Convergence09
From media X
Contents |
[edit] Collaborative Visualization for Collective, Connective, and Distributed Intelligence
AKA: Dynamic Knowledge Networks - Synthetic Minds
[edit] Event Type
Summer Institute at Wallenberg Hall Workshop - Visualization Vanguard Collaboratory
Download the original visual overview and agenda here: Collaboratory Overview
Evening reception on August 12, 7-9pm and Immersive GeoDome Experience at 6pm on August 13 (see overview for details)
Please visit the Comprehensive Visual Documentation Web Page for this Collaboratory at Indiana University's Scimaps.org [LINK]
[edit] Date
August 12-13-14, 2009
124 Wallenberg Hall, Building 160, 450 Serra Drive, Stanford, CA
[edit] SYNTHESIS FROM COLLABORATORY
[edit] Purpose of Collaboratory
To create and support a cascading of breakthroughs by addressing essential questions about the current state of data visualization and science mapping:
- How do most people see, think, and feel about data?
- What is the biggest challenge in data visualization – looking at tools and processes?
- How do we choose best approaches, tools, languages and systems for managing and visualizing data?
- How to we build analysis tools for group inquiry and collaboration?
- How does data visualization work to help understand scientific and mathematical understanding?
- How do we envision a new genre of data visualization?
- How do we support data transfer between and among the sciences?
[edit] Goals and Comments from Attendee Introductions
- Data visualization of models and systems (physical sciences and natural systems)
- Gaming visualizations could be useful for cartographies
- Time and space represents a new domain for visualization
- Citizens need to be science and mathematics literate
- Science and mathematics need visualization – especially data and model visualization
- Data visualization could be a universal language if humanity were a super organism / global mind
- Thoughts about data visualization include how people see and navigate information,
- Humans are the connective part of collective intelligence.
- Key word: infographics, social data
- Can data visualization help environmental decision making?
- Visualization can help for the framing of questions, decision support, and practicing environmental history.
- Layers of information and visualization facilitate deeper levels of data inquiry.
- Augmented tools for human analysis of data facilitates general navigation of complex topics
- Human concerns include collective and collaborative efforts in health care – how do we cure together? What treatments will work for most maladies?
- How do we crowdsource personalized medicine?
- What are the (feedback) loops of perception and action in data visualization?
- How do you make information available? How do you query data?
- Wikipedia has maps of visual knowledge – but how do you join and navigate different domains?
- How do humans interact in a 3D world? How do we collaborate efficiently?
- Can data visualization deepen our understanding of events, systems, and phenomenon?
- Data visualization, data mining and text mining are interesting converging tools and approaches to navigate structured and unstructured text, and to find connections between and among publications.
- Heuristics are important in understanding and interrogating information, and using data tools to help understand future consequences of current decisions (especially those which impact the environment).
- Some understandings of future consequences include forecasting future disruptions.
- Ideas inform a data space
- On demand communities for live events enhance ‘social learning’
- Need to understand visualization in context – create visualization taxonomies
- In business parlance, some data visualization might include:
1. How we got here
2. Mess map
3. Plausible solutions
[edit] Synthetic Conclusions & Key Questions
Cultural Issues:
Cultural frameworks – interchange of data, information, and knowledge through different human filters. We need to support cultural/linguistic differences for analysis/interpretation (symbols, color, metaphors differ culturally). Flexible “legends” could be an approach. How do you visualize culture and cultural competency?
Transparency:
Transparency and open data are important – information, data, and symbols influence informatics. Total transparency requires many readers collaborating.
Context:
How are the classification systems defined/created? Need for data curation as a practice. We need to synthesize/export “knowledge” gleaned from data. Integration of “data” - i.e., conceptual models and narrative, and the human interaction with data. We need to address the “emotional intelligence” that is part of reading and collaborating around data visualization.
Social Aspects:
We need more disciplined and broad ranging crowdsourcing approach to data sharing and more scalable visual analysis and stronger collaborative visualization tools. We need to preserve the social nature of data across all platforms, real world and digital. How do our visualization activities draw from and nurture “Connective Intelligence”? How do we synthesize data into knowledge - wisdom?
