The "digital breadcrumbs" of contemporary life offer "the potential of transforming our understanding of our lives, organizations, and societies in a fashion that was barely conceivable just a few years ago."

--Lazer, et al. 
'Science', 2009

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  • BDSS_HP_HERO_3.jpg

    The Databasement - home of Big Data Social Science IGERT

  • BDSS IGERT Boot Camp

    Boot Camp Kick-off Meeting Fall 2014

  • BDSS_HP_HERO_5.jpg

    BDSS IGERT Event - Global Event Hackathon

  • 'ggplot2' tutorial for PSU R-Users group

    IGERT trainees working with R-user group members on 'ggplot2' tutorial

  • BDSS IGERT Speaker Series - Yaw Anokwa

    BDSS IGERT Speaker Series - Dr. Yaw Anokwa

  • BDSS IGERT Speaker Series - Renee Knake

    BDSS IGERT Speaker Series - Dr. Renee Knake

  • RCC Workshop on Parallel Computing - Hive & Pig

    RCC Workshop - Using Hive & Pig

  • Quantitative Social Science Initiative Colloquium presentation - Nathaniel Porter

    QuaSSI Fellow, Nathaniel Porter - "Choosing a Social Network Tool: An Introduction for Non-specialists"

  • BDSS IGERT Poster Session

    BDSS IGERT Poster Session - trainees & associates presenting their work

Big Data Social Science

    This Integrative Graduate Education and Research Traineeship (IGERT) award draws together a diverse interdisciplinary team of researchers to create a new training program in Social Data Analytics, aimed at producing a new type of scientist capable of meeting emerging big data challenges. The program is intended to establish new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries, and to engage students in understanding the processes by which research is translated to innovations for societal benefit.Read More

    In response to massive new sources of data, “data science” and “analytics” are emerging as new fields of inquiry, merging statistics, computer science, and visualization. The greatest challenges and opportunities arise from socially-generated big data, observed as a result of human interactions that are increasingly recorded via web, mobile device, and distributed sensors, or revealed through digitization of historical records. Society faces a transformative data deluge, from which new scientific, economic, and social value can be extracted. The BDSS-IGERT project includes a new curriculum, training in advanced technologies of data science and analytics, a series of research rotations – in both academic and nonacademic settings – and a challenge mechanism, under which interdisciplinary teams compete to innovate solutions to real social data analytics problems.

    A recent report estimated that big data contain unexploited economic value over $1 trillion annually, but that 165,000 positions in “deep analytics” will need to be filled. Government statistics agencies need to produce useful statistical products, at lower cost, while protecting confidentiality. Big data technologies like crisis mapping present opportunities to address grand social challenges. Further, the BDSS-IGERT project expands the participation of underrepresented groups in data science, by combining an exciting new field with a focus on diversity as a research theme.

    IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to establish new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries, and to engage students in understanding the processes by which research is translated to innovations for societal benefit.

    Nowhere are the transformational opportunities, and new scientific challenges, greater than in the social sciences. BDSS-IGERT addresses both sides of this equation: bringing the big data technologies and advanced computational and inferential modes of thinking into social science, while bringing social science expertise and modes of thinking, about processes of human interaction and about how to study them, into the work of analytics.Read Less