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InfoVis CyberInfrastructure Katy Börner School of Library and Information Science katy@indiana

InfoVis CyberInfrastructure Katy Börner School of Library and Information Science katy@indiana.edu Presentation at InfoVis 2004, London, UK July 15 th , 2004. http://iv.slis.indiana.edu/sw. http://iv.slis.indiana.edu/db. http://iv.slis.indiana.edu/cr. http://iv.slis.indiana.edu/lm.

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InfoVis CyberInfrastructure Katy Börner School of Library and Information Science katy@indiana

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  1. InfoVis CyberInfrastructure Katy Börner School of Library and Information Science katy@indiana.edu Presentation at InfoVis 2004, London, UK July 15th, 2004

  2. http://iv.slis.indiana.edu/sw http://iv.slis.indiana.edu/db http://iv.slis.indiana.edu/cr http://iv.slis.indiana.edu/lm

  3. Motivation • Support developers and programmers in the comparison and distribution of new algorithms. • Support (non-programmer) users in the utilization of advanced InfoVis algorithms. • Interconnect algorithm developers and users. What algorithms do users need/want? • Provide a unique resource for InfoVis research and education. • Support ‘Knowledge Domain Visualization’ research. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  4. Related Research • InfoVis Toolkit by J.-D. Fekete • Prefuse by J. Heer, S. Card, James A. Landau • Universal Visualization Platform by G. Grinstein • Piccolo/Jazz by B. Bederson • GraphViz by S. North • JUNG by S. White • Tulip by D. Auber • GeoVista by M. Gahegan, Alan McEachren • Common GIS by Natalia and Gennady Andrienko • VTK Toolkit • IBM OpenDX What focus should a InfoVis Toolkit have? • Fekete’s Toolkit is well suited for the design and customization of complex visualizations (multiple windows, search, etc.) • IVC supports the combination/pipelining of data analysis & visualization algorithms. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  5. http://iv.slis.indiana.edu/sw http://iv.slis.indiana.edu/db http://iv.slis.indiana.edu/cr http://iv.slis.indiana.edu/lm

  6. IVC Oracle DB and Search Engine The Team Design and Implementation Jay Askren Saiful Bahari Andrew Bangert Christopher Friend Stephanie Gato Todd Holloway (Lead) Ruchi Kapoor Ketan Mane Lalitha Visvanath Qian Wang Data Experts Daniel O. Kutz Elijah Wright Graphic Design Caroline Courtney Project Start September 2003 Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  7. IVC DB System Overview Oracle/Apache/Tomcat/Java—Well understood and reliable tools DB features • Potentially one terabyte of data in flat files • Relational design • Allow for more collections to be added Search engine • Search on abstract, author, title, journal, date published, and more • User login for both Indiana University (IU) and non-IU users • User histories • Administration of data and user accounts • Compressed downloading of results • Term-by-document and co-author matrices of results Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  8. IVC DB Data Sets Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  9. http://iv.slis.indiana.edu/sw http://iv.slis.indiana.edu/db http://iv.slis.indiana.edu/cr http://iv.slis.indiana.edu/lm

  10. http://iv.slis.indiana.edu/sw http://iv.slis.indiana.edu/db http://iv.slis.indiana.edu/cr http://iv.slis.indiana.edu/lm

  11. IVC Software Framework The Team Master Minds/Programmers Jason Baumgartner, SLIS Nathan James Deckard, CS Nihar Sheth, Informatics Bruce William Herr, CS Shashikant Penumarthy, SLIS Graphic Design Caroline Courtney, Fine Art Project Start 2001 Algorithm Development and Integration Vivek Agrawal, Summer Intern Renee LeBeau, SLIS Josh Bonner, CS Todd Holloway, CS Jeegar Maru, CS Laura Northrup, CS Sriram Raghuraman, CS Nihar Sanghvi, Informatics Hardik Sheth, Informatics Sidharth Thakur, CS Ning Yu, SLIS Yuezheng Zhou, CS Students taking K. R. Subramanian’s (UNC Charlotte) InfoVis class integrated diverse algorithms into the IVC. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  12. IVC Software Framework Web Site: http://iv.slis.indiana.edu/sw Jason Baumgartner, Katy Börner, Nathan J. Deckard, Nihar Sheth. An XML Toolkit for an Information Visualization Software Repository. Poster Compendium, IEEE Information Visualization Conference, pp. 72-73, 2003. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