Data Acquisition:
How do we cope with massive amounts of data? What are the data sources? What are the issues, assumptions, questions and purposes behind the acquisition of data?
Data Neutrality:
There is no neutral data. What are the biases? What was the context of the acquisition? Who commissioned or owns data? What are the conscious and unconscious biases? Data isn’t objective – it can be subjective as it changes over time. We need to have a broader context and understanding of the worldviews of global users/creators/participants. Data should have real impact with and without human ‘spin’ on information
Scalability:
What will be the catalyst to get broader adoption of tools and process – what is the tipping point for this phenomenon? The current collapse of the business model of journalism and the profusion of multiple sources of data on the Internet may be a tipping point for the rapid adoption of new modes of data presentation. We are only at the early stage of open source tools and code, open content and open APIs.
Access:
We need tools for the common man, realtime interactivity. We need to allow visualization process and representations to move seamlessly from paper spaces to digital spaces.
Data Perception:
We must understand the perceptual aspects of datavis. We need to understand the strengths and weaknesses of varied communication environments for data visualization (i.e., collaborative immersive spaces, synchronous online interfaces, asynchronous display, mobile displays). We need to enhance the ability to create mobility between dimensions (2d, 3d, 4d) of display. How do we visualize the confluence of time and space? We need to have an ability to see the human perspective of the universe, our place in the universe and our place in culture - multiple scales for visualizing our networks and knowledge creation. How does data visualization support systems thinking and sythetic points of view?
Data Visualization Literacy:
Tool / platform / algorithm / display. Can we develop a standard visual vocabulary? How do you get deeper understanding – how do you ask more sophisticated questions. Presenting contextual data that highlights case studies – research projects. How do we build from a longer history of perception/perceptual frameworks?
[edit]
CASE-STUDIES
Battelle Center STEM Project
- Stemography project
- Socialize conversations over sensitive issues
- Snapshot representations
- Students longitudinal threads
- Value for grassroots participants
- A knowledge mapping iterative process
- Structure inquiries around improving the process
Buckminster Fuller Challenge – Idea Index
- What is in development geospatially and geotemporally?
- What kind of useability testing is needed?
- How do we map the village of topics by affinity groups
- How are ontologies developed for a Design Science taxonomy?
- Knowledge gardening evolutionary development
- We need strong ontologies symbiotically working with Affinity as a revolving process
Spatial History Project
- Very conceptual challenge:
- A lot of data in multiple formats – time, space, scale
- Who is our audience?
- Three main challenges:
1. What is the best data format?
2. What are the best output formats?
3. How do you make data more interesting?
- How do we extend our process?
- How do you map uncertainty?
- How can we use crowdsourcing?
- SCHEMA - API and tech systems
- Richness of spatial data
- We want to annotate our maps to allow conversations around them
[edit] Breakout Sessions Synthesis
[edit] TOOLS
State of the Art Visualization Tools
Open Source tools: Flare, Prefuse, Processing 1.0, ProtoViz
InfoVis Cyberinfrastructure at Indiana University
Post its? Posters?
Gapminder.org
Swivel.org
SimEarth (based on Lovelock’s Daisyworld algorithm)
Existing Challenges
Need declarative interfaces – allow user to say what he/she wants to understand or examine
Need data wrangling tools
Need tools for the common man
What do tools give you?
Why do you choose a particular tool?
How do our tools enable collective self-reflexivity?
How do our tools support iterative visualizations?
Platforms for visualization / platforms for conversation
Role based collaboration platforms
Future scenarios of tools
Data visualization versus mapping and… or…
Opportunities for Leverage
Delay locking process as long as possible
Science and collaboration should provide a non-prescriptive step ladder to transparency
Look at any object as toy – how does your relationship to it (tool/data) change?
Tools for feedback annotation social interpretation of visualization
everything must be faster and faster – people want to be able to get information faster – data liquidity
More and more systems of information are getting interconnected.
