The following section describes the contents of entries in the Bioregistry. The associated schema is encoded in Python classes using the Pydantic package which also generates a generally reusable JSON schema. Each element of the schema has associated unit tests that are run on any change to the Bioregistry to ensure that not only the schema is conformant, but also enables higher-level tests for style and content to be implemented.

Expand for a UMLS diagram of the datamodel ![](/bioregistry/img/datamodel_umls.svg)

Metadata and Properties


Each entry in the Bioregistry is annotated with a required canonical prefix (i.e., lower case, containing no strange punctuation or characters), an optional preferred prefix (i.e., containing stylization), and an optional list of alternate prefixes (i.e., synonyms).


Each includes flags if the resource for the prefix is deprecated (e.g. AERO), proprietary (e.g., NameRXN), or doesn’t contain any terms (e.g., ChIRO). These flags are helpful in subjectively deciding which resources could be considered as reliable.

Name, Description, and Homepage

All entries in the Bioregistry must have a name and description. This is important not only for active resources, but also for deprecated resources so the integrative registry can be used as a research tool and reference such as when encountering the variety of historically obscured cross references in OBO Foundry ontologies. All active resources must additionally have a homepage, while inactive resources may not have a homepage due to their respective sites being taken down. Entries are highly encouraged to include reference URLs and contributor free text comments, especially for deprecated resources to give context to readers.


License information is only readily available via the OBO Foundry and Ontology Lookup Service. Most use permissive licenses from the Creative Commons (either CC-BY or CC-0). Some licenses include license versions and some do not. There are several instances of conflict, often due to specification of the version of the Creative Commons license. Licenses only appearing a small number of times, such as CC-BY-SA, CC-BY-NC, and CC-BY-NC-SA were collapsed into “Other”. Licenses that were not appropriate for data (e.g., variants of the Apache License, GNU GPL) and custom licenses (e.g., in the case of the Human Phenotype Ontology) were also collapsed into “Other”.


The OLS is the only registry that consumes the data it references and provides detailed accessible artifacts, and is therefore the only registry that reports version information. Other lookup services like AberOWL and OntoBee consume ontologies but do not generate metadata reports. The OBO Foundry also references versioned data, but does not consume it and therefore can not report version information. Wikidata also contains version information for some databases, but is not currently viable for generally tracking version information. The other registries (e.g., MIRIAM, N2T) do not report version information as their resolution services are independent of the data versions. Alternatively, the Bioversions project sets out to be a registry-independent solution for identifying current versions of different databases, ontologies, and resources.

Local Unique Identifiers

All non-deprecated entries in the Bioregistry must include one or more example local unique identifiers. While each optionally (highly recommended) includes a regular expression pattern describing local unique identifiers, there are cases when they are difficult to generate due to the high complexity and heterogeneity of identifiers (e.g., Ensembl identifiers are highly complex), the lack of enough examples as is often the case with deprecated identifiers, or the triviality of assigning a wildcard pattern to a small enumerated namespace like FOAF, RDF, or RDFS.

While the Bioregistry imports identifier regular expression patterns from several registries (i.e., MIRIAM/, N2T, Prefix Commons, GO, and Wikidata), there exist many philosophical and practical discrepancies. A major one arises in the definition and management of redundant prefixes embedded in identifiers that is common to ontologies. For example, the colloquial local unique identifier for apoptosis in the Gene Ontology is GO:0006915, so the corresponding prefixed CURIE for this entity is GO:GO:0006915. Each registry handles cases like this slightly differently, whether it is to include the redundant prefix capitalized in the pattern, to include an extra flag in the metadata associated with the prefix, or whether to completely handle this programmatically.

In order to promote backwards compatibility with some MIRIAM prefixes, entries can contain an annotation “namespace embedded in LUI” to allow for overriding of MIRIAM metadata as well as the “banana” which explicitly states how the namespace embedded in LUI appears, for situations where it is not the same as the prefix itself (e.g., HOG).

Because there is such low consistency, the Bioregistry introduces a new field called the “banana” where the potentially redundant prefix can be explicitly enumerated, which allows for a general solution that can apply to FBbt, VariO, and other mixed-case embedded prefixes. The Bioregistry Python package includes functions for reformatting CURIEs based on the desired context (e.g., for general use, for compatibility with Further discussion on this topic can be found at

URI Format String

Each entry optionally (highly recommended) includes one or more URI format strings that can be used to generate URIs for a local unique identifier.

All active entries should have a provider, if possible. Deprecated resources likely do not have providers. Two persisting issues are due to providers being decommissioned but not removed from registries and the propagation of resolver services as providers which exacerbates the first. For example, because many ontologies use OBO-like PURLs, they are often annotated in registries as providers even though they do not resolve to anything. It is a future goal to provide more “health” checks over each registry and the Bioregistry as a whole.


Each entry includes three optional fields for when the resource is available as an ontology in the OWL (, OBO (, or OBO Graph JSON ( formats. These entries are typically imported from the OBO Foundry and OLS and are manually annotated to support large-scale ontology acquisition and processing such as with ROBOT, Pronto, or PyOBO.


