The Future of Information Discovery

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    The Future of Information Discovery - Presentation Transcript

    1. The Future of Information Discovery Ben Shneiderman ben@cs.umd.edu Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies University of Maryland College Park, MD 20742 Interdisciplinary research community - Computer Science & Info Studies - Psych, Socio, Poli Sci & MITH (www.cs.umd.edu/hcil) 1
    2. Design Issues • Input devices & strategies • Keyboards, pointing devices, voice • Direct manipulation • Menus, forms, commands • Output devices & formats • Screens, windows, color, sound • Text, tables, graphics • Instructions, messages, help • Collaboration & Social Media www.awl.com/DTUI • Help, tutorials, training Fifth Edition: March 2009 • Search • Visualization History of HCI & IR: Early Leaders 2
    3. History of HCI & IR: Early Leaders Gerald Salton Eugene Garfield Karen Sparck Jones Ted Codd History of HCI & IR: Early Leaders Gerald Salton Eugene Garfield Karen Sparck Jones Ted Codd Document Scientific Natural Relational Retrieval Publications Language Database 3
    4. History of HCI & IR: Recent Leaders Gary Marchionini Nick Belkin Susan Dumais Marti Hearst HCIR Home Page: Today’s Leaders 4
    5. HCIR Home page: Ideas HCIR Proceedings 5
    6. HCIR Proceedings - Information Exploration & Discovery Process 6
    7. Exploration & Discovery Process Exploration & Discovery Process 7
    8. Exploration & Discovery Process Exploration & Discovery Process Specific fact finding (known-item search) On what day was Barack Obama born? <Google succeeds> 8
    9. Exploration & Discovery Process Specific fact finding (known-item search) On what day was Barack Obama born? <Google succeeds> Extended fact finding (vague query) What cities did Barack Obama live in? Exploration of availability (vague result request) What genealogical information on Barack Obama is at the National Archives? Exploration & Discovery Process Specific fact finding (known-item search) On what day was Barack Obama born? <Google succeeds> Extended fact finding (vague query) What cities did Barack Obama live in? Exploration of availability (vague result request) What genealogical information on Barack Obama is at the National Archives? Open-ended browsing and problem analysis (hidden assumptions) How has Barack Obama’s position on the environment changed since 2001? Mismatch with metadata (requires exhaustive search) How has Barack Obama’s choice of clothing changed during his campaign? 9
    10. Exploration & Discovery Process Specific fact finding (known-item search Extended fact finding (vague query Exploration of availability (vague result request Open-ended browsing and problem analysis (hidden assumptions Mismatch with metadata (requires exhaustive search Exploration & Discovery Process 1-minute Specific fact finding (known-item search Extended fact finding (vague query Weeks & Exploration of availability (vague result request Months Open-ended browsing and problem analysis (hidden assumptions Mismatch with metadata (requires exhaustive search 10
    11. Exploration & Discovery Process Enrich query formulation Expand result management Enable long-term effort Enhance collaboration Deal with special cases of search: - Complete: Legal, patent & medical - Absence: Proving non-existence is difficult - Outliers: Unexpected connections - Bridging: Connecting disciplines (Arrowsmith) HCI & IR Trajectory Document Retrieval Information Retrieval Search (Web) Exploration & Discovery Process 11
    12. HCI & IR Future Document Retrieval Information Retrieval Search (Web) Exploration & Discovery Process Decision Making/Policy Collaboration/Creativity/Innovation Societal Improvement UN Millennium Development Goals To be achieved by 2015 • Eradicate extreme poverty and hunger • Achieve universal primary education • Promote gender equality and empower women • Reduce child mortality • Improve maternal health • Combat HIV/AIDS, malaria and other diseases • Ensure environmental sustainability • Develop a global partnership for development 12
    13. HCI & IR Future Mobile Search Spoken, Pointing & Location Search Voice, Web, SMS & Visual Results Collaboration for Healthcare/Wellness Electronic Health Records Science of Science Social Network Search for Community Safety Usage Log Analysis for Energy Sustainability Species Search for Biodiversity Climate Model Pattern Discovery Map Search for Better Wayfinding Email Discovery: Individuals, Groups & Communities Narrative Search: Trajectory, conflict, resolution Temporal Search: Electronic Health Records 13
    14. Temporal Search: Find Similar Patients Network Data • Nodes & Links • Relationships & communication • Scientific/legal citations • Difficult to complete tasks • Occlusion • Complexity 14
    15. Network Visualization by Semantic Substrates NVSS 1.0 Filtering links by source-target 15
    16. Filtering links by time attribute (1) Network Visualization by Semantic Substrates • Meaningful layout of nodes • User controlled visibility of links • Cross refs in 11 Circuit Courts (green) + few refs to District Court cases www.cs.umd.edu/hcil/nvss 16
    17. Network Visualization by Semantic Substrates NVSS 2.0 with Substrate Designer Citation Patterns: Within Research Front One key paper in DP, Statistical is richly linked 17
    18. Citation Patterns: Out from Statistical Statistical papers largely cite PBMT, in the past 4 years Citation Patterns: from PBMT to Statistical Key papers in PBMT mostly cite the key papers in Statistical 18
    19. Citation Patterns: In to Statistical PBMT & DP have no cross cites and only 2 papers in Statistical are cited jointly from PBMT and DP SocialAction: Senate Vote Patterns Perer & Shneiderman, CHI 2008 19
    20. NodeXL: Network Overview for Discovery & Exploration in Excel www.codeplex.com/nodexl casci.umd.edu/NodeXL_Teaching Weight Watchers Support Group Size = Weight loss Size = Weight loss Color = Questions answered Color = Membership length (Theresa Burlas) 20
    21. Research Methods Controlled experiments Logging usage patterns Multi-dimensional In-Depth Long-Term Case Studies (MILCs) Domain experts doing their own work for weeks & months Science 1.0 + Science 2.0 • Reductionist Integrated • Controlled Interventions & Experiments Case Studies • Laboratory Situated • Natural World Made World 21
    22. Science 1.0 + Science 2.0 • Reductionist Integrated • Controlled Interventions & Experiments Case Studies • Laboratory Situated • Natural World Made World • Hypothesis Testing • Predictive Theories • Replications (AAAS Science 319, March 7, 2008, 1349-1350) HCI & IR: The Final Frontier • Much work to be done • Difficult to attain all our goals • But we can make important contributions 22
    23. HCI & IR: The Final Frontier • Much work to be done • Difficult to attain all our goals • But we can make important contributions • Shift public policy • Change our research community • Restructure our academic curricula • Make the world a better place 27th Anniversary Symposium May 27-28, 2010 www.cs.umd.edu/hcil 23
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