Data visualization and computational tools (Lotus 1-2-3) facilitated mergers and acquisitions in the early to mid 80s
Climate simulation has been made much simpler to ‘approximate’ and have helped in some diplomatic conversations
Santa Fe studies of perception? Representation and organization of the perception
Impact of greater transparency on decision making
[edit] PHILOSOPHICAL CONCEPTS
State of the Art Approaches
If you know more things faster, do you know anything better?
Graphic as: 1. Summary of data or 2. Elicitation of new idea in viewer
The map is a hypothesis … a point of departure
Existing Challenges
Visual understanding is a social thing – collective/social sensemaking
Crowdsourcing: when is it really the “crowd”, when is it really undemocratic?
Role-based collaboration platforms
From tech “push” to user “pull”
Impact of greater transparency on decision-making? CEO salaries / Govt. corruption
Impact and effects of “speed” on knowing and understanding
Representation and the organization of perception
Platforms for Visualization – Platforms for conversation
Interface design and the tacit/formal knowledge interface
Data Viz versus Mapping – and? Or?
Role-based needs for representation
Intellectual vs emotional (agreement/communication)
Data visualization is an abstraction – never completely correct
Falsifyability makes it hard to have paradoxes
Observe exterior objective vs observe interior subjective
Me-think vs We-think
Science is not a world view but evolves
Different philosophy of Eastern and Western culture
What results can be replicated
Logic and Empirical data vs Paradox and Subjective empiricism
Falsify vs Paradoxes are okay
Demographics – under-represented groups = growing majority
Don’t learn into a hole – today’s workers need a flexible, transferable base of skills and knowledge.
Should humans or machines draw pics from data?
What is the goal of visualization?
Hegemonic principles affect data collection
Data-rich can --- innovation-poor
Map is consciously and unconsciously biased
What is the question being asked
Make them dynamic, not static
What is the meaning of the data?
Are we missing the context of data
Should humans or machines draw pictures (and conclusions?) from data?
(Information) maps are consciously and unconsciously biased
(Information) visualization should be dynamic, not static
Children are growing up with visualization as a norm – they don’t understand what is going on underneath
Data visualization decision support systems would help policy makers develop better insights and comprehension of problems.
What are the limits to understanding? How are we applying data to sustainability?
Opportunities for Leverage
Data content, information design and information architecture is essential to moving from data to information to knowledge.
Tools for feedback, annotation, social interpretation of visualization
Visual sensemaking tool can be social as well as analytical
Scientific studies of perception
Data Rule (Tufte) and Emotion Rule
Observer has impact on observation – need to be more careful when observing
Reflexivity in Science, i.e., Observer effect, Role of Perceptions
Science should accept/explore paradoxes
Delay locking process as long as possible
Science plus collaboration should present a non-presumptuous step ladder to tomorrow
Look at any object as a toy – how does your relationship to it change?
[edit] INTERFACE / DESIGN
State of the Art – User Interfaces
Google “One Box”
Ubiquity
Wolfram Alpha
IBM ManyEyes
Sense.us
NY Times Visualization Lab
Chrome Browser URL Bar - Flexible, simple to use, hard to implement
Wolfram Alpha
Interactive – Allows drill down double click and roll up
Select drag and drop to filter, color, build, etc.
Realtime collaboration: mulitple users see and interact in real time
The process of the analysis, search, etc. is transparent
Documented algorithms and workflows – accessible and changeable
Magic toys to the common folk
Evaluation of doing it again
Research under the auspices of art
Games for change
Interactive visualizations
Role based needs for representation
Usability testing
Existing Challenges
Total transparency requires many readers collaborating. If the app only targets a small number of users, there’s a limit to how much data can be made transparent
Data visualization using color is easier for humans to read and think about – but visualizations could (literally) ‘color’ the perception of the problem.
State of the Art challenges include formatting data for multipurpose use, different types of visualization tools and process
Problem of biasing end user with the type of data visualization formats that UI designers choose.
