Enhancing RAMOSE, a framework for implementing REST APIs and semantic-actionable outputs over data sources

Abstract

Scholarly infrastructures increasingly expose their data through REST APIs that follow shared specifications, such as the Scientific Knowledge Graphs - Interoperability Framework (SKG-IF), which defines a common data model, exchange format, and REST API for research information. Implementing such specifications over existing data sources, however, requires a development effort that many open infrastructures cannot afford. RAMOSE, the RESTful API Manager Over SPARQL Endpoints, is an open-source Python framework that reduces this effort by turning a declarative configuration file into a documented REST API over RDF triplestores. This article presents its second major version, which addresses nine new requirements. The new features include query orchestration across multiple SPARQL endpoints and non-RDF sources, with joins across their results; pluggable output formats and request parameters; pagination and caching; OpenAPI export; and write operations, with authentication for both API consumers and protected endpoints. A built-in module packages the format and filters that SKG-IF prescribes, letting a provider expose a compliant endpoint only through configuration. A functional comparison with nine similar tools, grounded in reproducible tests, shows that RAMOSE is the only one able to serve both RDF and non-RDF sources simultaneously within a single API operation, joining their results on arbitrary keys. Its first version served the OpenCitations REST APIs, which peaked at almost 38 million monthly requests between May 2025 and May 2026. The new version extends this deployment to the OpenCitations SKG-IF endpoint and is adopted by the GRAPHIA project to onboard data sources into its SKG-IF-based federation.