Skip to content

Biomappings

Data integration Semantic interoperability

Biomappings Case Study Infobox

  • Author: Charles Tapley Hoyt (@cthoyt)
  • Last updated: 2026-08-04
  • Mapping Type: Mapping Type
  • Status of this case study: Status

Biomappings: community-driven, semi-automated curation at scale

Short title

Biomappings

Summary

Biomappings is a community-driven repository of predicted and curated semantic mappings that follows the open data, open code, open infrastructure (O3) guidelines.

It builds on SSSOM Curator, a suite of tools for predicting and curating semantic mappings encoded in the Simple Standard for Sharing Ontological Mappings (SSSOM). SSSOM Curator has three major components:

  1. A semantic mappings prediction workflow, with implementations for lexical matching and lexical embedding similarity and extensibility for additional implementations
  2. A (local) web-based curation interface for quick triage of predicted semantic mappings that supports full curator provenance
  3. A set of tools for data integrity testing, summarization, and export

Domain

Primarily biomedicine, but domain-agnostic.

Use case category

Semantic interoperability (shared understanding of data across multiple systems)

Purpose of the mapping

The Biomappings repository fills gaps where first-party semantic mappings are not available. As such, Biomappings is typically used in conjunction with first-party semantic mappings (e.g., originating from inside an ontology, distributed with a database) when doing data integration (e.g., such as when constructing a knowledge graph). The Semantic Mapping Reasoner and Assembler (SeMRA) operationalizes such a workflow.

Type of mapped resources

This resource primarily deals with entity mappings (both classes and instances) from ontologies, databases, controlled vocabularies, taxonomies, and other related information artifacts.

Additionally, Biomappings covers a small number of simple schema mappings (where predicates can be mapped).

Semantic mappings curated in Biomappings have been demonstrated to be incorporated in upstream resources such as the Mondo Disease Ontology, Uber Anatomy Ontology (Uberon), and Cell Ontology (CL).

Tools used for creating the mapping

Because Biomappings is built on SSSOM Curator, any automated matching workflow can be incorporated. By default, it uses a simple workflow based on Gilda, and additionally includes wrappers around other named entity recognition and named entity normalization workflows such as spaCy, ScispaCy, and GLiNER, and can be extended to other workflows. It also implements simple workflows for text embedding-based matching.

Type of mapping relations

Most commonly a combination of one-to-one, one-to-many, many-to-one, and many-to-many (which are induced by the combination of the curated mappings in Biomappings with the first-party ones, when available):

  • skos:exactMatch
  • skos:narrowMatch
  • skos:broadMatch

A full breakdown (linked to the repository, which is always up-to-date):

Biomappings summary

Examples (samples) of different types of mapping implementations

The SSSOM Curator README contains examples on how to predict new mappings: https://github.com/cthoyt/sssom-curator#-getting-started

Custom mapping workflows have been implemented here: https://github.com/biopragmatics/biomappings/tree/main/scripts