investigating advanced user support desired by computational biologists

INVESTIGATING ADVANCED USER SUPPORT DESIRED BY COMPUTATIONAL BIOLOGISTSAdam Eck, Derrick Lam, and Dr. Leen-Kiat Soh September 30, 2010

http://biofinity.unl.edu/

Questions

2

1. What types of advanced user support are available?

2. How can advanced user support assist computational biologists?

3. What can we do beyond advanced support?

4. What avenues exist for joint research?TDWG 2010 -- Advanced User Support Working Group


Agenda

3

Introductions

Presentation

Questions

Survey

DiscussionTDWG 2010 -- Advanced User Support Working Group


Agenda

4

Introductions

Presentation

Questions

Survey



Motivation

5

Making the system functional for research Infrastructure Hardware Software

Making the system actively work for users Efficiency and Effectiveness Discovery and Investigation

TDWG 2010 -- Advanced User Support Working Group


Overview

6

Running Examples Encyclopedia of Life (EOL) Biofinity Project

Advanced user support Approaches/techniques Application to biodiversity research

Concerns/ConclusionsTDWG 2010 -- Advanced User Support Working Group


Examples| EOL

7

Encyclopedia of Life (Wilson, 2003; EOL, 2010) Portal for biodiversity information

Web page for every species Information about species Map Plots Taxonomy

Link related information Publications

Source: http://www.eol.org

Examples Support ConclusionsTDWG 2010 -- Advanced User Support Working Group

http://www.eol.org/


Examples| EOL

8

Source: http://www.eol.org


http://www.eol.org/


Examples| Biofinity Project

9

Biofinity Project Research portal for computational biology Organized around MyLabs

Federated databases from multiple groups/domains Biodiversity, genomics, etc. Ontologies representing relationships

Integrated tools for manipulating data Wiki-based collaboration Intelligent user interface to support users

Source: http://biofinity.unl.edu




Examples| Biofinity Project

10

Source: http://biofinity.unl.edu




Support| Overview

11

User Recommendations Summarization Task Automation Social Networking User Training Tracking Others



Support| Artificial Intelligence

12

Machine Learning Learn from user behavior, data Improve over time

Data Mining Find interesting patterns, relationships,

information

Intelligent Agents Personal Assistants



Support| User Recommendations

13Source: http://www.amazon.com


http://www.amazon.com/



14

Source: http://www.amazon.com





15

Make suggestions to users Actions Information

User-oriented Past behavior Interests Personal characteristics

Item-oriented Related items




16Examples Support Conclusions

EOL: Related publications, map data Biofinity: Pages to view, edit, create



Support| Summarization

17

Problem: Data overload! Too much to look through

Solution: filters? Have to know what you are looking for Good for expected results

What about unexpected?




18

Summarization Condense information into accessible form

Typical actions (Tucker and Whittaker, 2009) Excision Highlighting

Statistical processing Automate discovery in data




19

Example: Brussell (Wagner et al., 2009) News client plugin to Firefox Summarizes content for users

Uses summarization for context-awareness Finds additional news clips Builds timeline of events Finds related information on Wikipedia




20

EOL Summarize information across related species Create field guides

Biofinity Summarize occurrences plotted on map Analyze results of multiple in silico

experiments Automatically link related Wiki pages



Support| Task Automation

21

Users perform many repetitive tasks Scheduling meetings Sending emails Running experiments

Tasks have structure Can learn workflows (Shen et al., 2009;

Yorke-Smith et al., 2009) Automate execution



Support| Task Automation

22

EOL Field guide creation Page completion

Biofinity Run common experiments Automate Wiki page creation



Support| Social Networking

23

Sources: http://www.facebook.com, http://scratchpads.eu/, http://www.myexperiment.org/


http://www.facebook.com/

http://scratchpads.eu/

http://www.myexperiment.org/



24

Goal: connect related users Similar interests, expertise, acquaintances,

etc.

Repository of information Leave things for others to look at Mode of communication




25

Find connections amongst users Acquaintances, collaborators, etc.

Matchmake users (Vassileva et. al, 2003; Kester et. al, 2007) Find new collaborators Similar interests, complementary skills Valuable in cross-disciplinary research

Trust and reputation models (Sabater and Sierra, 2001; 2002)




26

EOL Find users working on similar species,

taxonomy tree Add authority scores based on uploaders

Biofinity Matchmake users from similar labs Recommend users editing similar pages



Support| User Training

27

Use system to train users Train how to use the system

Guided interactions Tutorials

Student education Teach key concepts

How to conduct research Process training Follow expert behavior Outreach for Citizen Science




28

Beyond FAQs and Walkthroughs

Learn good behavior from users Recommend to others

React to user actions/mistakes Wrong parameters to tools Many searches without results




29

EOL Student education How curators manage pages

Biofinity How to run embedded tools Improve search results



Support| Tracking and Learning

30

Need to learn models for advanced support User, data, tasks, etc.

Models need observations Intrusive: explicitly ask user for information

Most direct, more frustration Nonintrusive: implicitly derived from interactions

Less frustration, could be inaccurate

Rate of learning

Tracking usage vs. data



Support| Others

31

Adaptive Interfaces Change positions to match user behavior

Data visualization Adapt data displays based on content

Virtual agents Personal assistants with presence



Conclusions| Concerns

32

Privacy What information is mine? How to share? How to safeguard?

