Please Contact:

Burt L. Monroe
Pennsylvania State University

Liberal Arts Professor of Political Science and Social Data Analytics

Head, Program in Social Data Analytics (SoDA)


Details of the NSF-funded IGERT (Integrative Graduate Education and Research Training) Big Data Social Science Ph.D. Training Program

BDSS-IGERT was an interdisciplinary research and training program for Penn State PhD students interested in data-intensive and computation-intensive research based on large or complex datasets arising from human interaction. BDSS-IGERT had a core mission of enabling a new type of scientist, defining a new model and role for the social sciences in both research and education, reflected now in Penn State's new Program in Social Data Analytics (SoDA) and Center for Social Data Analytics (C-SoDA).

BDSS-IGERT trainees received a $30000 annual stipend and additional resources in order to complete a two-year training program involving the graduate curriculum in Social Data Analytics (SoDA), interdisciplinary research rotations, and externships. There were also a variety of mechanisms through which students could participate as "affiliates" of the program. From 2012-2018, BDSS-IGERT directly supported over 50 PhD student fellows and affiliates from political science, geography, statistics, sociology, information science, human development, health policy, criminology, computer science, and demography.

BDSS-IGERT was funded by a $3m IGERT grant from the National Science Foundation in 2012, with over $3m of additional programmatic and infrastructure support from the College of Liberal Arts, the Office of the Vice President for Research, the Social Science Research Institute, the Institute for CyberScience, the Department of Political Science, the Quantitative Social Science Initiative, and private donors. Participation of international students was made possible through support from the College of Liberal Arts, the Quantitative Social Science Initiative, and partner colleges: the College of Earth & Mineral Sciences, the College of Engineering, the College of Health & Human Development, the College of Information Sciences & Technology, and the Eberly College of Science.

BDSS-IGERT was developed by the Penn State Quantitative Social Science Initiative [QuaSSI], in partnership with over 90 faculty across the Penn State campus, as well as nonacademic partners in industry, government, and nonprofits.

BDSS-IGERT Training Program Requirements

The BDSS-IGERT training program consisted of four core elements:

  1. Curriculum. Integrated with their home PhD program requirements, BDSS-IGERT trainees completed an interdisciplinary curriculum, now instantiated as the dual-title PhD and doctoral minor in Social Data Analytics. Please see the SoDA Graduate Program page for more detail.
  2. Research rotations. Trainees spent the academic year as participants in interdisciplinary social data analytics research hosted by faculty, projects, and labs across Penn State. Trainees and research rotation hosts were advised to manage this as a roughly quarter time (10 hour / week) RAship. Most research rotation hosts were members of the SoDA Graduate Faculty. Trainees were matched to hosts primarily through the "Speed Dating / Matchmaking" event, held annually in September, and trainees were expected to rotate across the social science / non-social science boundary during their two years. Each spring semester, trainees and hosts presented a poster discussing the project and progress to that point. These research rotations have resulted in an impressive volume and breadth of interdisciplinary research co-authored by BDSS-IGERT students. Please see the Research page for more detail.
  3. Externships. Trainees were required to take up externships in their two BDSS-IGERT summers, engaging in social data analytics research outside of Penn State. At least one of these was to be in a nonacademic research setting such as private industry, government agencies, or nonprofits. BDSS-IGERT trainees took up externships in a wide variety of locations across the globe, resulting in both ongoing research collaborations and job opportunities. Please see the Externships page for more detail.
  4. Community. BDSS trainees and other students engaged in a wide variety of other collaborative and community events. These include taking (and offering) training workshops, hackathons and other research challenge events, and meeting with a variety of outside visitors hosted through the BDSS-IGERT Speaker and Event Series. The center for BDSS-IGERT community activity was the DataBasement in Sparks building in central campus. The result of a $1m renovation in 2013, the DataBasement is a flexible collaboratory, acting both as a student lab with access to computational infrastructure -- including a high throughput fiber optic research network, visualization wall, and Hadoop cluster -- and as the site for lectures, workshops, poster sessions, hackathons, and other events. The DataBasement is now the home of the Center for Social Data Analytics.


Eligibility for BDSS-IGERT (archived)

BDSS-IGERT students must be admitted to a participating Penn State PhD program: Statistics, Computer Science & Engineering, Information Sciences & Technology, Geography, a participating social science department in the College of Liberal Arts (Political Science, Sociology, Anthropology, Economics, Communication Arts & Sciences, Criminology) or the College of Health & Human Development (Human Development & Family Studies, Health Policy & Administration). Students in the dual-title degree in Demography, regardless of home department, are also eligible. BDSS-IGERT is, for most departments, a program taken up in the second and third year of the PhD program. (For programs that admit directly to a Masters, they might take up IGERT in years one and two of the PhD; there may be other exceptions.) NSF-funded trainees must, by US law, be US citizens or permanent residents, but there may be limited funding available from participating Penn State colleges to support international trainees. Please see the Application page for more detail.