EarthCube Data Discovery Studio: A gateway into geoscience data discovery and exploration with Jupyter notebooks

EarthCube Data Discovery Studio: A gateway into geoscience data discovery and exploration with Jupyter notebooks
复制标题

EarthCube Data Discovery Studio:使用 Jupyter Notebook 进行地球科学数据发现和探索的门户

DOI:
10.1002/cpe.6086
复制
发表时间:
2020
期刊:
Concurrency and Computation: Practice and Experience
影响因子:
--
通讯作者:
Stocks, Karen
Stocks, Karen
中科院分区:
--
文献类型:
--
作者:
Valentine, David;Zaslavsky, Ilya;Richard, Stephen;Meier, Ouida;Hudman, Gary;Peucker‐Ehrenbrink, Bernhard;Stocks, Karen

文献摘要

参考文献

被引文献

相似文献

EarthCube Data Discovery Studio(DDStudio)是一个跨领域的地球科学数据发现和探索门户。它索引了从40多个来源收集的超过165万条元数据记录,并利用可配置的元数据增强管道,使用文本分析和集成的地球科学本体来增强元数据内容。元数据增强器添加带有标识符的关键字,这些标识符将资源映射到科学领域、地理空间特征、测量变量和其他特征。管道从元数据中提取空间位置和时间参考,以生成结构化的空间和时间范围,维护每个元数据增强的起源,并允许用户验证。语义增强的元数据记录可作为标准ISO 19115/19139 XML文档通过标准搜索界面访问。搜索界面支持空间、时间和基于文本的搜索,以及用户贡献、标准化和更新资源描述的功能,并将搜索结果组织成可共享的集合。DDStudio通过允许用户为任何发现的数据集或数据集集集合启动驻留在多个平台上的MySQL笔记本,从而将资源发现和探索连接起来。DDStudio通过几个地球科学领域的一系列例子,展示了如何将目录中的搜索结果直接链接到软件工具和环境,从而缩短了科学研究的时间。网址:datadiscoverystudio.org
EarthCube Data Discovery Studio (DDStudio) is a crossdomain geoscience data discovery and exploration portal. It indexes over 1.65 million metadata records harvested from 40+ sources and utilizes a configurable metadata augmentation pipeline to enhance metadata content, using text analytics and an integrated geoscience ontology. Metadata enhancers add keywords with identifiers that map resources to science domains, geospatial features, measured variables, and other characteristics. The pipeline extracts spatial location and temporal references from metadata to generate structured spatial and temporal extents, maintaining provenance of each metadata enhancement, and allowing user validation. The semantically enhanced metadata records are accessible as standard ISO 19115/19139 XML documents via standard search interfaces. A search interface supports spatial, temporal, and text‐based search, as well as functionality for users to contribute, standardize, and update resource descriptions, and to organize search results into shareable collections. DDStudio bridges resource discovery and exploration by letting users launch Jupyter notebooks residing on several platforms for any discovered datasets or dataset collection. DDStudio demonstrates how linking search results from the catalog directly to software tools and environments reduces time to science in a series of examples from several geoscience domains. URL: datadiscoverystudio.org
DOI: 10.1039/9781847551047-00298
发表时间: 1973-05
影响因子: 5.2
作者:
David M. Rubin;Thomas H. Harris;David W. Jones;D. P. Sachs;Clarence A. Schoenfeld
通讯作者: David M. Rubin;Thomas H. Harris;David W. Jones;D. P. Sachs;Clarence A. Schoenfeld
DOI: 10.1093/nar/gkw1128
发表时间: 2017-01-04
影响因子: 14.9
作者:
Mungall CJ;McMurry JA;Köhler S;Balhoff JP;Borromeo C;Brush M;Carbon S;Conlin T;Dunn N;Engelstad M;Foster E;Gourdine JP;Jacobsen JO;Keith D;Laraway B;Lewis SE;NguyenXuan J;Shefchek K;Vasilevsky N;Yuan Z;Washington N;Hochheiser H;Groza T;Smedley D;Robinson PN;Haendel MA
通讯作者: Haendel MA
生物和化学海洋学数据管理办公室(BCO-DMO)简介
DOI: --
发表时间: 2007
期刊:
影响因子: --
作者:
C. Chandler;D. M. Glover;R. Groman;P. Wiebe
通讯作者: P. Wiebe
服务器
DOI: --
发表时间: 2021
期刊: Running Microsoft Workloads on AWS
影响因子: --
作者:
Ryan Pothecary
通讯作者: Ryan Pothecary
DOI: --
发表时间: 2018
期刊:
影响因子: --
作者:
K. Casey
通讯作者: K. Casey