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Abstract:
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Statistics has a role to play in ensuring publicly accessible research data are of high quality and reusable by others. Despite recent funder mandates to share data, most researchers lack the experience needed to prepare quality shared data for reuse by others or to protect data that have privacy or proprietary restrictions. While these are standard elements of statistical design and dissemination approaches, we will consider new contexts that arise in research data sharing and discuss how statistical practice can be adapted to improve planning and execution of research studies. For example, insights from information science indicate research outputs beyond data and metadata are needed to increase the “reusability” of shared research data by others (e.g., code used to process and analyze data, detailed methodologies). These outputs are also key to the practice of open science and ensuring rigor and transparency in scholarly research. Come join the discussion of how statistical practice can be adapted to improve the reusability of shared research data and support open science practice.
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