Data from: Knowledge graphs for seismic data and metadata

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.