Group interfaces – rooms/spaces as interfaces, data caves as early models? Group sensemaking
If the app only targets a small number of users, there is a limit to how much data can be made transparent
Standard analysis and visualization workflow - easy to change parameters and algorithms and see effects
Challenge for communicating large visualizations in small footprints (high image quality, not diffused)
Many presentations of data do not require analytical reasoning ability – and might be a repackaging of data in an easier to use (HCI)
“Export” new knowledge generated from visualization
Demography of the current viz community (many groups left out)
Managing transition from physical media to physical/digital
Group interfaces including social design, transcultural design, graphic and device design
Interface that Includes pictures linked with stories of how people affected by geography or climate
Interface that seamlessly allows for movement between policy to action level response
Supporting advanced, highly contextualized conversation
Very/too US-centric perspective
Find ways to avoid “cultural gray-out”
Symbols, metaphors are different in different cultures
Context: who? Why? Is doing the visualization
Creeping dimensionality
2D vs 3D vs 4D
Iterative
Design research
Implementing the metaphor
What is the appropriate use of technology to do something?
3D interactive navigation to help understanding
Infrastructure to do user-oriented design
Ways to represent time/process
Opportunities for Leverage
HOLODECK – large data sets, group work, haptics (tangible computing)
Force as much of your acute visual field into the small interface
User flexible “legends” (can change whole legend (colors/icons/etc. on the fly)
Cultural: nationality, gender, age, discipline
Appropriate use of the tools
Design for exploration; for preliminary finding
Perceptual simulation
Biosemiotics
Holistic science
[edit] DATA
State of the Art – Sharing/Accessing Data
Social context for data collection/sharing (i.e., Manyeyes, NY Times Visualization Lab)
Indiana University’s Scholarly Database for science citations data (CNSC, SLIS)
OpenStreetMap crowdsourced data
Google Earth crowdsourced data (i.e., Open Source KML library)
World Resources Institute (WRI)
GEON Grid Cyberinfrastructure for Earth Science Data
Existing Challenges
What is the role of data?
Classification systems may distort data – info – knowledge
Are dreams of the Linked Web / Semantic Web impossible?
BIAS of classification and conformation
Need a discipline for data curation
Each dataset is acquired for certain purpose – need to address purpose
There is no neutral data
There are no strategies to even approach highly politicized data (e.g., peak oil)
There is no unbiased source of data in a politicized issue like peak oil
No data was gathered without some assumptions. What was the interest of the gatherers?
Cost of accessing raw datasets, moving data, cleaning the data
Data needs context (ex. Web MD vs Medical Social Network)
Without a legend and “signed” data, visualization becomes eye candy
Expert vs Lay [knowledge]
What is the role of expertise in reducing bias in data?
How do we preserve the social nature of data?
Significant amounts of manual data handling
Coding of data is important to understanding how that data might be later used. As an example – DNA data is coded to help it be used in a variety of end user purposes. Many scientists are DIY data visualizers.
Opportunities for Leverage
Million minds approach to data generation/acquisition
Safety in numbers re: interpreting data
Make data acquisition process explicit and transparent
Have question first, then select the best data
Process vs Ontology
Diversity - “informal representation” as correctives?
