xsd.2_1.SDMXDataStructureSpecificBase.xsd Maven / Gradle / Ivy
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SDMX Core Base Structure Specific Data Module
The core base structure specific data module contains the descriptions of base structure specific data set format. The data set defined here describes the structure of the data set in all structure specific data messages. Any structure specific data messages must derive the data set from this format. The entire structure declared for the is data set is abstract, meaning that instances will have to be based on types derived from these structures in schemas created based on the details data structure definition.
DataSetType is the abstract type which defines the base structure for any data structure definition specific data set. A derived data set type will be created that is specific to a data structure definition and the details of the organisation of the data (i.e. which dimension is the observation dimension and whether explicit measures should be used). Data is organised into either a collection of series (grouped observations) or a collection of un-grouped observations. The derived data set type will restrict this choice to be either grouped or un-grouped observations. If this dimension is "AllDimensions" then the derived data set type must consist of a collection of un-grouped observations; otherwise the data set will contain a collection of series with the observations in the series disambiguated by the specified dimension at the observation level. This data set is capable of containing data (observed values) and/or documentation (attribute values) and can be used for incremental updates and deletions (i.e. only the relevant updates or deletes are exchanged). It is assumed that each series or un-grouped observation will be distinct in its purpose. For example, if series contains both data and documentation, it assumed that each series will have a unique key. If the series contains only data or only documentation, then it is possible that another series with the same key might exist, but with not with the same purpose (i.e. to provide data or documentation) as the first series.
This base type is designed such that derived types can be processed in a generic manner; it assures that data structure definition specific data will have a consistent structure. The group, series, and observation elements are unqualified, meaning that they are not qualified with a namespace in an instance. This means that in the derived data set types, the elements will always be the same, regardless of the target namespace of the schemas which defines these derived types. This allows for consistent processing of the structure without regard to what the namespace might be for the data structure definition specific schema.
The data set can contain values for attributes which do not have an attribute relationship with any data structure definition components. These attribute values will exist in XML attributes in this element based on this type (DataSet). This is specified in the content model with the declaration of anyAttributes in the "local" namespace. The derived data set type will refine this structure so that the attributes are explicit. The XML attributes will be given a name based on the attribute's identifier. These XML attributes will be unqualified (meaning they do not have a namespace associated with them). To allow for generic processing, it is required that the only unqualified XML attributes in the derived data set type (outside of the standard data set attributes) be for attributes declared in the data structure definition. If additional attributes are required, these should be qualified with a namespace so that a generic application can easily distinguish them as not being meant to represent a data structure definition attribute.
DataProvider contains a reference to the provider for the data set.
Group contains a references to a defined group in the data structure definition along with its key (if necessary) and values for the attributes which are associated with the group. An attribute is associated to a group by either an explicit group relationship or by a group attachment when the attribute has a relationship with a dimension which is a member of this group.
Series contains a collection of observations that share a common key (set of dimension values). The key of a series is every dimension defined in the data structure definition, save the dimension at the observation level. In addition to the key and observations, the series contains values for attributes which have a relationship with any dimension that is part of the series key, so long as the attribute does not specify an attachment group or also has a relationship with the dimension declared to be at the observation level.
Obs is an un-grouped observation. This observation has a key which is a set of values for all dimensions declared in the data structure definition. In addition to the key, the value of the observation can be provided along with values for all attributes which have an association with the primary measure or any dimension (so long as it does not specify a group attachment).
The REPORTING_YEAR_START_DAY attribute is an explict attribute for the reporting year start day, which provides context to the time dimension when its value contains a reporting period (e.g. 2010-Q1). This attribute is used to state the month and day that the reporting year begins (e.g. --07-01 for July 1st). In the absence of an explicit value provided in this attribute, all reporting period values will be assumed to be based on a reporting year start day of January 1. This is declared in the base schema since it has a fixed identifier and representation. The derived data set type may either require or prohibit this attribute, depending on whether the data structure declared the reporting year start day attribute and if so, the attribute relationship and assignment status assigned to it.
GroupType is the abstract type which defines a structure which is used to communicate attribute values for a group defined in a data structure definition. The group can consist of either a subset of the dimensions defined by the data structure definition, or an association to an attachment constraint, which in turn defines key sets to which attributes can be attached. In the case that the group is based on an attachment constraint, only the identification of group is provided. It is expected that a system which is processing this will relate that identifier to the key sets defined in the constraint and apply the values provided for the attributes appropriately.
