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AI-generated Key Takeaways
Concepts define data types and can be referenced across datasets, providing textual information, topic association, data type, attributes, properties, default values, and table mappings.
Each concept has a unique ID and can inherit properties from another concept using the extends attribute.
Concepts can be associated with topics, have attributes for additional information, properties for instance-specific details, and default values.
A concept's data type can be one of: string, float, integer, boolean, date, or another concept.
Concepts can be mapped to tables containing their values and non-constant properties for data storage and retrieval.
The unique identifier of the topic this concept is
associated with. The referenced topic may be defined in the same
dataset or externally, i.e., in another dataset. A reference to an
external topic must be of the form
"prefix:other_topic_id", where "prefix" is the
prefix used for the namespace of the external dataset (see XML
namespaces).
The data type of the concept. A concept must provide a type
declaration or extend another concept. In the case where it's
extending a concept, it may also provide a type declaration. The type of
the extended concept must be less restrictive than the type of the
concept extending it. "Less restrictive than" (LRT) is a
partial order defined as follows: string LRT float float LRT integer
string LRT date string LRT boolean
A reference to a concept that corresponds to the values
of the attribute. If the attribute specifies a type, then the type
must match the type of the referenced concept. A reference to an
external concept must be of the form
"prefix:other_concept_id", where "prefix" is
the prefix used for the namespace of the external dataset (see XML
namespaces).
The id of the concept attribute. This identifier must be
unique within the concept (across attributes and properties). The
id may be omitted if the concept attribute is specified. In that
case, an id is implicity created with value the local name of the
referenced concept. For instance <attribute
concept="unit:currency"/> is equivalent to
<attribute id="currency"
concept="unit:currency"/>
A property of the concept. Properties represent additional
information about instances of the concept (e.g., a concept
"city" may have a property "country").
A reference to a concept that corresponds to the values
of the property. If the property specifies a type, then the type
must match the type of the referenced concept. A reference to an
external concept must be of the form
"prefix:other_concept_id", where "prefix" is
the prefix used for the namespace of the external dataset (see XML
namespaces).
The id of the concept property. This identifier must be
unique within the concept (across attributes and properties). The
id may be omitted if the concept property is specified. In that
case, an id is implicitly created with value the local name of the
referenced concept. For instance <property
concept="geo:country"/> is equivalent to <property
id="country"
concept="geo:country"/>
If true, then this property must reference a concept, and
this property denotes a mapping (1-to-1) relationship between this
concept and the referenced concept. Each instance of the referenced
concept is referenced by at most one instance of this
concept.
If true, then this property must reference a concept, and
this property denotes a hierarchical relationship between this
concept and the referenced concept (e.g., the continent of a
country).
A concept is a definition of a type of data that appears in the
dataset (e.g., "GDP" or "County"). A concept may be
associated with an enumeration of all its possible values or not. A
concept defined in some dataset may be referenced in other
datasets.
The unique identifier of a concept that this concept
extends. The referenced concept may be defined in the same dataset
or externally, i.e., in another dataset. A reference to an external
concept must be of the form "prefix:other_concept_id",
where "prefix" is the prefix used for the namespace of
the external dataset (see XML namespaces).
The unique identifier of the topic this concept is associated
with. The referenced topic may be defined in the same dataset or
externally, i.e., in another dataset. A reference to an external topic
must be of the form "prefix:other_topic_id", where
"prefix" is the prefix used for the namespace of the external
dataset (see XML namespaces).
The unique identifier of a concept that this concept extends.
The referenced concept may be defined in the same dataset or externally,
i.e., in another dataset. A reference to an external concept must be of
the form "prefix:other_concept_id", where "prefix" is
the prefix used for the namespace of the external dataset (see XML
namespaces).
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-06-26 UTC."],[],["Concepts, within a dataset (namespace: `http://schemas.google.com/dspl/2010`), define data types and are globally unique. Concepts can extend others, using `prefix:other_concept_id` for external references. They include `info` (textual details), `topic` (associated topics via `ref`), `type` (data type, `ref`), `attribute` (additional information), `property` (instance information), `defaultValue`, and `table` (data source, `ref`). Key concept attributes are `id` (unique), and `extends` (referencing another concept). External references are in `prefix:identifier` format. A concept must have a `type` or `extends`.\n"]]