ASDF Schemas¶

ASDF uses JSON Schema to perform validation of ASDF files. Schema validation of ASDF files serves the following purposes:

Ensures conformity with core data types defined by the ASDF Standard. ASDF readers can detect whether an ASDF file has been modified in a way that would render it unreadable or unrecognizable.
Enables interoperability between ASDF implementations. Implementations that recognize the same schema definitions should be able to interpret files containing instances of data types that conform to those schemas.
Allows for the definition of custom data types. External software packages can provide ASDF schemas that correspond to types provided by that package, and then serialize instances of those types in a way that is standardized and portable.

All ASDF implementations must implement the types defined by the core schemas and validate against them when reading files. 1 The ASDF Standard also defines two other categories of schemas, which are optional for ASDF implementations:

unit
time

The ASDF Standard also defines two metaschemas which are used to validate the ASDF schemas themselves:

More information on the schemas defined by ASDF can be found in ASDF Schema Definitions.

Schema Implementation¶

ASDF schemas are encoded in YAML and conform to a superset of JSON Schema called YAML Schema. The version of YAML supported by ASDF is 1.1. Accordingly, all schemas begin with the following YAML header:

%YAML 1.1
---

The following top-level attributes are required for all ASDF schemas: 2

$schema: Indicates the metaschema definition used to validate this schema
id: A name that uniquely identifies the schema
tag: The YAML tag corresponding to the type described by this schema

Each of these attributes is described in more detail below.

$schema¶

ASDF schemas use the top-level $schema attribute to declare the metaschema that is used to validate the schema itself. Most custom ASDF schemas will conform to YAML Schema defined by the ASDF Standard, and so will have the following top-level attribute:

$schema: "http://stsci.edu/schemas/yaml-schema/draft-01"

Some ASDF schemas use the ASDF metaschema instead (e.g. ndarray). It is also possible to create custom metaschemas, although these should always inherit from either YAML Schema or the ASDF metaschema. 3

Some ASDF implementations may choose to validate the schemas themselves (e.g. as part of a regression testing suite). The $schema keyword should be used to determine the metaschema to be used for validation. All schemas should also validate successfully against YAML Schema.

id¶

The id represents the globally unique name of the schema. It must be a valid URI and cannot be an empty string or an empty fragment (e.g. #). See Naming Conventions for conventions to ensure global uniqueness.

While the id must be a valid URI, it does not have to describe a real location on disk or on a network. For example, the id values for all schemas in the ASDF Standard begin with the prefix http://stsci.edu/schemas/asdf/. However, as of this writing, none of the schemas are actually hosted at that location.

The id keyword is used for reference resolution both within a schema and between schemas. Relative references within a schema are resolved against the id of that schema. A reference to an external schema uses the id of that schema. See References below for additional information.

Each ASDF implementation must define how to resolve a schema id to a real resource that contains the schema itself. This could be done in a variety of ways, but the following seem like the most likely possibilities:

Resolve the id to a real network location (assuming the schema is actually hosted at that location)
Map the id to a file location on disk that contains the schema

Other mappings are possible in theory. For example, a schema could be stored in a string literal as part of a program.

tag¶

The tag attribute is used by ASDF to associate an instance of a data type in an ASDF file with the appropriate schema to be used for validation. It is a concept from YAML (see the documentation).

Libraries that provide custom schemas must ensure that the YAML tag that is written for a particular data type must match the tag attribute in the schema that corresponds to the data type. Tags must conform to the tag URI scheme which is defined in RFC 4151, but are otherwise perfectly arbitrary. However, certain Naming Conventions are recommended in order to facilitate a mapping between tag and id attributes.

ASDF implementations must be able to map tag attributes to the corresponding schema id. The way that this mapping is defined is up to individual implementations. However, if the Naming Conventions are followed, most implementations will be able to perform prefix matching and replacement.

While the id attribute will almost certainly become required in a future version of the ASDF Standard, the tag attribute may remain optional. This is because schemas can be referenced by id without necessarily referring to a particular tagged type in the YAML representation.

Descriptive information¶

Each schema may optionally contain descriptive fields: title, description and examples. These fields may contain core markdown syntax (which will be used for the purposes of rendering schema documentation by, for example, sphinx-asdf).

title: A one-line summary of the data type described by the schema
description: A lengthier prose description of the schema
examples: A list of example content that conforms to the schema, illustrating how to use it.

References¶

A particular ASDF schemas can contain references to other ASDF schemas. References are encoded by using the $ref attribute anywhere in the tree. While JSON Schema references are purely based on id, ASDF implementations must be able to resolve references using both id and tag attributes.

The resolution of id or tag references to actual schema files is up to individual implementations. It is recommended for ASDF implementations to use a two-phase mapping: one from tag to id, and another from id to an actual schema resource. In most cases, the id will be resolved to a location on disk (e.g. to a schema file that is installed in a known location). However, other scenarios might involve schemas that are hosted on a network, or schemas that are embedded in source files as string literals.

