Keeping track about various efforts that use SSSOM online - add you own if you like!

[matentzn]

Lets use this discussion to keep track of various places online that implement SSSOM one way or another. This can later be user to develop something like as showcase for documentation.

[matentzn]

https://github.com/jmillanacosta/mappings_enm

[matentzn]

https://github.com/brain-bican/metadata-schemas/tree/dev/docs/mappings

[matentzn]

https://github.com/British-Oceanographic-Data-Centre/NvsVocPrez

[matentzn]

https://github.com/MIT-LCP/mimic-code/tree/main/mimic-iv/concepts/concept_map (seems to be only reusing some elements)

[matentzn]

https://github.com/clnsmth/soso/tree/development/src/soso/data

[matentzn]

https://github.com/microbiomedata/nmdc-schema/tree/main/sssom

[matentzn]

https://github.com/qudt/qudt-public-repo/tree/main/community/mappings/SSSOM/IFC

[matentzn]

https://github.com/jhu-bids/TermHub

[matentzn]

https://github.com/tdwg/gbwg/tree/main/dwc-mixs/mapping

[matentzn]

https://github.com/geneontology/pathways2GO/tree/master/exchange/src/main/resources/YeastCyc

[matentzn]

https://docs.google.com/presentation/d/1jB1zRZvv0E_g6BPN4lpC5K3hAQt_wfziLb4TdfrlFPE/edit#slide=id.g285a545345d_2_0

[matentzn]

https://github.com/monarch-initiative/koza/pull/109/files

[matentzn]

https://github.com/dwslab/melt/blob/master/yet-another-alignment-api/src/main/java/de/uni_mannheim/informatik/dws/melt/yet_another_alignment_api/DefaultExtensions.java#L825

[matentzn]

Planteome/CO_337-groundnut-traits#7

[matentzn]

https://github.com/bridge2ai/clive

[matentzn]

https://github.com/cns-iu/onto-llm-mapping/

[matentzn]

https://github.com/BFO-Mappings/PROV-to-BFO/blob/main/prov-bfo-directmappings.ttl

[matentzn]

https://github.com/LiUSemWeb/Circular-Economy-Ontology-Catalogue/blob/main/alignments/task_a/CAMO-CEO/CAMO-CEO-sssom-AMD.ttl

[gouttegd]

Mappings between EFO and a few other ontologies, from RGD:

https://download.rgd.mcw.edu/ontology/mappings/

(produced by an ad-hoc “SSSOM File Generator” whose code is here: https://github.com/rat-genome-database/ontology-load-pipeline/blob/master/src/main/java/edu/mcw/rgd/dataload/ontologies/SSSOMGenerator.java)

[matentzn]

https://health-ri.github.io/semantic-interoperability/ontology/mappings/

[matentzn]

https://github.com/IBM/risk-atlas-nexus/

[matentzn]

https://biss.pensoft.net/article/181877/

[matentzn]

Related: https://biss.pensoft.net/article/181898

[matentzn]

https://mapping.bio/

[matentzn]

https://davidchavesfraga.com/outcomes/papers/2026/code2026llm.pdf

LLM Driven Justified Ontology Alignment

Ontology alignment is a key task for achieving semantic interoperability across heterogeneous knowledge graphs;
yet, it remains a time-consuming and expert-driven process. Recent advances in Large Language Models (LLMs)
offer new opportunities to automate this task, particularly in scenarios involving the parallel development of
multiple ontologies by automatic means that follow different approaches. In this paper, we propose an approach
for the automatic generation of ontology alignments using LLMs, producing mappings that are compliant with
the SSSOM standard and enriched with explicit justifications and provenance metadata that can support ontology
developers and domain experts in developing ontologies from multiple automatically generated versions. We
design and evaluate a set of progressively refined prompts to guide LLMs in generating structured and explainable
alignments. The approach is assessed using multiple state-of-the-art models (GPT-5.4, GPT-5 Mini, Gemini Flash,
and Gemini Pro) against a selection of ontology pairings from the OAEI Conference dataset. The evaluation
combines structural validation, standard alignment metrics (precision, recall, and F1-score), and expert qualitative
analysis. The results observed indicate that LLMs possess the potential to generate high-quality candidate
mappings, particularly for lexically similar entities. However, limitations persist in semantic discrimination,
predicate selection, and the exploitation of ontology structure. These findings indicate that LLMs are best suited
as assistive tools for knowledge engineers and domain experts in managing the parallel evolution of ontologies.

[matentzn]

https://github.com/EVORA-project/virus-taxonomy-mappings/tree/dev/mappings

[matentzn]

SSSOM cited by an ISO standard: https://www.iso.org/obp/ui/en/#iso:std:iso:21564:ed-1:v1:en

I dont know how its cited as the ISO standard is closed but, its cited.

[matentzn]

https://github.com/National-Clinical-Cohort-Collaborative/Data-Ingestion-and-Harmonization/blob/master/sssom_mapping_commons/example/sssom_mappings_1678icd10cm.csv

[matentzn]

https://github.com/KE-UniLiv/animl-ontology/blob/main/alignments/outputs/alignments.csv

[matentzn]

https://arxiv.org/html/2604.01728v1

Files dont seem valid (missing mapping_justification)

[gouttegd]

Also uses invalid format for most ID-typed fields (either full-length IRIs such as http://purl.allotrope.org/ontologies/common#AFC_0000162 or single keywords such as partOf or LogMap, instead of proper CURIEs).

And even if the file was actually valid, the scarcity of metadata in it makes this sentence of the paper looks like a joke:

All alignments are released using the Simple Standard for Sharing Ontological Mappings (SSSOM) [43], a format that provides relevant metadata to describe each mapping.

Yeah, that’s certainly what the SSSOM format allows to do… then why don’t they do it? 🙄

[jmillanacosta]

https://github.com/jmillanacosta/pysec2pri (will be moved to https://github.com/sec2pri/pysec2pri soon) collects deprecated/consolidated/split entry identifiers from databases and generates release-specific mapping sets. It also collects and qualifies (when possible) alias/synonym/etc labels.

[matentzn]

A schema mapping use case implemented in SSSOM. Bigger use of extensions slots in the wild: https://github.com/daakiv/ohdsi-gis-metadata-template/blob/main/authoring/kobotoolbox/mappings/sssom/kobo_testing_merged.sssom.tsv

I am getting to know that community and might suggest that there could be better ways to represent the transforms; but nice.