CI_for_NA

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CI_for_NA

  1. 1. CyberInfrastructure for Network Analysis <ul><li>Importance of, contributions by network analysis </li></ul><ul><li>Transformation of NA </li></ul><ul><li>Support needed for NA </li></ul>
  2. 2. Contributions by NA <ul><li>Grand scientific and societal challenges for which contributions by NA are essential, e.g.: </li></ul><ul><li>Epidemiology </li></ul><ul><li>Social influences in health-related behavior, substance (ab)use </li></ul><ul><li>Distributed governance </li></ul><ul><li>Politics – citizens opposition </li></ul><ul><li>Organizational analysis </li></ul><ul><li>Conflicts between groups within societies </li></ul>
  3. 3. Transformation of NA <ul><li>Network Analysis is currently transforming itself into a bigger (???) science: </li></ul><ul><li>Data * ways (automated) of collecting them, in addition to manually collected data * size: complexity & number of nodes </li></ul><ul><li>Analysis * computing * statistical modeling (beyond case studies) * visualization </li></ul><ul><li>Multi (inter, trans?) disciplinarity </li></ul>
  4. 4. What is needed to fulfill the promises <ul><li>The promises of NA can be fulfilled only if there is strong extra support. </li></ul><ul><li>Cyberinfrastructure: NA Technology: data collection, data availability, analysis, dissemination </li></ul><ul><li>Support for multi-stranded collaboration (disciplines, techniques, research questions) This must be facilitated by CI, but also includes education, dissemination, incentive structures </li></ul><ul><li>CI needs to handle diversity </li></ul>
  5. 5. NA Technology <ul><li>Extraction of network data </li></ul><ul><ul><li>from text, photos, videos, logs, processes, web </li></ul></ul><ul><ul><li>Data cleaning, entity resolution </li></ul></ul><ul><ul><li>To Create better metadata (e.g. with history) </li></ul></ul><ul><ul><li>Links between data sets / papers / methods / … </li></ul></ul><ul><li>Dealing with Huge / Complex networks </li></ul><ul><ul><li>Modeling, Approximation </li></ul></ul><ul><ul><li>New visualization and interaction techniques </li></ul></ul><ul><li>Temporal Analysis (including real time) </li></ul><ul><li>Interoperability </li></ul><ul><ul><li>Data and software level </li></ul></ul><ul><li>Social Engineering </li></ul><ul><ul><li>setting experiments in CI </li></ul></ul><ul><ul><li>simulated worlds </li></ul></ul>
  6. 6. NA Technology <ul><li>User Interfaces </li></ul><ul><ul><li>Facilitate/teach Analysis Process </li></ul></ul><ul><ul><li>History keeping/saving </li></ul></ul><ul><ul><li>Multilevel interfaces to address varying user needs and abilities </li></ul></ul>
  7. 7. Community support <ul><li>Grand challenge </li></ul><ul><li>Map of SNA community </li></ul><ul><li>Facilitate communication between and within disciplines (workshops, textbooks, web + paper tutorials) </li></ul><ul><li>+ many “CI-Generic tools” </li></ul><ul><ul><li>Query-able Digital Library of paper ref., datasets, tools, people </li></ul></ul><ul><ul><li>Archive </li></ul></ul><ul><ul><li>+ lots of things </li></ul></ul>
  8. 8. Evaluation <ul><li>Guidelines about what to use when </li></ul><ul><li>User studies for evaluation of components </li></ul><ul><li>Longitudinal studies (e.g. of the CI itself) </li></ul><ul><li>Caution: standardization, monopolies reduce diversity </li></ul>
  9. 9. Open Questions <ul><li>For which ends do we need standards, which, how? Middelware. </li></ul><ul><li>Centralize or not? Control must be loose! </li></ul><ul><li>Is there a CI curator? </li></ul><ul><li>Open source? </li></ul><ul><li>Commercial vs. freeware? </li></ul><ul><li>Ethics, privacy (note: some officials have more info than researchers!) We need new rules/norms for working with private info. Two-way transparency How can we study private things while retaining confidentiality? </li></ul>
  10. 10. <ul><li>What is the community? </li></ul><ul><li>What are the communities? (note: cross-fertilization with system biologists) </li></ul><ul><li>Note: small data sets remain important </li></ul><ul><li>Important contributions by social theories/theorists to NA & this work </li></ul><ul><li>Bias inherent in automated data collection </li></ul><ul><li>Public dissemination of results also to general public and policy makers </li></ul>

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