Data structure definition schemas will drive types based on this for each group defined in the data structure definition. Both the dimension values which make up the key (if applicable) and the attribute values associated with the group will be represented with XML attributes. This is specified in the content model with the declaration of anyAttributes in the "local" namespace. The derived group type will refine this structure so that the attributes are explicit. The XML attributes will be given a name based on the attribute's identifier. These XML attributes will be unqualified (meaning they do not have a namespace associated with them). The dimension XML attributes will be required while the attribute XML attributes will be optional. To allow for generic processing, it is required that the only unqualified XML attributes in the derived group type be for the group dimensions and attributes declared in the data structure definition. If additional attributes are required, these should be qualified with a namespace so that a generic application can easily distinguish them as not being meant to represent a data structure definition dimension or attribute.
The type attribute reference the identifier of the group as defined in the data structure definition. This is optional, but derived group types will provide a fixed value for this so that it always available in the post validation information set. This allows the group to be processed in a generic manner.
The REPORTING_YEAR_START_DAY attribute is an explict attribute for the reporting year start day, which provides context to the time dimension when its value contains a reporting period (e.g. 2010-Q1). This attribute is used to state the month and day that the reporting year begins (e.g. --07-01 for July 1st). In the absence of an explicit value provided in this attribute, all reporting period values will be assumed to be based on a reporting year start day of January 1. This is declared in the base schema since it has a fixed identifier and representation. The derived group types may either require or prohibit this attribute, depending on whether the data structure declared the reporting year start day attribute and if so, the attribute relationship and assignment status assigned to it.
SeriesType is the abstract type which defines a structure which is used to group a collection of observations which have a key in common. The key for a series is every dimension defined in the data structure definition, save the dimension declared to be at the observation level for this data set. In addition to observations, values can be provided for attributes which are associated with the dimensions which make up this series key (so long as the attributes do not specify a group attachment or also have an relationship with the observation dimension). It is possible for the series to contain only observations or only attribute values, or both.
Data structure definition schemas will drive a type based on this that is specific to the data structure definition and the variation of the format being expressed in the schema. Both the dimension values which make up the key and the attribute values associated with the key dimensions will be represented with XML attributes. This is specified in the content model with the declaration of anyAttributes in the "local" namespace. The derived series type will refine this structure so that the attributes are explicit. The XML attributes will be given a name based on the attribute's identifier. These XML attributes will be unqualified (meaning they do not have a namespace associated with them). The dimension XML attributes will be required while the attribute XML attributes will be optional. To allow for generic processing, it is required that the only unqualified XML attributes in the derived group type be for the series dimensions and attributes declared in the data structure definition. If additional attributes are required, these should be qualified with a namespace so that a generic application can easily distinguish them as not being meant to represent a data structure definition dimension or attribute.
The TIME_PERIOD attribute is an explict attribute for the time dimension. This is declared in the base schema since it has a fixed identifier and representation. The derived series type will either require or prohibit this attribute, depending on whether time is the observation dimension. If the time dimension specifies a more specific representation of time the derived type will restrict the type definition to the appropriate type.
The REPORTING_YEAR_START_DAY attribute is an explict attribute for the reporting year start day, which provides context to the time dimension when its value contains a reporting period (e.g. 2010-Q1). This attribute is used to state the month and day that the reporting year begins (e.g. --07-01 for July 1st). In the absence of an explicit value provided in this attribute, all reporting period values will be assumed to be based on a reporting year start day of January 1. This is declared in the base schema since it has a fixed identifier and representation. The derived series type may either require or prohibit this attribute, depending on whether the data structure declared the reporting year start day attribute and if so, the attribute relationship and assignment status assigned to it.
ObsType is the abstract type which defines the structure of a grouped or un-grouped observation. The observation must be provided a key, which is either a value for the dimension which is declared to be at the observation level if the observation is grouped, or a full set of values for all dimensions in the data structure definition if the observation is un-grouped. This key should disambiguate the observation within the context in which it is defined (e.g. there should not be another observation with the same dimension value in a series). The observation can contain an observed value and/or attribute values.
Data structure definition schemas will drive a type or types based on this that is specific to the data structure definition and the variation of the format being expressed in the schema. The dimension value(s) which make up the key and the attribute values associated with the key dimension(s) or the primary measure will be represented with XML attributes. This is specified in the content model with the declaration of anyAttributes in the "local" namespace. The derived observation type will refine this structure so that the attributes are explicit. The XML attributes will be given a name based on the attribute's identifier. These XML attributes will be unqualified (meaning they do not have a namespace associated with them). The dimension XML attribute(s) will be required while the attribute XML attributes will be optional. To allow for generic processing, it is required that the only unqualified XML attributes in the derived observation type be for the observation dimension(s) and attributes declared in the data structure definition. If additional attributes are required, these should be qualified with a namespace so that a generic application can easily distinguish them as not being meant to represent a data structure definition dimension or attribute.
