Information about the application schema used to build the dataset.
New metadata element, not found in ISO 19115, which is required to describe geographic data.
List of names of feature types with the same spatial representation (same as spatial attributes).
Value uniquely identifying an object within a namespace.
Root entity which defines metadata about a resource or resources.
Information describing metadata extensions.
Information identifying the portrayal catalogue used.
Spatial attributes in the application schema for the feature types.
Datatype of element or entity.
Obligation of the element or entity.
The notion of cataloguing a set of related documents together in a discoverable series is common in map catalogues. With digital spatial data, the definition of what constitutes a "dataset" is more problematic and reflects the institutional and software environments of the originating organization. Common metadata can be derived for a series of related spatial datasets, and such metadata is generally relevant or can be inherited by each of the dataset instances. Software to support this inheritance of metadata for geographic data within a cataloguing system can simplify data entry, update and reporting.
There is a potential hierarchy of re-usable metadata that can be employed in implementing a metadata collection. By creating several levels of abstraction, a linked hierarchy can assist in filtering or targeting user queries to the requested level of detail. The hierarchy should not necessarily be interpreted to require multiple copies of metadata being managed on-line. Conversely, the definition of general metadata can be supplemented by spatially specific metadata that, when queried, either inherits or overrides the general case. Through use of pointers this method can reduce the redundancy of metadata managed at a site and provide for different views of the holdings by users.
A series or collection of spatial data which share similar characteristics of theme, source date, resolution, and methodology. The exact definition of what constitutes a series entry will be determined by the data provider. Examples of data series metadata entries may include:
A flight line of digital aerial photographs collected during a single flight with one camera and film type. A continuous scan swathe collected from a satellite using the same sensors on a single orbital pass.
A collection of raster map data captured from a common series of paper maps.
A collection of vector datasets depicting surface hydrography with associated attribution for multiple administrative areas within a country.
The creation of a "data series" metadata level is an optional feature that allows users to consult higher-level characteristics for data search. The definition of this type of metadata may be adequate for the initial characterization of available spatial data, but may not be adequate for detailed assessment of data quality of specific datasets.
For the purposes of this specification, a dataset should be a consistent spatial data product instance that can be generated or made available by a spatial data distributor. A dataset may be a member of a data series, as defined in the previous subclause. A dataset may be composed of a set of identified feature types and instances, and attribute types and instances as described in the following four subclauses.
On a demand basis, metadata from series and dataset information will be merged to present the user with a view of the metadata at the dataset level of abstraction. Metadata for which no hierarchy is listed are interpreted to be "dataset" metadata, by default.
Spatial constructs known as features are grouped spatial primitives (0-, 1- and 2-dimensional geometric objects) that have a common identity. Spatial data services may elect to support feature type-level metadata where it is available and make such metadata available for query or retrieval. Feature Type -level metadata, together with feature instance-, attribute type- and attribute instance-level metadata, will be grouped into datasets, as defined in the previous subclause. Examples of feature type metadata entries may include:
Feature instances are spatial constructs (features) that have a direct correspondence with a real world object. Spatial data services may elect to support feature instance-level metadata where it is available and make such metadata available for query or retrieval. Feature Instance-level metadata, together with feature type-, attribute type- and attribute instance-level metadata, will be grouped into datasets. Examples of feature instance metadata entries may include:
Attribute types are the digital parameters that describe a common aspect of grouped spatial primitives (0-, 1- and 2- dimensional geometric objects). Spatial data services may elect to support attribute type-level metadata where it is available and make such metadata available for query or retrieval. Attribute type-level metadata, together with feature type-, feature instance and attribute instance-level metadata, will be grouped into datasets. Examples of attribute type metadata entries may include:
Attribute instances are the digital parameters that describe an aspect of a feature instance. Spatial data services may elect to support attribute instance-level metadata where it is available and make such metadata available for query or retrieval. Attribute instance-level metadata, together with feature type-, feature instance and attribute typelevel metadata, will be grouped into datasets. Examples of attribute instance metadata entries may include:
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