A LinkML model describes the structure of your data. Your data can be expressed as JSON or YAML files (the default form for LinkML), or as CSVs, or as a relational database, or even a triplestore or graph database.
LinkML models are authored as YAML files. These files can be understood as data files that instantiate SchemaDefinitions in the LinkML metamodel.
The overall layout of a schema yaml file is roughly as follows:
id: https://example.org/my-schema name: my_schema <OTHER METADATA HERE> # classes are the main organization until for data; # all data records instantiate a class classes: Person: ... Organization: ... # data fields get their own section slots: name: ... email: ... age: ... # optional: schema type extensions types: AgeType: ... # enumerations enums: GenderType: ...
To illustrate we will use an example schema for modeling people and attributes about people. The full schema can be found in this repo at examples/PersonSchema
Model metadata and directives
A LinkML model/schema may have various pieces of metadata associated with it, for example:
id: https://w3id.org/linkml/examples/personinfo name: personinfo description: |- Information about people, based on [schema.org](http://schema.org) license: https://creativecommons.org/publicdomain/zero/1.0/ default_curi_maps: - semweb_context imports: - linkml:types prefixes: personinfo: https://w3id.org/linkml/examples/personinfo/ linkml: https://w3id.org/linkml/ schema: http://schema.org/ rdfs: http://www.w3.org/2000/01/rdf-schema# prov: http://www.w3.org/ns/prov# default_prefix: personinfo default_range: string ...
names, identifiers, and metadata
default_range – The default range for all slots
See also uris-and-mappings
Classes provide templates for organizing data. Data objects should instantiate classes in the schema. Each class has a set of slots (aka fields, attributes) that are applicable to it.
Classes operate in a very similar way to classes in a programming language like Python or Java. They are analogous to tables in relational databases.
Classes are defined in a
classes block at the top level of your YAML, where the key is the class name:
classes: Person: is_a: NamedThing description: >- A person (alive, dead, undead, or fictional). class_uri: schema:Person mixins: - HasAliases slots: - primary_email - birth_date - age_in_years - gender - has_employment_history - has_familial_relationships - has_medical_history
See ClassDefinition for a full list of allowed slots
Note: class names can be normal natural language noun phrases
encompassing characters such as spaces. However, when converted to
external representations, different rules will be applied, and
typically the exported name is in PascalCase. So for example, you
could call your class
named thing, but the URI for the class would
Because LinkML is described in LinkML, your schema is an
instantiation of the LinkML metamodel, and schema elements have a list
of allowed slots. So for example,
are all slots that are applicable to instances of
This is a little meta at first but you get used to it!
Slots (aka attributes, fields, columns, properties) can be associated with classes to specify what fields instances of that class can have
For example, in the schema above, instances of Person classes can have values for primary email, birthdate, etc.
In LinkML slots are “first class” and are defined independently of classes, and a slot can be used in any number of classes.
Slots are defined in a
slots block at the top level of your YAML:
slots: id: identifier: true slot_uri: schema:identifier name: slot_uri: schema:name gender: slot_uri: schema:gender range: gender_enum age_in_years: range: integer minimum_value: 0 maximum_value: 999 has_employment_history: range: EmploymentEvent multivalued: true inlined_as_list: true current_address: range: Address
You can then re-use these in your class definitions. For example, if your
Person class has a
name slot, just list it:
classes: Person: ... slots: - ... - name - ...
Note that LinkML models are “closed” by default. If a slot is not listed for a class, then data that includes an unlisted slot will be invalid.
Slots are inherited, so for example if
name is listed
as an allowed slot for
Person inherits from
name will be valid for Person. There is no need to
See SlotDefinition for a full list of which metamodel slots can be applied to slots.
The Attribute slot
As a convenience feature, you can specify slot definitions directly within a class using the
classes: Person: is_a: NamedThing description: >- A person (alive, dead, undead, or fictional). class_uri: schema:Person mixins: - HasAliases attributes: gender: slot_uri: schema:gender range: gender_enum age_in_years: range: integer minimum_value: 0 maximum_value: 999
See TypeDefinition in the metamodel.
Types in LinkML are scalar data values such as strings, integers, floats, and so on. LinkML comes with its own set of types, and these can be extended.
For example, you may represent chemical formulae as strings in your model, but if you provide an explicit type that maps to string, it makes the intended meaning clearer, and different applications can operate on these differently:
chemical formula value: uri: xsd:string base: str description: A chemical formula
The core enumeration model is the same as for familiar systems, where there is a set of allowed string values:
enums: FamilialRelationshipType: permissible_values: SIBLING_OF: PARENT_OF: CHILD_OF:
You can also make your enums into a ticher controlled vocabulary, with definitions built in:
enums: FamilialRelationshipType: permissible_values: SIBLING OF: description: A family relationship where the two members have a parent on common PARENT OF: description: A family relationship between offspring and their parent CHILD OF: description: inverse of the PARENT_OF relationship
(note you can include spaces in your enums if you like)
LinkML goes beyond most frameworks and allows your enums to be backed by external ontologies. For example, this enum is backed by GSSO
prefixes: GGSO: http://purl.obolibrary.org/obo/GSSO_ enums: GenderType: permissible_values: nonbinary man: meaning: GSSO:009254 nonbinary woman: meaning: GSSO:009253 transgender woman: meaning: GSSO:000384 transgender man: meaning: GSSO:000372 cisgender man: meaning: GSSO:000371 cisgender woman: meaning: GSSO:000385
Elements of a schema can be partitioned into named subsets. These have no semantic meaning, but they can be useful for tagging parts of a schema for different purposs.