Big Data and AI-Enabled Construction of a Novel Gemstone Database: Challenges, Methodologies, and Future Perspectives
Year: 2025
Type: article
Abstract: Gemstone samples, as objects of study in gemology, carry rich geological information and cultural value, playing an irreplaceable role in teaching, research, and public science communication. In the current age of big data, machine learning and artificial intelligence techniques based on gemstone databases have emerged as a cutting-edge area of gemology. However, traditional gemstone databases have three major limitations: an absence of standardized data schemas, incomplete core datasets (e.g., records of synthetic and treated gemstones and inclusion characteristics), and poor data interoperability. These deficiencies hinder the application of advanced technologies, such as machine learning (ML) and AI techniques. This paper reviews gemstone data and applications, as well as existing gem-related sample databases, and proposes a framework for a new gemstone database based on standardization (FAIR principles), integration (blockchain technology), and dynamism (real-time updates). This framework could transform the gemstone industry, shifting it from “experience-driven” to “data-driven” practices. Powered by big data technology, this novel database will revolutionize gemological research, jewelry authentication, market transactions, and educational outreach, fostering innovation in academic research and practical applications.
Source: Minerals
DOI: 10.3390/min15111149
Authors: Yu Zhang, Guanghai Shi
Institution: China University of Geosciences (Beijing)
Language: English
Subfield: Geochemistry and Petrology
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4415811264