“Historically, we have tended to reward the papers that come from data collection more than the data themselves. But I think there is a growing recognition that creating high-quality, reusable datasets is an important scholarly contribution. Good data can support dozens of studies, answer questions we have not even thought of yet, and help connect researchers across disciplines.
I think this is especially important in extreme weather research, where advancing our understanding often depends on connecting data that bridge the social and physical sciences. Some of the most interesting discoveries happen when researchers use data in ways that were never envisioned when the original study was designed. The more accessible and reusable these datasets are, the more opportunities there are for those kinds of connections to emerge.”
-Dr. Joe Ripberger, The University of Oklahoma
The Weather Program Office Social Science Program (WPO SSP) hosted the third event in its Data Forums series on May 21, 2026, SSP Data Forums: Designing for Long-Term Data Reuse, featuring a conversation with Dr. Joe Ripberger from The University of Oklahoma. The forum’s goal was to exchange ideas and considerations for how to build data sets with reuse and interoperability intended at the outset, considering data as long-term infrastructure rather than as single-use. Dr. Ripberger provided an overview of the Extreme Weather and Society Survey effort he leads, focusing on the longitudinal data it collects as an example of these practices.
Attendees learned there are many factors to consider when designing a data set that is intended for secondary use by the hazard/extreme weather community, which Dr. Ripberger referred to as “collective reuse.” The data must be both consistent to allow for comparability over time and also adaptable to allow for flexibility as technology and measurement strategies evolve. Additionally, managing datasets for collective reuse and interoperability requires significant time, effort, coordination, and documentation so that it can be accessed and understood by people outside of the original research team. For the Extreme Weather and Society Survey in particular, the research team considers the interoperability of their data in layers: internal consistency across the various surveys (both temporally and thematically), compatibility with other social data sets (for example, census data), and the ability to be integrated with physical science data (for example, meteorological information). Emphasizing the commitment required for public data sharing, Dr. Ripberger estimated that 30–50% of project time is devoted to documentation, cleaning, and formatting data specifically for reuse.
The discussion then shifted to incentives and challenges related to data sharing and reuse. Historically, publishing papers was the ultimate metric for research productivity, with data being considered secondary or even proprietary. Increasingly, data is growing in recognition as a contribution of knowledge in its own right, with many funders and repositories providing persistent identifiers (DOIs) for data to enable the tracking of data citations and downloads. However, there continue to be challenges, especially for early career researchers looking to establish themselves, to produce original or new ideas and data; this can be a disincentive for researchers to reuse existing data. Another challenge is that regardless of how well documented the metadata is, contextual knowledge about collection methods remains with the original researchers which can leave data reusers navigating significant uncertainty. For the original research team, dedicating time to answering questions from the community and potentially seeing the data used in unexpected ways can also be a challenge. Ultimately, the goal of community efforts like the SSP Data Forums is to break down data-related barriers and build new norms by providing a place to share insights, learn skills, and connect ideas that advance science and serve societal need.
