mouse
interface):
– Increases physical participation
– Encourages reflection
– Fosters effective collaboration
– Facilitates more intuitive interaction
Liberact 2013

16. MoClo Planner
A collaborative tool for Modular Cloning
Liberact 2013

17. From Design to Synthesis

18. Clones multiple DNA fragments in a single reaction
Fusion sites – the cut and paste sites of Golden Gate cloning
Promoters
Fusion Site
Compatible Fusion Sites RBS
RBSPromoters
Modular Cloning

19. Requirements
• Process
visualization
• Resource
integration
• Efficiency
• Collaboration

20. Level 0: Basic Modules
Level 1:Transcriptional Units
Level 2: Multigene Constructs

21. S.Liu, K. Lu, N. Seifeselassie, C. Grote, N. Francisco, V. Lin, L. Ding, C. Valdes, R.
Kincaid, O. Shaer, MoClo Planner: Supporting Innovation in Bio-Design through
Multitouch Interaction , Demo abstract, ACM ITS 2012.
Research
Design
Build
Test

22. Evaluation
Position #
PIs 1
Postdocs 1
Student Researchers 22
Total 24
Institutions
• Boston University iGEM
• MIT iGEM
• WellesleyCollege
Goal
Evaluate the usability of the
program
Study
Procedure
Use PixelSense in user’s lab
environment
Usability
Task
 Select specific parts from Parts
Registry
 Build a Level 1 module
 Build a Level 2 module
 Create primers
Data
Collection
 Video recording
 Audio recording
 Post-task interview
 NASATLX questionnaire
 Engagement questionnaire

23. User Study Task

24. General findings
• Successful task completion
• User recommended
• Lowered complexity
• Quick and Efficient
Liberact 2013

25. Going forward
1) Reality-based interaction offers unique opportunities for
enhancing discovery and learning in data-intensive areas.
2) Designing interaction for problems in genomics can help move
forwards the theory and practice ofTEI.
3) Future research includes:
How to visualize and engage data, activity, progress spanning
many systems, people, places, timescales?
What representational forms, device ecologies, most
appropriate for large, abstract data?
Facilitating engagement with big data in ways that highlight
connections between multiple forms of evidence

26. Lessons learned and Going Forward
RBI can facilitate immediate, visible, and easily reversible manipulations
• How to designTEI for open-ended creative inquiries?
Visual representations can facilitate multi-stage workflows
• Important for execution and tracking of complex analyses
• Need parametrized, annotatable representations of complex large datasets
RBI could facilitate collaboration for co-located teams
• Large interdisciplinary teams and distributed work are common in this area
• Users can jointly manipulate assumptions and see consequences
RBIs can support understanding and discovery
• Provide access to different pieces of the problem (data, reactions)
• Help users forms accurate mental models through tangible/embodied manipulation

27. Acknowledgements
Liberact 2013

28. Orit Shaer
oshaer@wellesley.edu
Liberact 2013
Thank you