Approaches Opt-out settings Encryption and coded identification




33

Trust Something else is making decisions… What do I need to know? External data

Approaches Transparency Trust and reputation models Explicit ratings from users Implicit ratings based on usage




34

User Frustration Too many prompts Bad recommendations

How to reduce/avoid frustration? Reduce frequency Cool-off period Expected value

Challenge Balancing benefit with cost of interruption



Conclusions| Conclusion

35

Making the system actively work for users

Many techniques User recommendations Summarization Task automation Social networking User training

Concerns: privacy, trust, frustration



Questions?

36TDWG 2010 -- Advanced User Support Working Group

Contact: {aeck, dlam, lksoh}@cse.unl.edu


Agenda

37

Introductions

Presentation

Questions

Survey



Agenda

38

Introductions

Presentation

Questions

Survey



Biofinity Workshop

39

Biofinity Workshop Friday 2pm Saturday 9 am – 1:30 pm Location: Speck Auditorium (Rowe)

[email protected] Informal walk-ins Free!


mailto:[email protected]


References

40

Biofinity Project. Available from http://biofinity.unl.edu. Accessed 24 Sep 2010. Encyclopedia of Life, EOL 2010 Brochure, 2010. Available from

http://content2.eol.org/content/2010/08/26/08/00750.pdf. Accessed 24 Sep 2010 . J. Kester, et. al, Matchmaking in learning networks: Bringing learners together for knowledge

sharing, Interactive Learning Environments, vol. 15, no. 2, pp. 117-126, 2007. J. Sabater and C. Sierra, REGRET: reputation in gegarious socities, Proc. of Fourth Workshop on

Deception, Fraud and Trust in Agent Societies, pp. 61-69, 2001. J. Sabater and C. Sierra, Reputation and social network analysis in multi-agent systems, Proc. of

AAMAS’02, pp. 475-482, 2002. J. Shen, E. Fitzhenry, and T.G. Dietterich, Discovering frequent work procedures from resource

connections, Proc. of IUI’09, Sanibel Island, Florida, pp. 277-285, Feb. 8-11, 2009. S. Tucker and S. Whittaker, Have a say over what you see: Evaluating interactive compression

techniques, Proc. of IUI’09, Sanibel Island, Florida, pp. 37-46, Feb. 8-11, 2009. J. Vassileva, G. McCalla, and J. Greer, Multi-agent multi-user modeling in I-Help, User Modeling and

User-Adapted Interactions, vol. 13, pp. 179-210, 2003. E.J. Wagner, J. Liu, L. Birnbaum, and K.D. Forbus, Rich interfaces for reading news on the web,

Proc. of IUI’09, Sanibel Island, Florida, pp. 27-36, Feb. 8-11, 2009. E.O. Wilson. The encyclopedia of life. Trends in Ecology and Evolution, vol. 18, no. 2, pp. 77-80,

2003. Available from http://www.sciencedirect.com/science/article/B6VJ1-47C8RDN-3/2/befac60e32dd59e55ff8bfc75f9848c6. ISSN 0169-5347, DOI: 10.1016/S0169-5347(02)00040-X.

N. Yorke-Smith, S. Saddati, K.L. Meyers, and D.N. Morley, Like an intuitive and courteous butler: a proactive personal agent for task management, Proc. of AAMAS’09, Budapest, Hungary, pp. 337-344, May 13-15, 2009.TDWG 2010 -- Advanced User Support Working Group


http://content2.eol.org/content/2010/08/26/08/00750.pdf.%20Accessed%2024%20Sep%202010

http://www.sciencedirect.com/science/article/B6VJ1-47C8RDN-3/2/befac60e32dd59e55ff8bfc75f9848c6

http://www.sciencedirect.com/science/article/B6VJ1-47C8RDN-3/2/befac60e32dd59e55ff8bfc75f9848c6


Image References

41

Amazon. Available from http://www.amazon.com. Accessed 23 Sep 2010.

Biofinity Project. Available from http://biofinity.unl.edu. Accessed 24 Sep 2010.

EDIT Scratchpads. Available from http://scratchpads.eu/. Accessed 23 Sep 2010.

Encyclopedia of Life. Available from http://www.eol.org. Accessed 24 Sep 2010.

Facebook. Available from http://www.facebook.com. Accessed 23 Sep 2010.

MyExperiment. Available from http://www.myexperiment.org. Accessed 23 Sep 2010.

P. Patterson, C. Parr, and T. Dewey. Editors. "Homo sapiens Linnaeus, 1758". Encyclopedia of Life, available from http://www.eol.org/pages/327955. Accessed 24 Sep 2010.




http://scratchpads.eu/

http://www.eol.org/

http://www.facebook.com/

http://www.myexperiment.org/

http://www.eol.org/pages/327955.%20Accessed%2024%20Sep%202010

investigating advanced user support desired by computational biologists

Documents

advanced support

advanced user support

user behavior

group motivation5making

group examples eol8source

investigation tdwg

computational biologyorganized

related publications