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  21. IVC Software FrameworkDocu is at http://iv.slis.indiana.edu/sw ANALYSIS ALGORITHMS generate models from parsing other data structures and/or processing on the data LAYOUT ALGORITHMS run graphical processes on the appropriate model DATA MODEL PERSISTENCE factory to persist a model to a particular data store (i.e. XML format, database) STANDARD MODEL INTERFACES based on Java 2 Swing standard models CODE INTEGRATION new algorithms can be integrated easily by supporting one or more of the models Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  22. Framework can run different data analysis and IV algorithms on a standard set of input data formats (tree, matrix, network, table, list). • Models from the algorithms can be serialized through the persistence layer; and it is generic enough for plugging in various persistence options (XML, SQL database, etc). • Based on Model-View-Controller (MVC) by focusing on standard data model interfaces for data exchange. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  23. Demo IVC Software Framework Download from http://iv.slis.indiana.edu/sw/ (code is hosted at Sourceforge.net) CD contains • Readme.txt • 04-iv-ivc.ppt (this slide show) • IVC-www (web pages available via http://iv.slis.indiana.edu/) • IVC-source (IVC source code, needs to be compiled using ant) • IVC-build (contains an executable jar file and sample data) Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  24. Run the IVC Software Framework Copy CD content to harddrive In ‘/IVC-build’ double click ‘ivc.jar’ to open the window below Use menu system to • Load or simulate a data set. • Analyze, visualize, or interact with a data set. • To start a toolkit. • To access code reference pages, learning modules, javadoc, get updates, etc. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  25. Whenever an algorithm is selected, the user receives feedback on what algorithm was run, what parameters were used, any textual results, who developed this algorithm, etc. The amount of feedback can be customized. In addition, a log file is generated as a permanent track of all user actions. Each loaded/simulated data set is internally stored as a data model. All data models of a session are listed on the right hand side. Right click a model to rename it. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  26. Only algorithms that can be used with a selected data model are selectable (all others are grayed out).* *The black shown network visualizations are prefuse demo’s that do not (yet) use the IVC data modules but require their own data format. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  27. Currently Available Algorithms Data Modeling • P2P network modeling and search algorithms • - Structured P2P Systems (Content-Addressable Network Model (CAN) , Chord Model) • - Unstructured P2P System (PRU Model, Hypergrid Model) • TARL model for the co-evolution of author-paper networks Data Analysis • General Search Algorithm – Breadth First Search, k-Random Walk Search • CAN Search Algorithm, Chord Search Algorithm Visualization • JUNG network layout algorithms • Prefuse demos Interaction • Prefuse demos Toolkits • AW toolkit In Sept 2004, most of the algorithms at http://iv.slis.indiana.edu will be integrated, see menu.ini. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  28. Sample Exercises • Compare search time for structured and unstructured P2P networks • Generate P2P network models of similar size, run search algorithms, compare results. • Compare different network simulation/layout algorithms • Load/generate a network data set, visualize it using JUNG network layouts. • Run prefuse visualizations • Learn about different interaction algorithms (prefuse code, data is pregiven). • Use the IVC to run a toolkit. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  29. Prefuse Visualizations Ballon Tree: load /sampledata/prefuse/chitest.hdir TreeMap Demo: load /sampledata/prefuse/chitest.hdir Zoom -> right mouse button Radial Graph: load /sampledata/prefuse/friendster.xml or /sampledata/prefuse/terror.xml Force Demo (data is pregiven) Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  30. Interaction (prefuse code) Distortion Fisheye View Zooming Pan Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  31. ActiveWorld Toolkit From sampledata/activeworldtoolkit • Load mapper.ini (toolkit initialization file) • Load Propdump culture.dump (‘Culture’ is a world in the ‘Quest Atlantis’ universe of virtual worlds) • Load Registry questatlantis.reg (the Quest Antlantis universe has one registry) Checkmark Objects, Links, Teleports to display those. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  32. Load users culture.log (via Users > Load User Data) • Select users • Check Trails Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  33. Extend the IVC Software Framework Read the ‘IVC Software Framework Programmer Manual 0.1’ in /IVC-www/sw/papers/ivc-framework.doc Table of Contents 1 Introduction 2 Target Audiences 3 Major Design Decisions 4 Plug-In Based Software Architecture 4.1 Core 4.2 Data Models 4.3 Persistence 4.4 Graphical User Interface 4.5 Plug-Ins 5. Extending the IVC 5.1 Integrating New Algorithms 5.2 Writing New Persisters 5.3 Integrating Toolkits 6. Conclusions Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  34. Steps to integrate a new algorithm • Clean up the code and document it well. • Check if the IVC persistence layer satisfies your data storing and loading requirements (if not goto 5.2). • Implement the Plugin interface (visualization, java code) Two choices: (I) Build visualization window, return it to the IVC using getView method of the Plugin. (II) If your visualization uses a top-level GUI Container then start your visualization as a separate window and return null to the IVC. • Use java jar utility and archive your files including your plugin implementation and place it in the plugins folder. Put only java .class files in this jar. Put the other files at the same or lower level in the directory structure and make sure this is how you refer to your files within the code. Test your plugin to see that everything works. • Zip up or make a tar ball of all your files including non-java code. Now your algorithm is available to anyone who has the IVC. Anyone can download your zip file, unzip it in their plugins folder and the algorithm is immediately available. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  35. http://iv.slis.indiana.edu/sw http://iv.slis.indiana.edu/db http://iv.slis.indiana.edu/cr http://iv.slis.indiana.edu/lm

