Spatiotemporal Knowledge Visualization and Discovery in Dynamic Social Networks  Ralf Klamma,  Yiwei Cao , Marc Spaniol, Y...
Agenda <ul><li>Introduction </li></ul><ul><ul><li>Motivation </li></ul></ul><ul><ul><li>Scenario </li></ul></ul><ul><li>Re...
Introduction:  Visualization <ul><li>Spatiotemporal knowledge visualization </li></ul><ul><ul><li>Main tasks of geographer...
Motivation <ul><li>“ Structural Bias”  (Milgram, 1967) </li></ul><ul><li>Lack of means of spatiotemporal knowledge visuali...
Scenario <ul><li>Interoperability </li></ul><ul><li>User’s interactions </li></ul><ul><li>Unified toolkits </li></ul>Dynam...
Related Work: Features of Social Networks <ul><li>Spatiotemporal Data in  Social Networks  </li></ul><ul><ul><li>Geographi...
Social Network Visualization <ul><li>503 projects at  www.visualcomplexity.com   </li></ul><ul><li>6359 people bookmarks t...
Spatiotemporal Knowledge Visualization <ul><li>Temporal visualization </li></ul><ul><ul><li>Animation layout for node-link...
Spatiotemporal Knowledge Visualization Languages in Social Networks  <ul><li>Temporal visualization </li></ul><ul><ul><li>...
DyVT: System Concepts Relational data Temporal data Geospatial data Appearance data DyVT XML-based Target Language (DyVTML...
System Concepts to  3-Tier Architecture Relational data Temporal data Geospatial data Appearance data DyVT XML-based Targe...
3-Tier Architecture Intertier  data   flow Intra-tier   data   flow Legend Data Processing Tier Database Tier Visualizatio...
Database Tier :  Social Network Data <ul><li>Spatial data </li></ul><ul><ul><li>Spatial database </li></ul></ul><ul><li>Te...
Data Processing Tier :  DyVTML Geospatial data Appearance data ADML Temporal data Temporal data Mailing list data
Data Processing Tier :  Social Network Appearance Data <ul><li>Graphic setting interface </li></ul><ul><li>XML based ADML ...
Visualization Tier:  Layout Algorithms <ul><li>Circle Layout </li></ul><ul><li>KK Layout </li></ul><ul><li>Set the radius ...
Spatiotemporal Knowledge Visualization <ul><li>Mailing list visualization based on Google Maps </li></ul>
Conclusions <ul><li>DyVT </li></ul><ul><li>DyVTML(ADML) </li></ul><ul><li>Animation </li></ul><ul><li>Maps </li></ul>T Tem...
Outlook <ul><li>Interchange Formats </li></ul><ul><li>Multi-relational social  </li></ul><ul><li>networks </li></ul><ul><l...
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Spatiotemporal Knowledge Visualization and Discovery in Dynamic Social Networks

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Spatiotemporal Knowledge Visualization and Discovery in Dynamic Social Networks
Ralf Klamma, Yiwei Cao, Marc Spaniol, Yan Leng
Graz, Austria, 5-7 of September, 2007
Informatik 5, RWTH Aachen University, Germany

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  • Spatiotemporal Knowledge Visualization and Discovery in Dynamic Social Networks

