Abstract
Abstract: This Ph.D. research aims to improve the data management and stewardship for Earth sciencedigital resources by developing an implementable framework for the FAIR data principles. The
lack of a pragmatic framework to facilitate the translation of FAIR data principles into the
digital world has led to a gap between the theories and implementation of those principles for
Earth science data stewardship. To overcome this challenge, we ask four themed questions to
guide the research activities: First, how can we verify the validity and tautology of FAIR data
principles? Second, how can we theoretically address FAIR data principles? Third, how can we
technically approach FAIR data principles? Fourth, how can we efficiently evaluate the
FAIRness of a digital resource? The two formal logical methods used in this work are the Truth
Table and the Natural Deduction. The development method used is semantic web technologies
supported by a FAIR ontology. Furthermore, the FAIRness level evaluation method used is a
Fuzzy logic method. We show that FAIR data principles are valid and tautological, which
resulted in the formulation of FAIR theorems. This research is the first research that implements
formal logic to verify the FAIR data principles and uses fuzzy logic to assess the FAIRness
level, which helps set up a bridge between the human conceptualization and the machine
implementation of the FAIR data principles. We also show the prototype of FAIRtool.org, a
semantic web application that adopts FAIR data principles, and the creation of the Fuzzy FAIR
Assessment Framework (FFAF). The development of the FAIR theorems establishes rules to
translate the FAIR data principles into machine-readable formats, which are necessary for the
implementation of FAIR in the cyberinfrastructure. Using the FFAF model to assess the
FAIRness of a digital resource led to an efficient FAIRness level evaluation. We demonstrated
the outputs of this research with two examples from Earth science, the “NCDC Storm Events
Database” use case and the “Data for Building an Open Science Framework to Model Soil
Organic Carbon” use case. The Earth science community is actively promoting the adoption
and implementation of FAIR principles. This Ph.D. research provides evidence about the logic
validity of FAIR principles. The pilot system and examples show the implementability of FAIR
principles in the cyberinfrastructure for various datasets and other digital resources. With more
work and community of practice, this advancement in cyberinfrastructure will eventually
promote the precision of Earth science data management and stewardship to a new level.