NSF projects underway at the iSchool


Zadorozhny serves as co-PI for NSF project to study evolution of global social patterns

Vladimir Zadorozhny, Associate Professor at the iSchool, is serving as co-PI on an NSF-funded project to study global social patterns over time. This project is funded by the National Science Foundation’s Division of Social and Economic Sciences for $282,023 over a two-year period. Dr. Zadorozhny is partnering with the Center for Historical Information and Analysis at the University of Pittsburgh. To understand global social patterns as they exist today, it is increasingly clear that we need to understand how they have evolved over recent centuries. The Center for Historical Information and Analysis responds to this need and takes historical analysis into the realm of Big Data. It is expected that the data resources will grow to several terabytes in size. This project will stimulate development of more efficient research collaborations, enabling systematic large-scale consolidation of diverse historical data sources. Once collected and integrated, the data repository and analytical system will allow scholars to address a wider set of questions testing hypotheses about long-term and short-term social change at the global scale and catalyzing an expansion of the evidence base in social sciences. For example, our understanding of important societal issues can advance by linking health to demography and by incorporating climate and health factors into economic studies. Disciplinary theory will advance through interaction among the various scientific fields, so that a global network of social-science researchers will emerge.

This project will strengthen the organizational and technical infrastructure of the Center for Historical Information and Analysis (http://chia.pitt.edu), a multi-institutional collaborative of scholars in social, natural, and information sciences structured as a Research Collaborative and a Headquarters. The Research Collaborative links participating institutions that are collecting data on population, climate, and other topics with a crowdsourcing tool to demonstrate the feasibility of building a continuously growing collection of diverse historical data and metadata. The Headquarters assembles and develops knowledge on repository design to develop a repository sufficient to house the incoming data and permit global and interactive analysis. The Center for Historical Information and Analysis's future plans include expanding its collection and processing of historical data, broadening its community of social and natural science researchers, analyzing historical patterns of global change, and sharing its resources with researchers, policy-makers, teachers and students. CHIA is headquartered at the University of Pittsburgh with participating research groups at Boston University, Harvard University, Michigan State University, and University of California-Merced. Visit http://www.nsf.gov/awardsearch/showAward?AWD_ID=1244672&HistoricalAwards=false for more information about this project.

Weiss, Tipper, and Krishnamurthy to develop models of Secondary Spectrum Use as part of NSF grant

iSchool faculty members Martin Weiss, David Tipper and Prashant Krishnamurthy have been awarded a grant from the National Science Foundation’s Division of Computer and Network Systems for $484,962. The team will explore creating “Techno-Economic Models of Secondary Spectrum Use” over a two-year period. Dynamic Spectrum Access (DSA) technologies have been proposed and researched for 15 years, yet only some relatively experimental systems are in operation today. This research explores some essential but unexplored techno-economic aspects of DSA that are crucial if these systems are to come to commercial reality. One major thrust is an exploration of how substitutable different frequency bands that these systems might use are with each other. Another major thrust is how a firm that might be considering the use of DSA technologies can manage the technical and financial risk inherent in them. To accomplish this, a fungibility score based on mathematical models and agent-based simulations are developed to evaluate the substitutability among spectrum bands to assist firms as well as policymakers in assessing candidate bands for use in a DSA system. For risk management, the project employs real options analysis to develop a set of risk measures and mitigation strategies for technical and financial risk to assist secondary users in DSA systems. This work will help policymakers develop better guidelines for the industry. It will also help firms seeking to use DSA technologies reason more clearly about which technical and financial choices are best and why, providing guidelines for growth and job creation. The expected outcomes of this project will include a set of tools that will enable entrants into a secondary spectrum market to make decisions as well as for policy makers to evaluate the factors that may influence their regulatory guidelines in order to promote viable DSA markets. See http://www.nsf.gov/awardsearch/showAward?AWD_ID=1247546&HistoricalAwards=false for more information.