Recommendations for Advancing FAIR and Open Data Standards in the Water Treatment Community

Abstract

Water treatment researchers will maximize insights from data by implementing FAIR and Open (FAIR/O) principles for data storage and management. Progress toward domain-specific FAIR/O data infrastructure and practices advance data synthesizability, data extensibility, and stakeholder diversity. Embracing FAIR/O data principles in domain research would enable data-driven research breakthroughs that benefit a diverse array of water treatment research stakeholders. These breakthroughs arise from increased data density to improve research scope, better cross-mode data translation between experimental and modeling research outputs, and improved multiscale data integration to answer key questions across research scales. This paper addresses the gap between the current state of data sharing and the envisioned potential of FAIR/O data by offering practical steps toward building effective and sustainable water treatment data infrastructure, engaging key stakeholders, and motivating their participation. We clarify essential activities of a water treatment research data repository and suggest opportunities for communicating and growing its value.

FAIR and Open Data requires proper incentives and a shift in academic culture

“…This hesitancy might simply be because FAIR/O data management has only relatively recently entered the scientific and public debate, suggesting more time is needed to achieve a mindset change. Similarly, FAIRsharing is not yet common practice amongst most researchers, including in the field of water treatment 24 . The growing demand for FAIR/O data will thus require a significant investment from all involved stakeholders to create awareness and educate researchers about the power and the future of this new way of doing science 21,24 .…”

“…Similarly, FAIRsharing is not yet common practice amongst most researchers, including in the field of water treatment 24 . The growing demand for FAIR/O data will thus require a significant investment from all involved stakeholders to create awareness and educate researchers about the power and the future of this new way of doing science 21,24 . In addition, only very few domain-specific repositories exist, even though they are data to understand the fundamental factors governing reverse osmosis desalination, and to direct novel membrane design.…”

“…typically more effective in imposing structured FAIR/O data practices and standards than the more common generalist repositories 24 . In this regard, I envision journals playing an increasingly important role as a 'data transfer hub': they can mandate researchers to deposit the data in a repository, which is on its turn linked to an external domain-specific database, such as the OMD.…”

Toward Transdisciplinary Engineering Implications and Significance in ACS ES&T Engineering

“…Quay et al2 provided recommendations for making data findable, accessible, interoperable, and reusable (FAIR) and open (FAIR/O) to support data-driven methods, broader stakeholder involvement, and far-reaching benefits for all h i b i t e d .…”

“…Second, enhanced transparency through real-time information sharing about the performance or energy usage of an environmental engineering system can result in better decision making around resource allocation and create accountability. Quay et al provided recommendations for making data findable, accessible, interoperable, and reusable (FAIR) and open (FAIR/O) to support data-driven methods, broader stakeholder involvement, and far-reaching benefits for all through water technologies. Third, understanding the user-informed historical context of a location can motivate the design of novel environmental technologies that are more acceptable and trusted by users.…”