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... ... @@ -295,10 +295,12 @@ 295 295 Many XML tools and technologies have expectations about the functions performed by an XML schema, one of which is a very direct relationship between the XML constructs described in the XML schema and the tagged data in the XML instance. Strong data typing is also considered normal, supporting full validation of the tagged data. These message types are designed to support validation and other expected XML schema functions. 296 296 297 297 1. //Generic Metadata~:// For the exchange of reference metadata sets. ‘Generic’ means the XML elements and XML attributes are the same regardless of the metadata set. 298 -1. //Registry~:// All of the possible interactions with the SDMX registry services are supported using SDMX-ML interfaces and REST API calls. Submission of structural metadata content, data / metadata registrations and subscriptions is performed by a synchronous exchange of documents – a “request” message answered by a “response” message.298 +1. //Registry~:// All of the possible interactions with the SDMX registry services are supported using SDMX-ML interfaces and REST API calls. Submission of structural metadata content, data / metadata registrations and subscriptions is performed by a synchronous exchange of documents – a “request” message answered by a 299 299 300 - ==5.2 SDMX-JSON ==300 +“response” message. 301 301 302 +== {{id name="_Toc56241"/}}5.2 SDMX-JSON == 303 + 302 302 SDMX-JSON is the JSON transmission format specification for exchanging structural metadata, data and reference metadata. It provides an alternative to SDMX-ML and is most suited to applications like web data dissemination. 303 303 304 304 SDMX-JSON messages serve the same function as those of the XML formats but have a different structure. For data, an important distinction is that they carry both component codes and labels which provides all the information needed to display the content in a single JSON response. The XML Structure-specific Data format by contrast carries only code IDs thus requiring applications obtain and hold structural metadata about the data set in order to display the content in human-readable form. ... ... @@ -311,7 +311,7 @@ 311 311 1. //Data: //For the exchange of data. Unlike SDMX-ML, the structure of a SDMX-JSON data message is not specific to the DSDs of the data sets so schema validation will not check for compliance of the data with the DSDs. 312 312 1. //Metadata//: For the exchange of reference metadata sets. 313 313 314 -== 5.3 SDMX-CSV == 316 +== {{id name="_Toc56242"/}}5.3 SDMX-CSV == 315 315 316 316 SDMX-CSV is the CSV transmission format specification for exchanging data and reference metadata only. 317 317 ... ... @@ -322,7 +322,7 @@ 322 322 1. //Data//: For the exchange of data. Like SDMX-JSON, SDMX-CSV can include both code IDs and labels which is helpful when using the data to create human readable charts and dashboards. 323 323 1. //Metadata//: For the exchange of reference metadata sets. 324 324 325 -== 5.4 Formats and Messages Deprecated in Version 3.0 == 327 +== {{id name="_Toc56243"/}}5.4 Formats and Messages Deprecated in Version 3.0 == 326 326 327 327 The following formats and messages have been deprecated in version 3.0 to simplify, modernise and rationalise the standard. 328 328 ... ... @@ -339,35 +339,35 @@ 339 339 * SDMX-ML Query messages 340 340 * SDMX-ML Submit Structure Request messages 341 341 342 -= 6 Dependencies on SDMX content-oriented guidelines = 344 += {{id name="_Toc56244"/}}6 Dependencies on SDMX content-oriented guidelines = 343 343 344 344 The technical standards proposed here are designed so that they can be used in conjunction with other SDMX guidelines which are more closely tied to the content and semantics of statistical data exchange. The SDMX Information Model works equally well with any statistical concept, but to encourage interoperability, it is also necessary to standardize and harmonize the use of specific concepts and terminology. To achieve this goal, SDMX creates and maintains guidelines for cross-domain concepts, terminology, and structural definitions. There are three major parts to this effort. 345 345 346 -== 6.1 Cross-Domain Concepts == 348 +== {{id name="_Toc56245"/}}6.1 Cross-Domain Concepts == 347 347 348 348 The SDMX Cross-Domain Concepts is a content guideline concerning concepts which are used across statistical domains. This list is expected to grow and to be subject to revision as SDMX is used in a growing number of domains. The use of the SDMX Cross-Domain Concepts, where appropriate, provides a framework to further promote interoperability among organisations using the technical standards presented here. The harmonization of statistical concepts includes not only the definitions of the concepts, and their names, but also, where appropriate, their representation with standard code lists, and the role they play within data structure definitions and metadata structure definitions. 