Hydroinformatics Blog - FAIR and CARE Data Principles Assessment for Sustainable Water Resources Management on Reservation Lands

Posted Sep 13, 2023


Hydroinformatics Blog Post

Organized by the CUAHSI Informatics Standing Committee. Contributions are welcome, please contact Veronica Sosa Gonzalez at email hidden; JavaScript is required.

By: Parisa Sarzaeim, Grace Bulltail

Water resources management by Indigenous Peoples in the U.S. is a complex issue hindered by the lack of reliable and accessible high-quality databases. To address this challenge, we have initiated a research project to evaluate the availability of water-related databases for reservation lands in the U.S. The project focuses on the discoverability and reusability assessment of these databases in terms of both water quality and quantity variables with the goal of environmental justice for Indigenous communities.

The complexity of water resources management on reservation lands is due to the involvement of different regulatory systems at the federal, state, and tribal levels [1]. For sustainable water resources within a complex management system, high-quality and accessible data are crucial. However, the lack of databases consistent with FAIR and CARE principles has restricted the research on managing water resources quality and quantity for Indigenous People’s lands in the U.S. FAIR and CARE are two recently developed principles that promote data sharing and Indigenous sovereignty (Figure 1). FAIR principles foster data’s Findability, Accessibility, Interoperability, and Reusability [2], and CARE principles support data’s Collective benefits, Authority to control, Responsibility, and Ethics [3].

To achieve the proposed objective of this research, we have framed a four-step method to:

  1. explore, list, and review the available water-related databases for reservation lands in the U.S.,
  2. develop an evaluation framework to assess the available water-related databases adherence to the FAIR and CARE principles,
  3. identify the strengths and weaknesses of each database with respect to FAIR and CARE principles, and
  4. develop a comprehensive access protocol to support data discovery, findability, accessibility, and usability in alignment with tribal sovereignty.

Based on our preliminary assessment of water-related databases for reservation lands in the U.S., the insufficiency of digital spatiotemporal databases limits sustainable Indigenous Peoples water resources management. In addition, databases that contain data for reservation lands are often hard to find, and in some instances, access to them is not permitted. We assign these issues to the lack of databases consistent with FAIR and CARE principles, which has led to limited scientific literature on water resources management and environmental injustice for Indigenous Peoples in the U.S. Further in-depth results and outcomes of this research will be published soon.

Acknowledgments

We acknowledge the support from Indigenous Environment & Science Working Group,

Office of Vice Chancellor for Research and Graduate Education & Nelson Institute,

University of Wisconsin-Madison, and Center for Water Policy, School of Freshwater Science, University of Wisconsin-Milwaukee.

About the authors:

Parisa Sarzaeim is a postdoctoral Research Associate at the Nelson Institute for Environmental Studies at the University of Wisconsin-Madison. Her main research focuses on water resources management and environmental justice for underserved communities.

Grace Bulltail is an Assistant Professor at the Nelson Institute for Environmental Studies at the University of Wisconsin-Madison. Her main research focuses on developing resource sovereignty frameworks for Indigenous communities.

References

[1] Royster, J.V. (2011). Conjunctive management of reservation water resources: legal
issues facing Indian tribes. Idaho Law Review, 47(2), 255-272.

[2] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18.

[3] Carroll, S.R., Herczog, E., Hudson, M. et al. (2021). Operationalizing the CARE and FAIR Principles for Indigenous data futures. Sci Data 8, 108 (2021). https://doi.org/10.1038/s41597-021-00892-0.