Document Type
Poster
Publication Date
Summer 7-10-2024
Abstract
FAIRification (Findability, Accessibility, Interoperability, and Reusability) of geospatial and temporal data from the United States Geological Survey (USGS) is crucial for the continuance of the National Science Foundation (NSF) Engineering Research Center for Advancing Sustainable and Distributed Fertilizer Production (CASFER) whose aim is to aid in the development of eco-friendly fertilizers. The USGS data contains key information about water quality and contaminants, which are important metrics for our geospatial project since our work aims to track the contaminants' flow and work towards their reduction and subsequent elimination. FAIR principles refer to - Findability, Accessibility, Interoperability, and Reusability. This is important for the safeguarding and preservation of the data collected. Often, the data that has been extracted and worked on will be needed by someone else in the same project for a different purpose. The person working on the data will have their philosophies behind naming and storing the data which could become a problem for anyone else trying to use the data down the line if they do not have a guidebook or a manual to the initial person’s pointers. This is why FAIRification of data is crucial in academia and industry. The FAIR principles have been designed to create a standardized and globally recognized nomenclature for the storage of data.
- Findability refers to assigning the data an identifier that is global and unique and the data is indexed in a searchable database.
- Accessibility means that the data can be retrieved by its identifier using a universally implementable protocol with authentication procedures wherever required. It also refers to the fact that the metadata will be accessible even when the data is not available.
- Interoperability means that the metadata uses a formal, accessible, and applicable language for knowledge representation and uses vocabularies that follow FAIR principles.
- Reusability refers to the fact that the metadata is extensively described with relevant attributes and released with a clear and accessible data usage license.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Department/Center
Materials Science & Engineering
Recommended Citation
Panda, Attiksh Ansool; Akanbi, Olatunde D.; Mandayam, Vibha S.; Barcelos, Erika I.; and French, Roger H., "FAIRification of Geospatial Data" (2024). Student Scholarship. 18.
https://commons.case.edu/studentworks/18