NOMAD¶

NOMAD schemas have comparable concepts about reusable objects (sections) with typed properties (quantities). Example:

definitions:
  sections:
    Element:
      quantities:
        label:
          type: str
        density:
          type: np.float64
          unit: g/cm**3
        isotopes:
          type: int
          shape: ['*']
    Composition:
      quantities:
        composition:
          type: str
      sub_sections:
        elements:
          section: Element
          repeats: true

can be expressed as the following JSON Schema (formated as yaml)

definitions:
  sections:
    Element:
      properties:
        label:
          type: string
        density:
          type: number
          unit: g/cm**3
        isotopes:
          type: array
          items:
            type: integer
          format: table
    Composition:
      properties:
        composition:
          type: str
        elements:
          type: array
          format: table
          items:
            $ref: '#/definitions/sections/Element'

generating/validating the same JSON/YAML data (see also playground), e.g.

composition: H2O
elements:
  - label: H
    density: 8.375e-05
    isotopes: [1, 2, 3]
  - label: O
    density: 1.141
    isotopes: [16, 17, 18]

by using the following mapping (work in progress):

NOMAD Schema	JSON Schema	Note
quantities	properties
type (int, str, ...)	type (integer, string, ...)	specific python types like `np.int32` can be annotated in the JSON-LD context
unit, m_annotations, ..	format / options	additional custom annotation keywords can be kept or mapped to format and options
shape[*]	type: array, items: type: number	specific values can be mapped to minItems and maxItems
shape[,]	type: array, items: type: array, items: type: number	nested array
sub_sections: ... : repeats: true	type: array, items: type: object	array of objects
...