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Identifying genomic data use with the Data Citation Explorer.

Neil Byers1, Charles Parker1, Chris Beecroft1

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Summary
This summary is machine-generated.

The Data Citation Explorer (DCE) automatically finds scientific literature using genomic data that was not formally cited. This tool improves data citation accuracy and helps track the impact of genomic data resources.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Scientific Literature Analysis

Background:

  • The exponential growth in sequencing data and publications necessitates automated methods for linking literature with genomic information.
  • Manual curation of associations between scientific literature and genomic data is becoming increasingly unfeasible due to data volume.

Purpose of the Study:

  • To introduce the Data Citation Explorer (DCE), an automated service designed to identify scientific publications that utilize genomic data without formal citation.
  • To enhance the management and discoverability of genomic data resources and their associated literature.

Main Methods:

  • Development of the Data Citation Explorer (DCE) service.
  • Utilizing automated approaches to discover and link scientific literature with relevant genomic datasets.
  • Comparing automated discovery with manual curation for identifying data-literature associations.

Main Results:

  • The DCE successfully identifies scientific literature that incorporates genomic data not formally cited, expanding the known use cases of JGI data products.
  • The service offers consistent resource coverage, metadata enrichment, and identifies conflicting metadata, surpassing manual curation limitations.
  • Implementation of the DCE reduces labor costs and improves the quality of genome metadata at the U.S. Department of Energy Joint Genome Institute (JGI).

Conclusions:

  • Automated tools like the DCE are essential for managing the complexity of modern genomic data and scientific literature.
  • The DCE enhances understanding of JGI's research impact, improves credit attribution for data generation, and encourages data sharing by demonstrating data reuse.
  • The service facilitates better tracking of genomic data impact and promotes scientific reproducibility and data accessibility.