项目来源

美国国家科学基金(NSF)

项目主持人

Xiaogang Ma

项目受资助机构

Regents of the University of Idaho

项目编号

2126315

立项年度

2021

立项时间

未公开

研究期限

未知 / 未知

项目级别

国家级

受资助金额

792475.00美元

学科

未公开

学科代码

未公开

基金类别

Standard Grant

关键词

EarthCube ; EXP PROG TO STIM COMP RES

参与者AI

林铭杰;翁岳鹏;陈明贤;游舒羽;马小刚;张继吟

参与机构AI

福建农林大学;爱达荷大学

项目标书摘要：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.