Heterogeneous classification systems
New semantic search capabilities, ontologies and computational knowledge engines will be served by data viz as navigation interfaces (Freebase, Twine, Open Calais, WolframAlpha, Bing Decision Engine)
[edit] Leaders
Jeffrey Heer, Bonnie DeVarco, Katy Borner
BONNIE DEVARCO is an interdisciplinary researcher, writer and curator and a Media X Distinguished Visiting Scholar. With an academic background in cultural anthropology, dance ethnology and archives management, she writes and lectures on Design Science, virtual worlds, next generation geographic information systems, information visualization and the culture of cyberspace. She has served as an education technology consultant to non-profit, corporate and educational organizations for the past 20 years (including PBS, AIANY Center for Architecture, San Diego and Imperial County Boards of Education, James Burke's Knowledge Web, UC Santa Cruz, UCOP, the Buckminster Fuller Institute). She helped develop multi-institutional programs for distance and media enhanced learning for the University of California Office of the President and served as research and development consultant for the UC College Prep Initiative (UCCP), one of the first statewide virtual high school programs 1998-2003. Bonnie serves on a variety of advisory boards, including Places & Spaces - Mapping Science International Exhibition series and the Buckminster Fuller Challenge Prize. She served as archivist for the Buckminster Fuller collection from 1989-1995 and is completing a book on Fuller titled Invisible Architecture II. She is currently co-authoring Shape of Thought, on the history and evolution of visual language with Eileen Clegg and is co-editing a book on ludic cartographies with Matteo Bittanti and Henry Lowood of Stanford University.
http://scaleindependentthought.typepad.com
JEFFREY HEER is Assistant Professor, Computer Science at the Human-Computer Interaction Lab at Stanford University. His research interests include studying human-computer interaction, visualization, and social computing. He is author of the prefuse and flare toolkits for interactive visualization and previously worked at (Xerox) PARC, Microsoft Research, IBM Research, and Tableau Software.
http://jheer.org
KATY BÖRNER is the Victor H. Yngve Professor of Information Science at the School of Library and Information Science, Adjunct Professor in the School of Informatics, Core Faculty of Cognitive Science, Research Affiliate of the Biocomplexity Institute, Fellow of the Center for Research on Learning and Technology, Member of the Advanced Visualization Laboratory, and Founding Director of the Cyberinfrastructure for Network Science Center (http://cns.slis.indiana.edu) at Indiana University. She is a curator of the Places & Spaces: Mapping Science exhibit (http://scimaps.org). Her research focuses on the development of data analysis and visualization techniques for information access, understanding, and management. She is particularly interested in the study of the structure and evolution of scientific disciplines; the analysis and visualization of online activity; and the development of cyberinfrastructures for large scale scientific collaboration and computation. She is the co-editor of the Springer book on ‘Visual Interfaces to Digital Libraries’ and of a special issue of PNAS on ‘Mapping Knowledge Domains’ (2004). Her new book ‘Atlas of Science: Guiding the Navigation and Management of Scholarly Knowledge’ published by MIT Press will become available in 2010. She holds a MS in Electrical Engineering from the University of Technology in Leipzig, 1991 and a Ph.D. in Computer Science from the University of Kaiserslautern, 1997.
http://www.scimaps.org http://cns.slis.indiana.edu http://www.scimaps.org
[edit] Invited Presenters
EILEEN CLEGG is a visual journalist, book author and founder of the company Visual Insight, creating large-scale, real-time murals for organizations. She invokes visual language to wordlessly capture the ideas, intuition and shared vision of groups--combining contemporary reporting techniques with ancient, universal symbols. Clients have included Art Center College of Design, IBM, O'Reilly Media, American Society of Training and Development, and the Gates Foundation's Model Secondary Schools Program. Eileen was a daily newspaper journalist for many years before joining Institute for the Future in 1999, where large-scale graphics were used in futures forecasting. She developed her unique visual journalism approach in 2001. Publications include: Claiming Your Creative Self (New Harbinger 1999), the Corporate University Workbook (Jossey Bass Pfeiffer 2005) and most recently Evolving Collective Intelligence with Doug Engelbart and Valerie Landau (NextNow Collab Press 2008). She is working on a book documenting The Visual Insight Process, and collaborating with Bonnie DeVarco on a book about the history and evolution of visual language, Shape of Thought.
