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

EarthCube 功能:OpenMindat - 开放获取和可互操作的矿物学数据,以扩大社区访问并推进地球科学研究

基本信息

  • 批准号:
    2126315
  • 负责人:
  • 金额:
    $ 79.25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-01 至 2025-08-31
  • 项目状态:
    未结题

项目摘要

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.
Mindat是一个社区驱动的、免费访问的在线数据库,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可以免费供用户浏览,但数据访问和下载的机器界面从未完全建立。OpenMindat项目将首次允许自动查询和下载该数据资源用于学术研究。这一努力包括技术发展以建立开放的数据访问,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,以及对地球立方和广大地球科学界的外联活动。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已经是地球科学教育的重要资源。目前,该网站每月的页面浏览量超过350万次。OpenMindat中的这些新数据访问工具将使课堂、实验室甚至家中的矿物学数据的教育访问变得更加容易,让学生有更多的机会进行矿物学数据科学实验。OpenMindat项目将涉及将所有适当的Mindat数据转移到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,准备有关使用这些数据的所有文档,并构建一套开发人员工具,包括Python和R软件包,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,并组织一系列参与和外联活动,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矿物演化和矿物生态学的最新研究,其中Mindat数据是一个关键组成部分。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数据集结合使用,可以在地球及其他地方的矿物多样性中发现以前看不见的模式,例如将地球上的矿物组合和位置与其他行星进行比较。该项目将说明在分析矿物样品时收集和提供某些信息的重要性,从而引起矿物学数据收集和共享的文化转变。同样,该项目中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推进。作为OpenMindat一部分开发的服务和工具本身将是开源的,并可能对希望提供对其数据访问的其他项目有益。该奖项反映了NSF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。

项目成果

期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Geoweaver_cwl: Transforming geoweaver AI workflows to common workflow language to extend interoperability
  • DOI:
    10.1016/j.acags.2023.100126
  • 发表时间:
    2023-06-15
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Kale, Amruta;Sun, Ziheng;Ma, Xiaogang
  • 通讯作者:
    Ma, Xiaogang
Data sharing: more science unions must act
数据共享:更多科学联盟必须采取行动
  • DOI:
    10.1038/d41586-022-03233-2
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    64.8
  • 作者:
    Ma, Xiaogang;Wyborn, Lesley;Hodson, Simon
  • 通讯作者:
    Hodson, Simon
A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications
  • DOI:
    10.1016/j.apgeochem.2022.105273
  • 发表时间:
    2022-03
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Yuyang He;You Zhou;Tao Wen;Shuang Zhang;Fang Huang;Xinyu Zou;Xiaogang Ma;Yueqin Zhu
  • 通讯作者:
    Yuyang He;You Zhou;Tao Wen;Shuang Zhang;Fang Huang;Xinyu Zou;Xiaogang Ma;Yueqin Zhu
OpenMindat : Open and FAIR mineralogy data from the Mindat database
OpenMindat:Mindat 数据库中开放且公平的矿物学数据
  • DOI:
    10.1002/gdj3.204
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    3.2
  • 作者:
    Ma, Xiaogang;Ralph, Jolyon;Zhang, Jiyin;Que, Xiang;Prabhu, Anirudh;Morrison, Shaunna M.;Hazen, Robert M.;Wyborn, Lesley;Lehnert, Kerstin
  • 通讯作者:
    Lehnert, Kerstin
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Xiaogang Ma其他文献

Biogas residue biochar still had ecological risks to the ultisol: evidence from soil bacterial communities, organic carbon structures, and mineralization
沼渣生物炭对有机土仍然具有生态风险:来自土壤细菌群落、有机碳结构和矿化的证据
  • DOI:
    10.1007/s11368-022-03269-x
  • 发表时间:
    2022-08
  • 期刊:
  • 影响因子:
    3.6
  • 作者:
    Ping Cong;Xuebo Zheng;Lanfang Han;Liying Chen;Jintao Zhang;Wenjing Song;Jianxin Dong;Xiaogang Ma
  • 通讯作者:
    Xiaogang Ma
Examining fingerprint trace elements in cassiterite: Implications for primary tin deposit exploration
检查锡石中的指纹微量元素:对原生锡矿床勘探的影响
  • DOI:
    10.1016/j.oregeorev.2022.105082
  • 发表时间:
    2022-10
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Chengbin Wang;Kui-Dong Zhao;Jianguo Chen;Xiaogang Ma
  • 通讯作者:
    Xiaogang Ma
Using a 3D heat map to explore the diverse correlations among elements and mineral species
使用 3D 热图探索元素和矿物种类之间的不同相关性
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Jiyin Zhang;Xiang Que;Bhuwan L. Madhikarmi;Robert M. Hazen;Jolyon P. Ralph;A. Prabhu;S. Morrison;Xiaogang Ma
  • 通讯作者:
    Xiaogang Ma
Salinity-dependent mitigation of naphthalene toxicity in migratory Takifugu obscurus juveniles: Implications for survival, oxidative stress, and osmoregulation.
迁徙暗纹东方鲀幼鱼中萘毒性的盐度依赖性缓解:对生存、氧化应激和渗透压调节的影响。
  • DOI:
    10.1016/j.scitotenv.2023.165248
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    J. Wang;Mengya Li;Xinnan Zhuo;Xiaojian Gao;Xiaogang Ma;Xiaojun Zhang
  • 通讯作者:
    Xiaojun Zhang
A Boundary Distance-Based Symbolic Aggregate Approximation Method for Time Series Data
一种基于边界距离的时间序列数据符号集合逼近方法
  • DOI:
    10.3390/a13110284
  • 发表时间:
    2020-11
  • 期刊:
  • 影响因子:
    2.3
  • 作者:
    Zhenwen He;Shirong Long;Xiaogang Ma;Hong Zhao
  • 通讯作者:
    Hong Zhao

Xiaogang Ma的其他文献

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{{ truncateString('Xiaogang Ma', 18)}}的其他基金

RII Track-2 FEC: Leveraging Big Data to Improve Prediction of Tick-Borne Disease Patterns and Dynamics
RII Track-2 FEC:利用大数据改进对蜱传疾病模式和动态的预测
  • 批准号:
    2019609
  • 财政年份:
    2020
  • 资助金额:
    $ 79.25万
  • 项目类别:
    Cooperative Agreement
Elements: Software: HDR: A knowledge base of deep time to facilitate automated workflows in studying the co-evolution of the geosphere and biosphere
要素:软件:HDR:促进研究地圈和生物圈共同进化的自动化工作流程的深度时间知识库
  • 批准号:
    1835717
  • 财政年份:
    2018
  • 资助金额:
    $ 79.25万
  • 项目类别:
    Standard Grant
Student Support for the 2018 U.S. Semantic Technologies Symposium (US2TS)
2018 年美国语义技术研讨会 (US2TS) 的学生支持
  • 批准号:
    1815526
  • 财政年份:
    2017
  • 资助金额:
    $ 79.25万
  • 项目类别:
    Standard Grant

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