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Project Overview

    Beginning Spring, 2015, with U.S. National Science Foundation (NSF) support, we have been working on “Forecasting Innovation Pathways of Big Data & Analytics. Our research has two main elements:

  • ‘tech mining’ (empirical analyses of research funding, literature, and patents to discern R&D trends and active players), and
  • engagement of stakeholders and experts to help understand developmental prospects and likely outcomes.
  • We invite you to our “Publications” based mainly on tech mining of R&D on “Big Data & Analytics” (BDA) drawn from multiple databases: Web of Science (WoS), INSPEC, ABI Inform, NSF and NSFC (National Natural Science Foundation of China) awards, and Derwent Innovation Index patents. The analyses show amazing growth in R&D and attention to BDA building since 2008. A map of the publications indexed by WoS shows incredibly broad interest — extending way beyond computer & data science — in using BDA to advance research in diverse fields. Our analyses find the U.S. and China leading the global BDA effort.
    We now focus on understanding BDA outcomes – particularly the “unintended, indirect, and delayed effects” of applications in many arenas. We invite your contributions to this.


    We acknowledge support from the US National Science Foundation (Award #1527370 – “Forecasting Innovation Pathways of Big Data & Analytics”). The findings and observations contained in this project are those of the authors and do not necessarily reflect the views of the National Science Foundation. Thanks for review and suggestions: Sanjay Arora(Georgia Tech); Laura Haas (IBM); James Cooper (George Mason University School of Law); Muhammad Anshari(Universiti Brunei Darussalam, Continuing Education Centre & e-Government Innovation Centre); Michael Rappa(North Carolina State University); Dan Suciu(University of Washington).

[Other Resources]

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