  36. IVC Learning Modules Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  37. Visualizing Tree Data http://iv.slis.indiana.edu/lm/lm-trees.html Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  38. Student’s Project Results User & Task Analysis for Visualizing Tree Data • Visualizing the structure of IU’s Decision Support System • Visualizing the co-occurrences of keywords in DLib Magazine articles. • Visualization of the Java API • Visualizing the Library of Congress Classification System to retrieve legal materials in a library. See Handin pages at http://ella.slis.indiana.edu/~katy/ handin/L579-S04/cgi/handinlogin.cgi Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004. Image by Peter Hook and Rongke Gao

  39. Validation: Teaching InfoVis using the Learning Modules Time Series Analysis & Visualization http://iv.slis.indiana.edu/lm/lm-time-series.html Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  40. Student’s Project Results Time Series Analysis & Visualization • Using Timesearcher and the Burst Detection Algorithm to Analyze the Stock Market from 1925 to 1945 • Applying Burst and TimeSearcher to Chat Data • Lab Access Trends • Quest Atlantis Chat Log Data See Handin pages at http://ella.slis.indiana.edu/~katy/handin/L579-S04/cgi/handinlogin.cgi Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  41. Visualizing the Work of the United States Supreme Court Based on Time Data and Top Level West Topics by Peter A. Hook & Rongke Gao Top fifteen most occurring topics from 1944 to 2004 in Timesearcher All topics grouped by West Category and Sub-Category grouped over the entire lengths of the data set Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004. All topics by West Category and Sub-Category grouped corresponding to the five chief justices

  42. Visualizing niches of the blog universe. Visualizing Niches of the Blog Universe BY Mike Tyworth and Elijah Wright Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  43. Future Work This summer, more data modeling, data analysis and visualization algorithms will be integrated into the IVC. Hope many of you will contribute to the IVC via Sourceforge http://sourceforge.net/projects/ivc. A programmer-friendly Java API that allows researchers to pipeline data between analysis algorithms and visualization tools within and outside the IVC will be implemented. Algorithm documentation and the learning modules set will be updated/expanded. We plan to have demos/tutorials on the InfoVis CyberInfrastructure at the - InfoVis Conference 2004 in London, UK, July 14-16. - IEEE InfoVis Conference 2004 in Austin, Texas, Oct 10-12. - Visualization and Data Analysis Conf. 2005 in San Jose, CA, Jan 17-18. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

  44. Acknowledgements Craig A. Stewart, Mary Papakhian, Anurag Shankar all UITS generously made the Research Database Complex available for this project and provided very insightful comments. Stephanie Burks, Principal Unix Systems Administrator, Research and Technical Services, UITS has been instrumental in setting up the computing infrastructure and administration of the Oracle database. Algorithm developers and integrators are acknowledged in the code documentation. Katy Börner: InfoVis CyberInfrastructure, InfoVis Conference 2004.

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