Incorporate temporal topology in a deep-time knowledge base to facilitate data-driven discovery in geoscience

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Geoscience Data Journal Pub Date : 2022-07-17 DOI:10.1002/gdj3.171
Chao Ma, Shaunna M. Morrison, A. Drew Muscente, Chengbin Wang, Xiaogang Ma
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引用次数: 1

Abstract

Data-driven discovery in geoscience requires an enormous amount of FAIR (findable, accessible, interoperable and reusable) data derived from a multitude of sources. Many geology resources include data based on the geologic time scale, a system of dating that relates layers of rock (strata) to times in Earth history. The terminology of this geologic time scale, including the names of the strata and time intervals, is heterogeneous across data resources, hindering effective and efficient data integration. To address that issue, we created a deep-time knowledge base that consists of knowledge graphs correlating international and regional geologic time scales, an online service of the knowledge graphs, and an R package to access the service. The knowledge base uses temporal topology to enable comparison and reasoning between various intervals and points in the geologic time scale. This work unifies and allows the querying of age-related geologic information across the entirety of Earth history, resulting in a platform from which researchers can address complex deep-time questions spanning numerous types of data and fields of study.

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将时间拓扑整合到一个深度时间知识库中,以促进地球科学数据驱动的发现
地球科学中的数据驱动发现需要大量来自多种来源的FAIR(可查找、可访问、可互操作和可重复使用)数据。许多地质资源包括基于地质时间尺度的数据,这是一种将岩石(地层)层与地球历史时期联系起来的年代测定系统。这种地质时间尺度的术语,包括地层和时间间隔的名称,在数据资源中是异构的,阻碍了有效和高效的数据集成。为了解决这个问题,我们创建了一个深度时间知识库,该库由关联国际和区域地质时间尺度的知识图、知识图的在线服务和访问该服务的R包组成。该知识库使用时间拓扑来实现地质时间尺度中的各种区间和点之间的比较和推理。这项工作统一并允许查询整个地球历史上与年龄相关的地质信息,从而形成了一个平台,研究人员可以从中解决跨越多种类型数据和研究领域的复杂深层次问题。
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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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