http://www.visualinsight.net
WALTER W. POWELL is Professor of Education and (by courtesy) Sociology, Organizational Behavior, Management Science and Engineering, and Communication at Stanford University. He is also an external faculty member at the Santa Fe Institute. He is co-director of the Stanford Center on Philanthropy and Civil Society. He joined the Stanford faculty in July 1999, after previously teaching at the University of Arizona, MIT, and Yale. He has been a fellow at the Center for Advanced Study in the Behavioral Sciences three times, and a visiting fellow at the Institute for Advanced Studies in Vienna twice. Powell has received honorary degrees from Uppsala University, the Helsinki School of Economics, and Copenhagen Business School, and is a foreign member of the Swedish Royal Academy of Sciences. He is a U.S. editor for Research Policy, and has been a member of the board of directors of the Social Science Research Council since 2000. Professor Powell's full biography is available online at Stanford University. http://www.stanford.edu/~woodyp/
ALEX SOOJUNG-KIM PANG is a futurist and historian of science. He is an Associate Fellow at the Saïd Business School at Oxford University, where he works with students interested in strategy, technology and organizations, a Visiting Scholar in Stanford University's History and Philosophy of Science program, and director of Future2.org, a nonprofit startup. Previously he was Managing Editor of the Encyclopedia Britannica, where he oversaw its transition from printed to electronic publication, and was a Research Director at the Institute for the Future (IFTF), a Silicon Valley think-tank. Alex is a specialist on the history and future of visualization technologies and science, and is author of numerous articles on 19th and 20th century scientific visualization. http://askpang.typepad.com/
JON CHRISTENSEN has been an environmental journalist and science writer for 21 years. His work has appeared in The New York Times, western regional newspaper High Country News, and many other newspapers, magazines, journals, and public radio and television shows. Jon was a Knight Professional Journalism Fellow at Stanford in 2002-2003 and a Steinbeck Fellow at San Jose State University in 2003-2004. He is now finishing his Ph.D. in the Department of History at Stanford and is associate director of the Spatial History Project of the Bill Lane Center for the American West. His dissertation, “Critical Habitat,” is a history of ideas, narratives, science, land use change, and practices of conservation and extinction of a species in time and space. His broader research and teaching interests include environmental history, natural history and the history of biological and ecological sciences, climate change, conservation, western history, and the history of journalism.
http://stanford.edu/~jonallan/ http://spatialhistory.stanford.edu
DAVID MCCONVILLE is a media artist and theorist whose work explores the interplay between perceptual immersion, transcalar visualizations, contemporary cosmograms, ecological dynamics, and reflexive awareness of the processes of worldview construction. He is co-founder of The Elumenati, a design and engineering firm that integrates immersive environments, interactive narratives, and real-time data visualizations to create custom installations for clients ranging from art festivals to space agencies. He is currently developing historical and cognitive frameworks for his work with dome-based environments as a PhD candidate in the Planetary Collegium (http://www.planetary-collegium.net). He is on the Board of Directors of the Buckminster Fuller Institute, collaborating with a global network of design scientists developing solutions that comprehensively address the world's most pressing challenges.
http://www.elumenati.com http://www.bfi.org
[edit] Topics
[edit] Overview
This highly visual, action-centered Media X Collaboratory will bring together visualization vanguards from the leading edge of science mapping, collaborative visual sensemaking, social network analysis and the emerging semantic web. The collaboratory will bring together visual approaches from the World Café process and unconference strategies to encourage rapid action networking amongst participants. The Shape of Thought and Visual Insight mural process will support visual brainstorming and documentation throughout the workshop to create a realtime “map” to the new territories presented.
Surrounded by the Places & Spaces: Mapping Science Exhibition at Wallenberg Hall and dynamic maps from Stanford’s Spatial History Project and the Human-Computer Interaction Lab, visual thinkers from four departments on campus, designers and special guests will explore a series of case studies of their work to gain a synthetic perspective on the future of visualization for connective intelligence. New cyberinfrastructures of scholarly data, network analysis and visualization tools will be presented along with novel approaches to data sharing from the social semantic web.
