October e-Newsletter Community Guest Spotlight with Kristina Vrouwenvelder
Posted Oct 9, 2024
Supporting open and FAIR data in hydrology: October e-Newsletter Community Guest Spotlight
Kristina Vrouwenvelder, Ph.D., Assistant Director, Publications, American Geophysical Union
In an era where addressing global scientific and societal challenges demands cooperation and speed, it’s more important than ever to embrace open science practices, which aim to make research more transparent, accessible, reproducible, and inclusive. Governments and funders recognize this: UNESCO has released international recommendations towards open science, the E.U. has emphasized open science policies, and the U.S. Office of Science and Technology Policy 2013 Holdren memo and 2022 Nelson memo have set new standards that will result in significant improvements in public access to federally-funded research outputs.
In the AGU community, both more open and more reproducible science is needed. The use of AI in the geosciences is accelerating, amplifying the need for high-quality, well-documented data. Projects in open science and data at AGU over the years have therefore emphasized the FAIR principles, which provide a framework to ensure research data is findable, accessible, interoperable, and reusable. In our support for open science and data, we’ve partnered with organizations including ESIP, EGU, and JpGU to convene open science workshops and help desks at international and domestic scientific meetings, including at WaterSciCon24 in Minneapolis earlier this year and an upcoming workshop with CUAHSI scientist Lindsay Platt at AGU24. We now host an Open Science Recognition Prize and multiple learning circles for AGU members teaching skills for sharing data and code and practicing open science and we support open access publishing in our journals. For almost half a decade, our editors have been dedicated to supporting open and FAIR data in research articles published by AGU.
But what does it mean for research data to be FAIR? This can vary by discipline, data type, and potential for reuse (e.g., earth observation datasets that can only be collected once have high standards for documentation and preservation!). Scientific disciplinary communities – whether organized through the sections of societies like AGU or EGU, disciplinary organizations like CUAHSI, or following other models – could play an important role here by coming together to define and support standards for sharing FAIR research data. These standards might define what kinds of data should be preserved, and for how long; they might define standard file types, or standard types of metadata (which might include instruments used, or locations of data collections, or anything unique to that discipline and important for reuse). Community accepted and supported disciplinary repositories like HydoShare could continue to serve as places to uphold standards, ensuring that hydrology data is easily found and reused.
Of course, many disciplines need more educational, material, or infrastructure support to achieve FAIR-er data. Not all data can be or should be shared and preserved at this high a level; legal, privacy, or data sovereignty considerations might also apply to some disciplines. Ultimately, the goal of these efforts is to increase scientific efficiency, allowing data to outlive a single analysis in a publication and curating all research outputs as a resource for scientists beyond a single research group.