If the data structure definition specific schema requires that explicit measures be used (only possible when the measure dimension is specified at the observation), then there will be types derived for each measure defined by the measure dimension. In this case, the types will be specific to each measure, which is to say that the representation of the primary measure (i.e. the observed value) will be restricted to that which is specified by the specific measure.
The type attribute is used when the derived format requires that explicit measure be used. In this case, the derived type based on the measure will fix this value to be the identification of the measure concept. This will not be required, but since it is fixed it will be available in the post validation information set which will allow for generic processing of the data. If explicit measures are not used, then the derived type will prohibit the use of this attribute.
The TIME_PERIOD attribute is an explicit attribute for the time dimension. This is declared in the base schema since it has a fixed identifier and representation. The derived series type will either require or prohibit this attribute, depending on whether time is the observation dimension. If the time dimension specifies a more specific representation of time the derived type will restrict the type definition to the appropriate type.
The REPORTING_YEAR_START_DAY attribute is an explict attribute for the reporting year start day, which provides context to the time dimension when its value contains a reporting period (e.g. 2010-Q1). This attribute is used to state the month and day that the reporting year begins (e.g. --07-01 for July 1st). In the absence of an explicit value provided in this attribute, all reporting period values will be assumed to be based on a reporting year start day of January 1. This is declared in the base schema since it has a fixed identifier and representation. The derived observation type may either require or prohibit this attribute, depending on whether the data structure declared the reporting year start day attribute and if so, the attribute relationship and assignment status assigned to it.
The OBS_VALUE attribute is an explicit attribute for the primary measure, which is intended to hold the value for the observation. This is declared in the base schema since it has a fixed identifier. This attribute is un-typed, since the representation of the observed value can vary widely. Derived types will restrict this to be a type based on the representation of the primary measure. In the case that an explicit measure is used, the derived type for a given measure might further restrict the type of the primary measure to be more specific to the core representation for the measure concept. Note that it is required that in the case of multiple measures being used, that the representation of the primary measure is broad enough to handle the various representations of the measure concepts.
DataScopeType is an enumeration of the possible validity scopes for a data set. These scopes indicate the level at which the data is stated to be valid.
The data set conforms simply to the data structure definition as it is defined, without regard to any constraints.
The data set conforms to the known allowable content constraints applied to the data structure definition.
The data set conforms to the known allowable content constraints applied to the dataflow.
The data set conforms to the known allowable content constraints applied to the provision agreement.
The SetAttributeGroup defines a common set of attributes pertaining to any data set. The attributes are qualified, so that they will be easily distinguished from attributes that are specific to the data structure. Note that many of these attributes are duplications of fields available in the header of the data messages. The reason for this is to allow the header values to be overridden at the data set level when a message contains more than one data set. If an attribute here does not have a value, then the value from the header is applied to the data set.
The structureRef contains a reference to a structural specification in the header of a data or reference metadata message. The structural specification details which structure the data or reference metadata conforms to, as well as providing additional information such as how the data is structure (e.g. which dimension occurs at the observation level for a data set).
The setID provides an identification of the data or metadata set.
The action attribute indicates whether the file is appending, replacing, or deleting.
The reportingBeginDate indicates the inclusive start time of the data reported in the data or metadata set.
The reportingEndDate indicates the inclusive end time of the data reported in the data or metadata set.
The validFromDate indicates the inclusive start time indicating the validity of the information in the data or metadata set.
The validToDate indicates the inclusive end time indicating the validity of the information in the data or metadata set.
The publicationYear holds the ISO 8601 four-digit year.
The publicationPeriod specifies the period of publication of the data or metadata in terms of whatever provisioning agreements might be in force (i.e., "Q1 2005" if that is the time of publication for a data set published on a quarterly basis).
The dataScope attribute indicates the scope at which the data is meant to be validated. These scopes are hierarchical and are (from the top down); DataStructure, ConstrainedDataStructure, Dataflow, and ProvisionAgreement. the hierarchy of these scopes represent the cascading level of constraints, which can restrict the valid values for components. For example, a data structure defines a dimension with a coded representation. A data flow might have a constraint associated with it which further restricts the values allowed from the referenced code list to a subset of the values allowed by the data structure definition. A provision agreement that is based on the dataflow might also have a constraint, which further restricts the subset of the codelist from the dataflow. Therefore, the allowed content becomes stricter lower in the hierarchy. Data that is given a scope of one value is stated to be valid at that level and all levels below it. Therefore, this scope serves to state that data that is meant to be structured simply against the data structure definition is not meant to be validated against the a dataflow, where constraints might be applied.