Big Data Science Veracity (Robustness Robustness of the simulation is dependent upon the (collection, Issues, semantics) quality of the model. However, robustness of the curation, computation itself, although non-trivial, is tractable. analysis, Visualization Would require very large amount of movement of action) data to enable visualization. Data Quality (syntax) Consistent due to generation from a model Data Types Primarily network data. Data Analytics Summary of various runs and replicates of a simulation Big Data Specific Computation of the simulation is both compute intensive and data Challenges (Gaps) intensive. Moreover, due to unstructured and irregular nature of graph processing the problem is not easily decomposable. Therefore it is also bandwidth intensive. Hence, a supercomputer is applicable than cloud type clusters. Big Data Specific None Challenges in Mobility Security & Privacy Several issues at the synthetic population-modeling phase (see social Requirements contagion model). Highlight issues for In general contagion diffusion of various kinds: information, diseases, generalizing this use social unrest can be modeled and computed. All of them are case (e.g. for ref. model that utilize the underlying interaction network to study the architecture) evolution of the desired phenomena. More Information (URLs) Note: <additional comments> Use Case Title Social Contagion Modeling Vertical (area) Social behavior (including national security, public health, viral marketing, city planning, disaster preparedness) Author/Company/Email Madhav Marathe or Chris Kuhlman /Virginia Bioinformatics Institute, Virginia Tech or ckuhlman@vbi.vt.edu /Actors/Stakeholders and their roles and responsibilities Goals Provide a computing infrastructure that models social contagion processes. The infrastructure enables different types of human-to-human interactions (e.g., face-to-face versus online media; mother-daughter relationships versus mother-coworker relationships) to be simulated. It takes not only human-to-human interactions into account, but also interactions among people, services (e.g., transportation), and infrastructure (e.g., internet, electric power). Use Case Description Social unrest. People take to the streets to voice unhappiness with government leadership. There are citizens that both support and oppose government. Quantify the degrees to which normal business and activities are disrupted owing to fear and anger. Quantify the possibility
Big Data Science (collection, curation, analysis, action) Veracity (Robustness Issues, semantics) Robustness of the simulation is dependent upon the quality of the model. However, robustness of the computation itself, although non-trivial, is tractable. Visualization Would require very large amount of movement of data to enable visualization. Data Quality (syntax) Consistent due to generation from a model Data Types Primarily network data. Data Analytics Summary of various runs and replicates of a simulation Big Data Specific Challenges (Gaps) Computation of the simulation is both compute intensive and data intensive. Moreover, due to unstructured and irregular nature of graph processing the problem is not easily decomposable. Therefore it is also bandwidth intensive. Hence, a supercomputer is applicable than cloud type clusters. Big Data Specific Challenges in Mobility None Security & Privacy Requirements Several issues at the synthetic population-modeling phase (see social contagion model). Highlight issues for generalizing this use case (e.g. for ref. architecture) In general contagion diffusion of various kinds: information, diseases, social unrest can be modeled and computed. All of them are model that utilize the underlying interaction network to study the evolution of the desired phenomena. More Information (URLs) Note: <additional comments> Use Case Title Social Contagion Modeling Vertical (area) Social behavior (including national security, public health, viral marketing, city planning, disaster preparedness) Author/Company/Email Madhav Marathe or Chris Kuhlman /Virginia Bioinformatics Institute, Virginia Tech or ckuhlman@vbi.vt.edu /Actors/Stakeholders and their roles and responsibilities Goals Provide a computing infrastructure that models social contagion processes. The infrastructure enables different types of human-to-human interactions (e.g., face-to-face versus online media; mother-daughter relationships versus mother-coworker relationships) to be simulated. It takes not only human-to-human interactions into account, but also interactions among people, services (e.g., transportation), and infrastructure (e.g., internet, electric power). Use Case Description Social unrest. People take to the streets to voice unhappiness with government leadership. There are citizens that both support and oppose government. Quantify the degrees to which normal business and activities are disrupted owing to fear and anger. Quantify the possibility