OPERAS Metrics Database

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Authors: Cristian Garcia, OPERAS
Cited by: 0

Abstract

OPERAS Database Archive Description This archive contains a complete PostgreSQL database dump for OPERAS Metrics, a service that offers usage and impact information for published Open Access books. Designed with the nuanced needs of Social Sciences and Humanities in mind, OPERAS Metrics consolidates diverse data sources into a single, transparent interface. The database supports the aggregation of metrics not only from publisher websites but also from multiple sites where books are available, providing comprehensive impact assessment for SSH scholarly publications. Database Structure The database (operas_db) is organized in a hierarchical structure with strict dependency ordering: Reference Tables: continent: Geographic continental classifications locale: Language and regional locale definitions namespace: Metadata namespace classifications source: Data source identifiers type: Metric and data type definitions version: Version tracking information Dependent Tables: country: Country data (depends on continent) measure: Research assessment metrics and indicators (depends on namespace, source, type, version) publisher: Publisher information measure_description: Multilingual descriptions of measures (depends on measure and locale) event: Event-based data linked to measures and countries (depends on measure and country) Supporting Data: doi_to_publisher: DOI prefix to publisher name mappings (includes dedicated CSV import) Contents database_creation.sh: Automated restoration script 170936/: Directory containing SQL files schema.sql: Complete database schema with tables, constraints, and indexes Individual .sql files for each table's data prefix_publishers.csv: DOI prefix mappings for publisher identification

Fields of Study & Subjects

scientometrics and bibliometrics research Publishing and Scholarly Communication Library Science and Information

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
6 February 2026
Language
EN
Document type
Dataset