Tikoff and 5 co-authors reported in mid-2023 that the field of geology is poised to make a fundamental transition in the quality, character, and types of science that are possible for practitioners. Geologists are developing data systems—consistent with their workflow—to digitally collect, store, and share data. Separately, geologists and cognitive scientists have been working together to develop tools that can characterize the level of uncertainty of both data and models.
Two different cross sections depicting different interpretations for the regional geology.
The transformational change comes from the simultaneous combination of these two approaches: digital data systems designed to capture and convey scientific uncertainty. This approach promotes better data collection practice, improves reproducibility, and increases trust in community-based digital data. We applied these methods—attending to uncertainty and its incorporation into digital repositories—to the Sage Hen Flat pluton in eastern California, USA, where two published maps provide different interpretations. Incorporating uncertainty into our workflow, from field data collection to publication, allows us to move beyond binary choices (e.g., is this data/model right or wrong?) to a more nuanced view (e.g., what is my level of uncertainty about the data/model?) that is shareable with the larger community.
The authors concluded that it is generally recognized that science and society are undergoing a digital revolution. The geological community has the opportunity to adapt best practices of the past to the emerging new workflows that result from the ability to operate digitally. They proposed the systematic use of uncertainty scales when collecting digital field data and developing models, which are easily recorded by digital technologies, as better science practice.
The authors applied the use of uncertainty scales to bedrock mapping at the Sage Hen Flat pluton in eastern California, where different data resulted in different models for the regional geology. New data was collected in the area of most divergence between the two geological maps. The purpose of their evaluation was to show how data that contain uncertainty estimates provide a fundamentally better record of geological field data, can adjudicate between different models, and can guide future research.
Managed & Built by I2M Consulting, LLC | © 2010-
