Mindat: A crowd-sourced and expert-curated open data ecosystem for mineralogy

Over the past three years, we have successfully launched an open data service for Mindat, one of the largest databases focused on mineral species and their global distributions. Our achievements include: 1) a comprehensive review of existing data records, covering the list of data subjects, their characteristics, and inherent biases, 2) the establishment of an open data API (application programming interface) alongside Python and R packages to integrate the API into workflow platforms, and 3) fostering community collaboration on data standards and best practices for open data, such as mineral nomenclature, rock classification, and technical frameworks for applying the FAIR (findable, accessible, interoperable, and reusable) principles. Mindat is both crowd-sourced and expert-curated, and for the past decades it has been proven to be an effective approach to engage both data contributors and users. Mindat has been popular amongst geoscience professionals and the public alike. Through our open data initiatives and community engagement, we have also gathered valuable insights to guide future developments of Mindat open data. In this presentation, we will highlight the current open data capabilities, provide an overview of the review of Mindat's data records, and share our vision for leveraging advanced artificial intelligence technologies to expand and enhance Mindat in the future.