Each includes two required attribution fields for the contributor and reviewer that each require a minimum of an ORCiD identifier and name with optional email address and GitHub handle. Each also includes an optional attribution field for an external contact person for the resource that could have either the ORCiD identifier, email, GitHub handle.

Ontological Relationships Between Prefixes

In addition to metadata and properties, the Bioregistry includes rich ontological relationships between prefixes in the Bioregistry as well as external prefixes.

Exact Matches

The most novel aspect of the Bioregistry is its ability to store equivalence mappings (e.g., skos:exactMatch) between Bioregistry records and external records (external records’ semantics are mediated by the metaregistry). Each entry in the Bioregistry can contain several mappings to different databases. Typically, each prefix can only have one exact match in each database. Exceptions have arisen due to duplicate records, in which case the mapping is curated to the canonical external record. These records support interoperability by enabling conversion between the standard flavor of a prefix defined by the Bioregistry and context-specific variants.

Depends On

Each entry contains a list of external entries that its associated resource depends on. This is particularly useful in ontologies, since they may either import terms from an external ontology or use external prefixes in their xrefs, provenance, or relationships. These are mostly imported from the OBO Foundry but also have an aspect of novel manual curation. While not explicitly stored in the source data, the Bioregistry python package infers the inverse relationship ( i.e. appears in) for easy access given a prefix.


While prefixes in the Bioregistry are supposed to correspond to nomenclature authorities, this is not always true because it imports from external sources that don’t enforce this constraint. For example, the Comparative Toxicogenomics Database uses NCBI Gene for naming genes and MeSH for naming diseases and chemicals. has minted 3 prefixes (ctd.gene, ctd.disease, and ctd.chemical) that mostly reflect the entries of the authorities for which they are providers. Another example is ValidatorDB, which provides information based on Protein Databank records. An even more exotic example are the Gene Ontology Annotations provided by the EBI because it provides for several types of identifiers including those from UniProt, RNA Central, and the ComplexPortal.

Therefore, prefixes in the Bioregistry can be annotated with the prefix for which they provide (e.g., ctd.gene provides mesh). Along with the part of and has canonical relationships (described below), this relationship can promote better standardization and help deconvolute multiple prefixes that use the same URI format string, which is problematic when generating high quality prefix maps for use in CURIE-IRI interconversion.

Has Canonical

While there should not be redundancies in the Bioregistry, there are several scenarios in which two or more prefixes equally correspond to the same nomenclature authority. Because these can not be merged without making the data model for the Bioregistry much more complicated and inaccessible, the has canonical annotation allows for the subjective choice of which is considered highest priority. A few scenarios in which this annotation is used are:

  1. A prefix has been replaced by another one (e.g., hgnc.genefamily was replaced by hgnc.genegroup)
  2. A prefix is redundant of another (e.g., glycomedb is redundant of glytoucan, pdb-ccd is redundant of pdb.ligand)
  3. Multiple prefixes are used by different groups for the same shared semantic space, but none of them own it (e.g.,, ena.embl)

Records in the has canonical relationship do not necessarily have the same URI format string, but if they do, this relationship further promotes choosing a deterministic prefix when parsing an IRI in combination with the provides and part of relationships.

Part Of

There are several flavors of hierarchical relationships between prefixes in the Bioregistry annotated with the part of relationship. For example, chembl.compound and are each a part of chembl and kegg.pathway and kegg.ligand are each a part of kegg. Connecting these prefixes provides significantly more context to readers of the Bioregistry. Other scenarios include:

  1. no shared prefix, has parent prefix (e.g., fbbt, fbcv, fbrf, … and flybase)
  2. has shared prefix, has dot delimiter, has a parent prefix (e.g., kegg with kegg.pathway, kegg.ligand),
  3. has shared prefix, has dot delimiter, no parent prefix (e.g., insdc.cds/insdc.gca/insdc.sra),
  4. has shared prefix, no dot delimiter, has a parent prefix (N/A)
  5. has shared prefix, no dot delimiter, no parent prefix (e.g., dlxb/dlxb, NCBIGene/NCBIProtein/NCBITaxon)
  6. prefix matching resource name and extra prefixes (e.g., biogrid and biogrid.interaction)

In several cases such as KEGG and ChEMBL, the parent prefix and child prefixes share a URI format string. Practically, the parent prefix would be sufficient, but it is often pertinent to use a subspace to denote entity types within the nomenclature. In the case of KEGG, each different entity type has a different identifier pattern. In the case of ChEMBL, all different entity types have the same identifier pattern. Ultimately, the part of relationship is the last part combined with the provides and has canonical relationships along with a small amount of additional logic to construct a high-quality prefix map.

The Rat Genome Database (RGD) constitutes an edge case with its three prefixes: rgd, rgd.qtl, and rgd.strain. The rgd prefix is more of a bucket than a parent - it includes all of the entity types (e.g., genes, articles) in the RGD that are neither quantitative trait loci (QTLs) nor strains. Because of cases like this, we have begun discussions on imposing a prefix subspacing policy at