SPI-Hub

SPI-Hub provides decision support by aggregating and encoding journal policies and practices to inform journal selection and trustworthiness assessment in the health sciences.


Key Features:

  • Knowledge Management Journal Record™: Captures detailed information about journal policies and practices using 25 metadata fields that represent best publishing practices.
  • Data Framework: Aggregates and organizes publication-related information from multiple sources to support decision support functionality.
  • Semi-Automated Data Collection: Populates metadata fields through a semi-automated process using custom programming to access content efficiently.
  • Extensive Database: Maintains a repository of over 24,000 health sciences journal records.
  • Quality Assessment: Incorporates multiple quality points per journal to provide publication recommendations and holistic trustworthiness assessments.
  • Automation Efficiency: Employs automated and semi-automated methods to streamline data collection while preserving data quality.

Scientific Applications:

  • Journal Selection: Identifies journals aligned with specific research focus and publication goals based on encoded policies and practices.
  • Trustworthiness Assessment: Evaluates journal credibility using multiple quality points to help avoid predatory or low-quality publications.
  • Best Practices Guidance: Provides actionable recommendations grounded in the 25 metadata fields representing publishing best practices.

Methodology:

Semi-automated data collection using custom programming and automated methods to populate a 25-field Knowledge Management Journal Record™; a data framework aggregates and organizes publication-related information from multiple sources.

Topics

Details

Added:
1/18/2021
Last Updated:
2/21/2021

Operations

Publications

Koonce TY, Blasingame MN, Zhao J, Williams AM, Su J, DesAutels SJ, Giuse DA, Clark JD, Fox ZE, Giuse NB. SPI-Hub™: a gateway to scholarly publishing information. Journal of the Medical Library Association. 2020;108(2). doi:10.5195/jmla.2020.815. PMID:32256240. PMCID:PMC7069808.