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

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

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)...

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Bibliographic Details
Published in:Geoscience data journal 2023-10, Vol.10 (4), p.489-499
Main Authors: Ma, Chao, Morrison, Shaunna M., Muscente, A. Drew, Wang, Chengbin, Ma, Xiaogang
Format: Article
Language:eng
Subjects:
Age
Data integration
Earth history
Earth science
geologic time scale
Geology
Graphs
History
Intervals
Knowledge bases (artificial intelligence)
knowledge graph
Knowledge representation
Ontology
R package
Regions
Relational data bases
Semantic web
Semantics
Strata
Stratigraphy
Time
Topology
workflow platforms
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Summary: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.
ISSN:2049-6060
2049-6060