Naming Conventions¶

Schema id attributes must be valid URIs. Schema tag attributes must be valid URIs that conform to the tag URI scheme defined in RFC 4151 Aside from these requirements, assignment of these attributes is perfectly arbitrary. However, certain conventions are strongly recommended in order to ensure uniqueness and to enable a simple correspondence between the id and tag attributes. These conventions are described below.

All schema ids should encode the following information:

organization: Indicates the organization that created the schema
standard: The “standard” this schema belongs to. This will usually correspond to the name of the software package that provides this schema.
name: The name of the data type corresponding to this schema.
version: The version of the schema. See Versioning Conventions for more details.

Consider the schemas from the ASDF Standard as an example. In this case, the organization is stsci.edu, which is the web address of the organization that created the schemas. The standard is asdf. Each individual schema in the ASDF Standard has a different name field. In the case of the ndarray data type, for example, the name is core/ndarray. The version of ndarray is 1.0.0. Some other types in the ASDF Standard have multiple versions, such as quantity-1.0.0 and quantity-1.1.0.

While schema ids can be any valid URI, under this convention they always begin with http://. The general format of the id attribute becomes:

http://<organization>/schemas/<standard>/<name>-<version>

Continuing with the example of ndarray, we have:

id: "http://stsci.edu/schemas/asdf/core/ndarray-1.0.0"

The idea behind the convention for id is that it should be possible (in principle if not in practice) for schemas to be hosted at the corresponding URL. This motivates the choice of the organization’s web address as the organization component. However, this is not a requirement. The primary objective is to create a globally unique id.

Given the components defined above, the tag definition follows in a straightforward manner. The generic tag URI template is:

tag:<organization>:<standard>/<name>-<version>

Considering ndarray once again, we have:

tag: "tag:stsci.edu:asdf/core/ndarray-1.0.0"

Following the naming convention for both id and tag attributes enables a simple mapping from tag to id. In this case, simply take the prefix tag:stsci.edu: and replace it with http://stsci.edu/schemas/.

Designing a new tag and schema¶

This section will walk through the development of a new tag and schema. In the example, suppose we work at the Example Organization, which can be found on the world wide web at example.org. We’re developing a new instrument, foo, and we need a way to define the specialized metadata to describe the exposures that it will be generating.

According to the Naming Conventions, our tag and id attributes will consist of the following components:

organization: example.org
standard: foo
name: metadata
version: 1.0.0 (by convention the starting version for all new schemas)

So, for our example instrument metadata, the tag is:

tag:example.org:foo/metadata-1.0.0

Each tag should be associated with a schema in order to validate it. Each schema must also have a universally unique id, which is in the form of unique URI.

Note that this URI doesn’t actually have to resolve to anything. In fact, visiting that URL in your web browser is likely to bring up a 404 error. All that’s necessary is that it is universally unique and that the tool reading the ASDF file is able to map from a tag name to a schema URI, and then load the associated schema.

Again following with our example, we will assign the following URI to refer to our schema:

http://example.org/schemas/foo/metadata-1.0.0

Therefore, in our schema file, we have the following keys, one declaring the name of the YAML tag, and one defining the id of the schema:

id: "http://example.org/schemas/foo/metadata-1.0.0"
tag: "tag:example.org:foo/metadata-1.0.0"

Since our schema is just a basic ASDF schema, we will declare that it conforms to YAML Schema defined by the ASDF Standard:

$schema: "http://stsci.edu/schemas/yaml-schema/draft-01"

Descriptive information¶

Continuing our example, we include some descriptive metadata about the data type declared by the schema itself:

title: |
  Metadata for the foo instrument.
description: |
  This stores some information about an exposure from the foo instrument.
examples:
  -
    - A minimal description of an exposure.
    - |
        tag:example.org:foo/metadata-1.0.0
          exposure_time: 0.001

The schema proper¶

The rest of the schema describes the acceptable data types and their structure. The format used for this description comes straight out of JSON Schema, and rather than documenting all of the things it can do here, please refer to Understanding JSON Schema, and the further resources available at json-schema.org.

In our example, we’ll define two metadata elements: the name of the investigator, and the exposure time, each of which also have a description:

type: object
properties:
  investigator:
    type: string
    description: |
      The name of the principal investigator who requested the
      exposure.

  exposure_time:
    type: number
    description: |
      The time of the exposure, in nanoseconds.