COLLABORATORY GOALS
The goal of this collaboratory is to catalyze multi-institutional research projects involving the visualization of scholarly data, design science strategies and innovative sustainability networks. Discussions will center around:
- understanding the history of science mapping and forecasting the future of the visualization of knowledge
- exploring design tools that facilitate distributed knowledge sharing and collaboration
- identifying optimum user interface design approaches for collaboration and access between institutions, disciplines, academia and the general public
- exploring cyberinfrastructures and plug-and-play macroscopes to navigate and synthesize large bodies of networked data
[edit] Agenda
DAY 1 August 12 - Mapping the Challenges
8:30 Arrival, Registration, Continental Breakfast
9am Welcome by Workshop Leaders (Jeff Heer, Bonnie DeVarco, Katy Borner)
9:15 Collaboration Dynamics Overview, Card/Mural Process intro (Eileen Clegg, Bonnie DeVarco)
9:30 Participant Intros – Visioning Mural - 2 min each (goals, visions, challenges captured visually)
11:30 All participants interact with, discuss and add cards to extend mural (will remain active throughout workshop)
Noon LUNCH BREAK
1:00 Bonnie DeVarco - Shape of Thought Deep History (mural will be presented)
1:30 Jeff Heer – A Brief History of Information Visualization and Collaborative Visual Sensemaking
2:00 Katy Borner – A Brief History of Science Mapping (large timeline will be presented)
2:30 WORLD CAFÉ #1 Visual Brainstorming (separate into smaller groups, change rooms every 30 min.) Eileen Clegg, Bonnie DeVarco introduce process
TOOLS - Hardware/Software
PHILOSOPHICAL CONCEPTS
INTERFACES/DESIGN
ISSUES/CHALLENGES
4:30 Report Out on Breakouts (mural captured)
5:00 ADJOURN for Dinner
7:00pm - 9:00pm Evening Reception
Places & Spaces: Mapping Science Guided Tour with Katy Borner, Andre Skupin, Sarah Williams
Stanford University's Spatial History Project Lab Tour with Jonathan Christensen
DAY 2 August 13 - Case Studies and Collaborations' 9:00 Ecology of Tools & Discovery Process Jeff Heer
9:30 Plug-and-Play Macroscopes Katy Borner
10:00 Open Demos - Big Screen and laptop
11:00 “Second Best Idea” exercise - (Katy Borner introduces)
11:50 Case Study Introductions (10 min. each)
Case Studies:
Mapping the Structure of Sustainability Science Research
Visualizing Sustainability Innovation Networks
Visualizing Eco-history for Conservation Planning
Collaboration Ecosystems for Emerging Industries
12:30 LUNCH BREAK
1:30 Mapping Innovation Networks - Woody Powell
2:30 WORLD CAFÉ #2 – Working group Sessions: Case-Studies (separate into smaller groups – change rooms every 30 minutes Bonnie DeVarco, Jeff Heer, Katy Borner lead
3:00 change
3:30 change
4:00 Report out – Mural captured - Mural walkthrough and Collaborative Synthesis Eileen Clegg
5:15 ADJOURN (dinner on or off campus - 3 rotating groups for immersive visualizations in the GeoDome)
6:00 - 8:00pm Transcalar Imaginary - Guided Journeys in the GeoDome with David McConville (in three groups)
DAY 3 (half day) August 14 Reflections, Connections, Convergences
8:30 arrival, continental breakfast
9:00 Bonnie DeVarco, Eileen Clegg - Reflections, Connections, Convergences (condensed brainstorming mural process)
10:00 Funding ideas, Partnerships – Katy Borner, lead
10:30 BREAK
10:45 The Future of Visualization - 10 Year Forecast - Trends (Interactive Timeline exercise in PREZI) Alex Soojung-Kim Pang
12:15 ADJOURN
[edit] ATTENDEES
Attendees:
Bonnie DeVarco, Media X, Stanford University, Palo Alto, CA
Jeffrey Heer, HCI, Stanford, Palo Alto, CA
Borner Katy Indiana University, Bloomington, IN
Clegg Eileen, - Visual Insight Bodega Bay, CA
Alex Soojung Kim Pang, Presenter - Stanford Universityy Palo Alto, CA
