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Near-Real-Time Integration of Multi-Source Seismic Data.

José Melgarejo-Hernández1, Paula García-Tapia-Mateo1, Juan Morales-García1

  • 1Department of Software and Computing Systems, Universidad de Alicante (UA), 03690 Alicante, Spain.

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|January 28, 2026
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Summary
This summary is machine-generated.

This study introduces an automated framework to integrate global seismic data from diverse sources, overcoming format and access challenges. The system ensures reliable, near-real-time earthquake catalog construction for improved hazard assessment and research.

Keywords:
FAIR principlesnear-real-time systemsopen APIsseismic data integration

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Area of Science:

  • Geophysics and Earth Sciences
  • Data Science and Informatics
  • Seismology and Earthquake Science

Background:

  • Heterogeneity in seismic data from providers like USGS, EMSC, and IGN hinders real-time monitoring and hazard assessment.
  • Differences in data formats, update frequencies, and access methods pose significant challenges for unified seismic data acquisition.
  • Need for a standardized, automated solution to integrate global seismic information for improved earthquake studies.

Purpose of the Study:

  • To present a modular and automated framework for scheduled, near-real-time ingestion of global seismic data.
  • To overcome limitations posed by heterogeneous data sources using open APIs and semi-structured web data.
  • To ensure data adheres to FAIR principles for enhanced accessibility and interoperability.

Main Methods:

  • Developed a Docker-based architecture for automated data retrieval, harmonization, and storage.
  • Utilized a cron-based scheduler for regular data ingestion from heterogeneous sources.
  • Standardized data into a unified schema, validated for duplicates, and stored in a relational database.

Main Results:

  • The system demonstrated 100% availability across all sources during a seven-day deployment.
  • Successfully integrated 4533 new seismic events and identified 595 duplicate detections.
  • Maintained stable operation, proving the framework's robustness for multi-source seismic catalog integration.

Conclusions:

  • The proposed framework provides a robust foundation for automated integration of multi-source seismic catalogs.
  • Enables the construction of more comprehensive and globally accessible earthquake datasets.
  • Supports enhanced data-driven research and situational awareness for earthquake monitoring and hazard assessment worldwide.