We’ll also define an optional element for the exposure time unit. This is a somewhat contrived example to demonstrate how to include elements in your schema that are based on the custom types defined in the ASDF standard:

exposure_time_units:
  $ref: "http://stsci.edu/schemas/asdf/unit/unit-1.0.0"
  description: |
    The unit of the exposure time.
  default:
    s

Lastly, we’ll declare exposure_time as being required, and allow extra elements to be added:

required: [exposure_time]
additionalProperties: true

The complete example¶

Here is our complete schema example:

%YAML 1.1
---
$schema: "http://stsci.edu/schemas/yaml-schema/draft-01"
id: "http://example.org/schemas/foo/metadata-1.0.0"
tag: "tag:example.org:foo/metadata-1.0.0"

title: |
  Metadata for the foo instrument.
description: |
  This stores some information about an exposure from the foo instrument.
examples:
  -
    - A minimal description of an exposure.
    - |
        tag:example.org:foo/metadata-1.0.0
          exposure_time: 0.001

type: object
properties:
  investigator:
    type: string
    description: |
      The name of the principal investigator who requested the
      exposure.

  exposure_time:
    type: number
    description: |
      The time of the exposure, in nanoseconds.

  exposure_time_units:
    $ref: "http://stsci.edu/schemas/asdf/unit/unit-1.0.0"
    description: |
      The unit of the exposure time.
    default:
      s

required: [exposure_time]
additionalProperties: true

Extending an existing schema¶

JSON Schema does not support the concept of inheritance, which makes it somewhat awkward to express type hierarchies. However, it is possible to create a custom schema that adds attributes to an existing schema (e.g. one defined in the ASDF Standard). It is important to remember that it is not possible to override or remove any of the attributes from the existing schema.

The following important caveats apply when extending an existing schema:

It is not possible to redefine, override, or delete any attributes in the original schema.
It will not be possible to add attributes to any node where the original schema declares additionalProperties: false
Instances of the custom type will not be recognized as an instance of the original type when resolving schema references or processing YAML tags (i.e. there is no concept of polymorphism).

Here’s an example of extending a schema using the software schema defined by the ASDF Standard. Here’s the original schema, for reference:

%YAML 1.1
---
$schema: "http://stsci.edu/schemas/yaml-schema/draft-01"
id: "http://stsci.edu/schemas/asdf/core/software-1.0.0"
title: |
  Describes a software package.
description: |
  General-purpose description of a software package.

tag: "tag:stsci.edu:asdf/core/software-1.0.0"
type: object
properties:
  name:
    description: |
      The name of the application or library.
    type: string

  author:
    description: |
      The author (or institution) that produced the software package.
    type: string

  homepage:
    description: |
      A URI to the homepage of the software.
    type: string
    format: uri

  version:
    description: |
      The version of the software used.  It is recommended, but not
      required, that this follows the (Semantic Versioning
      Specification)[http://semver.org/spec/v2.0.0.html].
    type: string

required: [name, version]
additionalProperties: true
...

Since the software schema permits additional properties, we are free to extend it to include an email address for contacting the author:

%YAML 1.1
---
$schema: "http://stsci.edu/schemas/yaml-schema/draft-01"
id: "http://somewhere.org/schemas/software_extended-1.0.0"
title: |
  Describes a software package.
description: |
  Extension of ASDF core software schema to include the
  software author's contact email.

allOf:
  - $ref: http://stsci.edu/schemas/asdf/core/software-1.0.0
  - properties:
      author_email:
        description: |
          The contact email of the software author.
        type: string
    required: [author_email]
...

The crucial portion of this schema definition is the way that the allOf operator is used to join a reference to the base software schema with the definition of a new property called author_email.

The allOf combiner means that any instance that is validated against software_extended-1.0.0 will have to conform to both the base software schema and the properties specific to the extended schema.

Default annotation¶

The JSON Schema spec includes a schema annotation attribute called default that can be used to describe the default value of a data attribute when that attribute is missing. Recent versions of the spec point out that there is no single correct way to choose an annotation value when multiple are available due to references and combiners. This presents a problem when trying to fill in missing data in a file based on the schema default: if multiple conflicting values are available, the software does not know how to choose.

Previous versions of the ASDF Standard did not offer guidance on how to use default. The Python reference implementation read the first default that it encountered as a literal value and inserted that value into the tree when the corresponding attribute was otherwise missing. Until version 2.8, it also removed attributes on write whose values matched their schema defaults. The resulting files would appear to the casual viewer to be missing data, and may in fact be invalid against their schemas if the any of the removed attributes were required.

Implementations must not remove attributes with default values from the tree. Beginning with ASDF Standard 1.6.0, implementations also must not fill default values directly from the schema. This will avoid ambiguity when multiple schema defaults are present, and also permit the default attribute to contain a description that is not appropriate to use as a literal default value. For example:

default: An array of zeros matching the dimensions of the data array.

For ASDF Standard < 1.6.0, filling default values from the schema is required. This is necessary to support files written by older versions of the Python implementation.

Footnotes

1: Implementations may expose the control of validation on reading to the user (e.g. to disable it on demand). However, validation on reading should be the default behavior.
2: The presence of id and tag is not currently enforced by the YAML Schema but may be in a future version of the ASDF Standard. Authors of new schemas should assume that at the very least id will be required in a future version of the Standard.
3: For an example of how to inherit from another metaschema, look at the contents of the ASDF metaschema and see how there is a reference to the YAML schema in the top-level allOf.