Woody Powell - Stanford University 13, 14 Palo Alto, CA
Jon Christensen - Associate Director, Spatial History Project Palo Alto, CA
David McConville – Buckminster Fuller Challenge, ELumenati, Asheville, NC
Aaron Koblin – Presenter, Experimental Labs, Google
Johan Bollen - Indiana University, Los Alamos Labs
Amanda Cravens - Spatial History Project Palo Alto, CA
Ruth Askevold - SFEI - San Francisco Estuary Institute Oakland, CA
Graham Creasey - Stanford University Palo Alto, CA
Steven Rose - Orange Labs, San Francisco, CA
Vellakal Asha - Orange Labs, San Francisco, CA
Wencheng Li - Orange Labs, San Francisco, CA
Eric Steiner – Director, Spatial History Lab, Stanford University, Palo Alto, CA
Neil Rubens - University of Electro-Communications San Francisco, CA
Kathy Sullivan - Battelle Center for Science and Education Policy, Ohio State Univ. Ohio
Courtney Heppner - Battelle Center for Science and Education Policy, Ohio State Univ. Ohio
Brian Kritzstein - Battelle Center for Science and Education Policy, Ohio State Univ. Ohio
Dave Augustine - Research & Technology
Harry Blount - The Tech San Jose, CA
Nicole Coleman - Stanford Humanities Lab, Palo Alto CA
Matteo Bittanti - Stanford Humanities Lab, Palo Alto, CA
Susan Rojo - Stanford Humanities Lab, Stanford Palo Alto, CA
Walczyk David – Pratt Institute and Buckminster Fuller Challenge, New York, CA
Koblin Aaron – Google Creative Lab, SF, aaronkoblin.com, San Francisco, CA
Skupin Andre P&S - San Diego State University San Diego, CA
Schales Paula – Software Engineer, Artist
Cormia Robert - Foothill College, Los Altos
Alexandra Carmichael – Cure Together San Francisco, CA
Jack Park, Open University Palo Alto, CA
Martha Russell Media X Assoc. Dir. Media X, Stanford University Palo Alto, CA
Charles House, Media X Exec Dir. Media X, Stanford University Palo Alto, CA
Douglass Carmichael – Media X Distinguished Visiting Scholar, Stanford University, Palo Alto
Ted Kahn, Design Worlds for Learning, Media X Distinguished Visiting Scholar, Stanford University
David Nordfors, Stanford Research Center of Innovative Journalism, Stanford University
[edit] ACKNOWLEDGMENTS
Special Thanks to:
Media X Summer Institute Directors: Martha Russell, Charles House
Wallenberg Hall Facility & Logistics Support: Adelaide Dawes
Video Documentation: Bob Smith and John Kelly
Photographic Documentation, Bill Daul
Scribes & Tweeters: Robert Cormia & Paula Schales
On Site Volunteers: Jack Park, Alexandra Carmichael, Marikka Rypa, Seana McNamara
Collaboratory Documentation Web Page Development: Bonnie DeVarco, Katy Borner, Elisha Hardy
Sponsorship, Support
This collaboratory was made possible by the generous support of the following:
• The H-Star Institute and Media X http://mediax.stanford.edu
• The Buckminster Fuller Institute & the Buckminster Fuller Challenge Prize http://challenge.bfi.org
• The Human-Computer Interaction Lab, Stanford University http://hci.stanford.edu
• The Spatial History Project, Stanford University http://spatialhistory.stanford.edu
• Tooling Up for Digital Histories, Presidential Fund for Innovation in the Humanities, Stanford University, a collaboration between the Spatial History Project and the Computer Graphics Lab.
• The Cyberinfrastructure for Network Science Center at Indiana University http://cns.slis.indiana.edu
• National Science Foundation under Grant No. IIS-0715303 http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0715303
In Kind Contributions:
• Elumenati http://www.elumenati.com
• Places & Spaces: Mapping Science http://www.scimaps.org
• Shape of Thought http://www.shapeofthought.typepad.com
• Visual Insight http://www.visualinsight.net
NOTE
- Opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
