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A new structure for representing and tracking version information in a deep time knowledge graph.

Authors :
Ma, Xiaogang
Ma, Chao
Wang, Chengbin
Source :
Computers & Geosciences. Dec2020, Vol. 145, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

Ontologies and vocabularies are an effective way to promote data interoperability in open data and open science. The deep time knowledge graph is one of the most discussed and studied topics in geoscience ontologies and vocabularies. The continuous evolution of deep time concepts calls for a mechanism of version control and organization to reduce the semantic ambiguity. In this paper we propose a new structure for version control and tracking of concepts, attributes and topological relationships in the deep time knowledge graph. In our work we have reused the existing ontologies for geologic time scale and vocabularies for the International (Chrono)stratigraphic Chart (ISC). Through the new structure, we are able to represent the whole version history of the ISC charts (from 2004 to 2018) in a single knowledge graph. Moreover, the resulting knowledge graph is consistent with the existing ontologies and vocabularies. Experiments of SPARQL queries prove the efficiency of this structure for version tracking of concepts and attributes. We are now extending the knowledge graph with concepts from regional and local geologic time standards, such as North America, Europe, Britain, China, and Australia, and building a graphic user interface for the services. In a future work, we will implement the knowledge graph in data integration workflows. We hope this research will spur more discussion and development of methods for version control of knowledge graphs in geoscience and other disciplines. • A novel structure is designed for version control in the deep time knowledge graph. • Existing ontologies and vocabularies are fully reused and accredited. • A vocabulary is built to include all versions of international geologic time scale. • Vocabulary service allows tracking version information of concepts and attributes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00983004
Volume :
145
Database :
Academic Search Index
Journal :
Computers & Geosciences
Publication Type :
Academic Journal
Accession number :
146754260
Full Text :
https://doi.org/10.1016/j.cageo.2020.104620