CIF21: DIBBs: Building a Unified Infrastructure for Data Integration on Political Violence and Conflict

University Of Maryland, College Park, College Park MD

Investigators

Abstract

Building a Unified Infrastructure for Data Integration on Political Violence and Conflict This proposal s a conceptualization project whereby leaders of several major data collections, along with experts in insurgency, ethnic conflict, terrorism, computer science, and data management, will build consensus around a unified infrastructure for political violence data collection and integration. The project will create a scalable ontology focused on four domains relevant to all forms of political violence: conflicts, actors, geographies, and events. This ontological infrastructure will allow researchers and policy makers who study political violence, including its etiology and consequences, to access and integrate existing data from the major political violence data collections currently collected at academic institutions and non-governmental organizations around the world. This infrastructure will also facilitate the development of new non-linear and semantic analytical methods to decipher the complex dynamics of conflict and violence. Finally, this infrastructure will provide a platform for the next generation of data collection on violence and conflict by creating a flexible framework for new data collection projects that is both easily exchangeable and adheres to the consensus-based ontologies developed. The proposed project incorporates a two-day stakeholder workshop, a schematic design of the ontological infrastructure for political violence data collection, and a web-based community-moderated issue-tracking wiki to encourage participatory development and refinement of the ontologies. Additionally, the proposed project supports one of the core missions of NSF?s Big Data initiative, focusing on the development of a data infrastructure relevant to national security. Intellectual Merit: Although scientists have made major advances in the empirical understanding of political violence in recent years, nonetheless further advances are being hindered by the fact that leading projects from around the world are largely autonomous and uncoordinated. This project will address this weakness by creating a scalable ontology focused on domains critical to political violence. The major goal of this enterprise is to design a strategy for integrating the world?s most important data bases on political violence within an expandable platform that will allow not only updating original data but the addition of new data and variables, including rapidly evolving data sets derived from the social media. The proposal has built in sufficient resources to host a two-day stakeholder conference, to prepare read-ahead materials for stakeholders before the conference, to design and staff a wiki for reaching out to the research community and for developing a final report that will serve as a springboard for a proposal to implement the ontology designed. By integrating the major data bases, providing an infrastructure for growth, and making the end product available to the world?s research community, the proposed activity could have a transformative impact on the science of political violence. Broader Impacts: This ontological approach to political violence data collection will offer critical insights for data integration and for advancing the scientific study of violent conflict. Effective identification of ontologies across major political violence data collections will provide an essential roadmap for the integration of these data structures and the development of new applications and analysis for research on national security. Additionally, the workshop will serve to network senior and junior faculty alongside graduate students thereby developing a new generation of political violence experts. The translation of the workshop report into a community-moderated and web-based issue-tracking wiki will serve to expand participation to include other researchers who will be instrumental in defining and shaping a larger ontological structure for both existing and future data collection efforts.