2024/01/05 by W. M. Davis, C. R. Hunt · 1 voice
Computer Science · Earth and Planetary Sciences · #Geochemistry and Geologic Mapping #Geological Modeling and Analysis #Seismology and Earthquake Studies
paper · doi:10.1016/j.acags.2023.100151
openalex publication_date 2024/01/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/03
The increasing scale and diversity of seismic data, and the growing role of big data in seismology, has raised interest in methods to make data exploration more accessible. This paper presents the use of knowledge graphs (KGs) for representing seismic data and metadata to improve data exploration and analysis, focusing on usability, flexibility, and extensibility. Using constraints derived from domain knowledge in seismology, we define semantic models of seismic station and event information used to construct the KGs. Our approach utilizes the capability of KGs to integrate data across many sources and diverse schema formats. We use schema-diverse, real-world seismic data to construct KGs with millions of nodes, and illustrate potential applications with three big-data examples. Our findings demonstrate the potential of KGs to enhance the efficiency and efficacy of seismological workflows in research and beyond, indicating a promising interdisciplinary future for this technology.