EarthCube Capabilities: OpenMindat - Open Access and Interoperable Mineralogy Data to Broaden Community Access and Advance Geoscience Research

Mindat是一个社区驱动的、免费访问的在线数据库，它记录了所有已知矿物种类及其全球分布的信息。虽然Mindat网站上的所有数据都是免费供用户浏览的，但数据访问和下载的机器接口从未完全建立起来。OpenMindat项目将首次允许从这个数据资源中自动查询和下载，用于学术研究。这项工作包括建立开放数据访问的技术开发、研究和培训活动，以推进数据管理和数据驱动的地球科学发现，以及向EarthCube和广泛的地球科学社区开展推广活动。开放Mindat数据供免费学术使用将鼓励地球科学和其他学科的新一代研究。Mindat已经成为地球科学教育的重要资源。目前，该网站每月的浏览量超过350万。OpenMindat中的这些新的数据访问工具将使在教室、实验室甚至在家里访问矿物学数据变得更加容易，让学生有更多的机会实验矿物学数据科学。OpenMindat项目将包括将所有适当的Mindat数据转移到一个开放科学兼容的许可证中，构建和运行一个基于web的平台，用于自动查询和批量数据下载，准备有关这些数据使用的所有文档，以及构建一套开发人员工具，包括Python和R包，用于从工作流平台直接访问数据。OpenMindat还将部署元数据标准，以建立与EarthCube GeoCODES的连接。该项目将设立若干培训职位，并组织一份参与和外联活动清单，优先考虑代表性不足的群体。大型矿物学数据集的计算和统计工作推动了最近矿物演化和矿物生态学的研究，其中Mindat数据是关键组成部分。OpenMindat将使这项研究民主化，允许任何希望利用Mindat数据进行研究的人立即这样做。将机器学习技术与OpenMindat数据集相结合，提高了在地球及其他星球上发现以前未见过的矿物多样性模式的可能性，例如，将地球上的矿物组合和位置与其他行星进行比较。这个项目将说明在分析矿物样品时收集和提供某些资料的重要性，从而引起矿物数据收集和分享方面的文化转变。同样，该项目的研究将成为一个例子，说明当数据到位并结合先进的分析技术和数据科学专业知识时，科学发现可以多么迅速地向前发展。作为OpenMindat的一部分开发的服务和工具本身将是开源的，并且可能对其他希望提供访问其数据的项目有益。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Mindat is a community-driven, free-access, online database that records information about all known mineral species and their worldwide distribution. Although all the data on the Mindat website are free for users to browse, the machine interface for data access and download has never been fully established. The OpenMindat project will, for the first time, allow automated querying and downloads from this data resource for academic research. This effort includes technical developments to establish open data access, research and training activities to advance data curation and data-driven geoscience discovery, and outreach activities to EarthCube and the broad geoscience communities. Opening the Mindat data for free academic use will encourage a new generation of research in geosciences as well as other disciplines. Mindat is already an important resource for geoscience education. Currently, it receives more than 3.5 million page views every month. These new data access tools in OpenMindat will make it easier for educational access to mineralogical data in the classroom, the laboratory, and even from home, allowing students greater opportunities to experiment with mineralogical data science. The OpenMindat project will involve moving all appropriate Mindat data into an open science compatible license, building and operating a web-based platform for both automated queries and bulk data downloads, preparing all documentation on the use of this data, and building a suite of developer tools including packages in Python and R for direct data access from workflow platforms. OpenMindat will also deploy metadata standards to establish connections to EarthCube GeoCODES. The project will create several training positions and organize a list of engagement and outreach activities, with priorities given to underrepresented groups. Computational and statistical work on large mineralogy datasets has driven the recent studies in Mineral Evolution and Mineral Ecology of which the Mindat data was a critical component. OpenMindat will democratize this research allowing anyone wishing to utilize the Mindat data for research to do so immediately. Using machine learning techniques in combination with the OpenMindat dataset raises the possibility of finding previously unseen patterns in the mineralogical diversity on the Earth and beyond, such as, comparing the mineral assemblages and localities on Earth with other planets. This project will illustrate the importance of collecting and providing certain information when analyzing mineral samples and thus cause a cultural shift in mineralogical data collection and sharing. Likewise, the studies in this project will be an example for how rapidly scientific discovery can move forward when the data are in place and coupled with advanced analytical techniques and data science expertise. The service and tools that will be developed as part of OpenMindat will themselves be open-sourced and potentially of benefit to other projects wishing to provide access to their data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.