Organization and Management Theory OMT

AOM PDW: Open and Public Datasets

  • 1.  AOM PDW: Open and Public Datasets

    Posted 4 days ago

    AOM 2024 PDW: Public Datasets for Strategy, Entrepreneurship, and Innovation Research

    Friday, August 9, 2024, 10:30 AM to 1:00 PM | Swissotel, St. Gallen 3

    Are you interested in advancing management research through open and publicly available datasets?

    Join us for the AOM PDW session on Open and Public Datasets for Strategy, Entrepreneurship, and Innovation Research!

    Pre-registration Deadline: July 15th, 2024

    Pre-registration link:

    Empirical research in strategy, entrepreneurship, and innovation often involves specialized data collection by scholars or the use of proprietary datasets. These data sources have significantly contributed to our understanding of management phenomena but can also present challenges regarding replicability, generalizability, and accessibility. Analyses based on individually collected datasets, while tailored to specific research questions, can be difficult for others to verify. Proprietary datasets, though often comprehensive, can be costly and have usage restrictions that limit their wider application.

    To this end, open and public data, such as the Reliance on Science, SciSciNet, or the World Management Survey datasets, offer several advantages for advancing strategy, entrepreneurship, and innovation research. They facilitate study replication, accelerate cumulative research, and streamline peer review processes. Moreover, these datasets reduce redundancy in data collection, leading to more efficient use of research funding while democratizing research by providing all scholars equal access to high-quality data.

    This PDW explores the opportunities and challenges of using open and public datasets and is designed to be interactive and engaging. Matt Marx from Cornell opens with a presentation on Open Datasets for Strategy, Innovation, and Entrepreneurship Research. Yian Yin from Cornell will discuss large-scale open data lakes for science-of-science research, followed by Angela Aristidou from UCL/Stanford on data governance via data trusts. Kristina McElheranfrom the University of Toronto will present on the opportunities, challenges, and risks of large-scale administrative data collection. Leandro Nardi from HEC Paris will explore public datasets to enhance social performance measurement. A 30-minute Q&A session follows, moderated by Sarah Wolfolds from Cornell and Konstantin Scheuermann from UCL. The PDW concludes with a 30-minute roundtable discussion, providing a platform for more personal dialogue between panelists and attendees.

    For any questions, please email us at:, or

    We look forward to seeing you in person at the PDW!


    The Organizers

    Konstantin Scheuermann

    Sarah Wolfolds

    Angela Aristidou

    Konstantin Scheuermann
    UCL School of Management
    London, UK