    1. 1. Spatiotemporal Knowledge Visualization and Discovery in Dynamic Social Networks Ralf Klamma, Yiwei Cao , Marc Spaniol, Yan Leng Graz, Austria, 5-7 of September, 2007 Special Track on Knowledge Visualization and Knowledge Discovery (KVD ’07 at i-know) Informatik 5, RWTH Aachen University, Germany
    2. 2. Agenda <ul><li>Introduction </li></ul><ul><ul><li>Motivation </li></ul></ul><ul><ul><li>Scenario </li></ul></ul><ul><li>Related work </li></ul><ul><ul><li>Social networks and visualization </li></ul></ul><ul><ul><li>Spatiotemporal knowledge visualization languages </li></ul></ul><ul><li>DyVT: Dynamic Social Network Visualization Tool </li></ul><ul><ul><li>System concepts </li></ul></ul><ul><ul><li>3-Tier architecture </li></ul></ul><ul><li>Conclusions and outlook </li></ul>
    3. 3. Introduction: Visualization <ul><li>Spatiotemporal knowledge visualization </li></ul><ul><ul><li>Main tasks of geographers and cartographers (Andrienko, 2006) </li></ul></ul><ul><li>Social network visualization </li></ul>Source: Touchgraph Facebook Browser, TouchGraph LLC, 2007 Source: “A technique for spotting connections” NYTimes, Feb. 25, 2006.
    4. 4. Motivation <ul><li>“ Structural Bias” (Milgram, 1967) </li></ul><ul><li>Lack of means of spatiotemporal knowledge visualization of rich dynamic information </li></ul><ul><ul><li>Temporal attributes </li></ul></ul><ul><ul><li>Geospatial attributes </li></ul></ul><ul><li>Limited interchange formats for social network data </li></ul><ul><ul><li>Text-based formats (UCINET DL, Pajek .net…) </li></ul></ul><ul><ul><li>XML-based formats (GraphML, DynetML…) </li></ul></ul><ul><li>Few options or controls by end users </li></ul>
    5. 5. Scenario <ul><li>Interoperability </li></ul><ul><li>User’s interactions </li></ul><ul><li>Unified toolkits </li></ul>Dynamic distributed social network data How to visualize complex dynamic social network data? Appearance Data Geospatial Data Temporal Data Relational Data How to interoperate social network data?
    6. 6. Related Work: Features of Social Networks <ul><li>Spatiotemporal Data in Social Networks </li></ul><ul><ul><li>Geographic distribution </li></ul></ul><ul><ul><li>Dynamic change by time </li></ul></ul><ul><li>Common features </li></ul><ul><li>Social network analysis ( Brandes & Erlebach, 2005 ) </li></ul>Emails, Mailing lists, Forums, Blogs, Wikis, ...
    7. 7. Social Network Visualization <ul><li>503 projects at www.visualcomplexity.com </li></ul><ul><li>6359 people bookmarks this link (as of Sep.4, 2007) </li></ul><ul><li>Complexed results </li></ul>Most Visited Projects: Windows vs Linux Server (2006) The Strengths of Nations (2006) Data Visualisation of a social network (2007) Neuronal Network (2006) Mammal Supertree (2007) Hierarchical Edge Bundles (2006) A Networked Designer‘s Critical Path (2004) Visualization of Blogspace (2003) New York Subway Map (1972) Structural Bias?
    8. 8. Spatiotemporal Knowledge Visualization <ul><li>Temporal visualization </li></ul><ul><ul><li>Animation layout for node-link graphs (Erten et al. 2005) </li></ul></ul><ul><ul><li>Readability and mental map preservation </li></ul></ul><ul><li>Geospatial visualization </li></ul><ul><ul><li>Spatial data collecting, sharing and analyzing </li></ul></ul><ul><ul><li>Web map services (Google, 2007) </li></ul></ul><ul><li>Personalized visualization </li></ul><ul><ul><li>User preference and customization </li></ul></ul><ul><ul><li>To visualize: icons, sizes, colors, weight, etc. (Krempel, 2005) </li></ul></ul>
    9. 9. Spatiotemporal Knowledge Visualization Languages in Social Networks <ul><li>Temporal visualization </li></ul><ul><ul><li>Animation layout for node-link graphs </li></ul></ul><ul><ul><li>Readability and mental map preservation </li></ul></ul><ul><li>Geospatial visualization </li></ul><ul><ul><li>Spatial data collecting, sharing and analyzing </li></ul></ul><ul><ul><li>Web map services </li></ul></ul><ul><li>Personalized visualization </li></ul><ul><ul><li>User preference and customization </li></ul></ul><ul><ul><li>To visualize: icons, sizes, colors, weight, etc. </li></ul></ul>DyNetML: dynamic network data as sets of time slices KML: used by Google Earth and Google Maps GraphML: published and well-supported Metadata interoperability Integration
    10. 10. DyVT: System Concepts Relational data Temporal data Geospatial data Appearance data DyVT XML-based Target Language (DyVTML) Multi-media data types Animation Mashup views Map view SVG GIF JPEG
    11. 11. System Concepts to 3-Tier Architecture Relational data Temporal data Geospatial data Appearance data DyVT XML-based Target Language (DyVTML) Multi-media data types Animation Mashup views Map view SVG GIF JPEG Database tier Data processing tier Visualization tier
    12. 12. 3-Tier Architecture Intertier data flow Intra-tier data flow Legend Data Processing Tier Database Tier Visualization Tier
    13. 13. Database Tier : Social Network Data <ul><li>Spatial data </li></ul><ul><ul><li>Spatial database </li></ul></ul><ul><li>Temporal data </li></ul><ul><li>Social network data </li></ul><ul><ul><li>Mailing lists </li></ul></ul><ul><ul><li>BBS/Forums </li></ul></ul><ul><ul><li>Weblogs </li></ul></ul><ul><ul><li>Social bookmarks </li></ul></ul><ul><ul><li>Other multimedia social networks (music, pictures, videos …) </li></ul></ul>
    14. 14. Data Processing Tier : DyVTML Geospatial data Appearance data ADML Temporal data Temporal data Mailing list data
    15. 15. Data Processing Tier : Social Network Appearance Data <ul><li>Graphic setting interface </li></ul><ul><li>XML based ADML format </li></ul>XML Schema for ADML
    16. 16. Visualization Tier: Layout Algorithms <ul><li>Circle Layout </li></ul><ul><li>KK Layout </li></ul><ul><li>Set the radius </li></ul><ul><li>Arrange nodes </li></ul><ul><li>Set parameters </li></ul><ul><li>Get initial positions </li></ul><ul><li>Calculate energy </li></ul><ul><li>Rearrange the node until </li></ul><ul><li>it is below the lowest energy </li></ul><ul><li>Iterate until get lowest energy </li></ul>
    17. 17. Spatiotemporal Knowledge Visualization <ul><li>Mailing list visualization based on Google Maps </li></ul>
    18. 18. Conclusions <ul><li>DyVT </li></ul><ul><li>DyVTML(ADML) </li></ul><ul><li>Animation </li></ul><ul><li>Maps </li></ul>T Temporal data Geospatial data Appearance data S A
    19. 19. Outlook <ul><li>Interchange Formats </li></ul><ul><li>Multi-relational social </li></ul><ul><li>networks </li></ul><ul><li>More database support </li></ul><ul><li>Appearance data </li></ul><ul><li>Various output formats </li></ul>Spatiotemporal knowledge visualization & discovery in dynamical social networks Future Work <ul><li>Visualization and discovery </li></ul><ul><li>Matrix-based forms </li></ul><ul><li>Application of other layout algorithms </li></ul><ul><li>Spatiotemporal data mining </li></ul><ul><li>Evaluation and openness </li></ul><ul><li>Further evaluation </li></ul><ul><li>Integration into other tools (e.g. Paladin, pattern based Dynamic NA) </li></ul><ul><li>Extensions of other social patterns (Co-authorship networks, …) </li></ul><ul><li>Privacy and security </li></ul>

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