349 349 350 350 The intent of this guideline is two-fold: to provide a core set of concepts which can be used to structure statistical data and metadata, to promote interoperability between systems (“structural metadata”, as described above); and to promote the exchange of metadata more widely, with a set of harmonized concept names and definitions for other types of metadata (“reference metadata”, as defined above.) 351 351 352 -== 6.2 Metadata Common Vocabulary == 354 +== {{id name="_Toc56246"/}}6.2 Metadata Common Vocabulary == 353 353 354 354 The Metadata Common Vocabulary is an SDMX guideline which provides definition of terms to be used for the comparison and mapping of terminology found in data structure definitions and in other aspects of statistical metadata management. Essentially, it provides ISOcompliant definitions for a wide range of statistical terms, which may be used directly, or against which other terminology systems may be mapped. This set of terms is inclusive of the terminology used within the SDMX Technical Standards. 355 355 356 356 The MCV provides definitions for terms on which the SDMX Cross-Domain Metadata Concepts work is built. 357 357 358 -== 6.3 Statistical Subject-Matter Domains == 360 +== {{id name="_Toc56247"/}}6.3 Statistical Subject-Matter Domains == 359 359 360 360 The Statistical Subject-Matter Domains is a listing of the breadth of statistical information for the purposes of organizing widespread statistical exchange and categorization. It acts as a standard scheme against which the categorization schemes of various counterparties can be mapped, to facilitate interoperable data and metadata exchange. It serves another useful purpose, however, which is to allow an organization of corresponding “domain groups”, each of which could define standard data structure definitions, concepts, etc. within their domains. Such groups already exist within the international community. SDMX would use the Statistical Subject-Matter Domains list to facilitate the efforts of these groups to develop the kinds of content standards which could support the interoperation of SDMX-conformant technical systems within and across statistical domains. The organisation of the content of such schemes is supported in SDMX as a Category Scheme. 361 361 362 362 SDMX Statistical Subject-Matter Domains will be listed and maintained by the SDMX Initiative and will be subject to adjustment. 363 363 364 -== 6.4 SDMX Concept Roles == 366 +== {{id name="_Toc56248"/}}6.4 SDMX Concept Roles == 365 365 366 366 These guidelines define the standard set of SDMX Concept Roles and their use. This set of standard SDMX Concepts are implemented as a cross-domain Concept Scheme that defines the set of concept roles and gives examples on concept role implementation in SDMX 2.0, 2.1 and 3.0. A concept role gives a particular context to a concept for easy and systematic interpretation by machine processing and visualization tools. For example, the concepts REPORTING_AREA and COUNTERPART_AREA are different concepts but they are both geographical characteristics, therefore they can be associated with the same concept role ID: "GEO". This allows visualization systems to interpret these concepts as geographical data in order to generate maps. The implementation of concept roles is different in versions 2.0 and 2.1/3.0 of the SDMX technical standard. Specifically for SDMX 3.0, this set of roles is considered a normative list that must be interpreted in the same way by all organisations. 367 367 368 368 Additional roles may be provided via the standard roles’ mechanism in SDMX 3.0, i.e., via Concept Schemes; the semantics of these roles have to be agreed bilateraly in data exchanges. The Concept Roles are available as an SDMX Concept Scheme on the SDMX Global Registry. 369 369 370 -= 7 Validation and Transformation Language = 372 += {{id name="_Toc56249"/}}7 Validation and Transformation Language = 371 371 372 372 For many years the SDMX initiative has been fostering and supporting the development of a standard calculation language, called Validation and Transformation Language (VTL). A blueprint for defining calculations was already described in the original SDMX 2.1 specifications (package 13 of the Information Model - “Transformations and Expressions”). It was just a basic framework that required further developments to became operational in order to achieve a calculation language able to manipulate SDMX artefacts. 373 373