Changes for page SDMX 2.1 Standards. Section 1. Framework for SDMX technical standards

Last modified by Artur on 2025/09/10 11:19

From 3.2 to 3.3 From 3.4 to 3.5

From version 3.3

edited by Helena
on 2025/05/19 15:12

Change comment: There is no comment for this version

To version 3.4

edited by Helena
on 2025/05/19 15:15

Change comment: There is no comment for this version

Raw
Rendered

Summary

Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

@@ -9,12 +9,9 @@
  |(% style="width:154px" %) |(% style="width:118px" %)April 2011|(% style="width:533px" %)Initial release
  |(% style="width:154px" %)1.0|(% style="width:118px" %)July 2020|(% style="width:533px" %)(((
  Added the last two sentences of the Section 1 – Introduction
--Added the Section 10 –Validation and Transformation Language (VTL)
--)))
++Added the Section 10 –Validation and Transformation Language (VTL))))
--(((
  = {{id name="_Toc38908"/}}1. Introduction =
--)))
  The Statistical Data and Metadata Exchange (SDMX) initiative (http:~/~/www.sdmx.org) sets standards that can facilitate the exchange of statistical data and metadata using modern information technology, with an emphasis on aggregated data.
@@ -32,9 +32,7 @@
  Please note also that the SOAP and REST specifications are not maintained any more in the section 7 (Web Service Guidelines), the link to these specifications can be found on the SDMX website
--1. (((
  = {{id name="_Toc38909"/}}2. Changes from Previous Version =
--)))
  The 2.0 version of this standard represented a significant increase in scope, and also provided more complete support in those areas covered in the version 1.0 specification. Version 2.0 of this standard is backward-compatible with version 1.0, so that existing implementations can be easily migrated to conformance with version 2.0.
@@ -78,13 +78,9 @@
  **Support for partial item schemes such as a code list: **The concept of a 143 partial (sub-set) item scheme such as a partial code list for use in exchange scenarios has been introduced**.**
--1. (((
  = {{id name="_Toc38910"/}}3. Processes and Business Scope =
--1. (((
  == {{id name="_Toc38911"/}}3.1 Process Patterns ==
--)))
--)))
  SDMX identifies three basic process patterns regarding the exchange of statistical data and metadata. These can be described as follows:
@@ -104,10 +104,7 @@
  It is important to note that SDMX is primarily focused on the //exchange// and //dissemination// of statistical data and metadata. There may also be many uses for the standard model and formats specified here in the context of internal processing of data that are not concerned with the exchange between organizations and users, however. It is felt that a clear, standard formatting of data and metadata for the purposes of exchange and dissemination can also facilitate internal processing by organizations and users, but this is not the focus of the specification.
--1.
--11. (((
  == {{id name="_Toc38912"/}}3.2 SDMX and Process Automation ==
--)))
  Statistical data and metadata exchanges employ many different automated processes, but some are of more general interest than others. There are some common information technologies that are nearly ubiquitous within information systems today. SDMX aims to provide standards that are most useful for these automated processes and technologies.
@@ -120,10 +120,7 @@
  The SDMX standards specified here are designed to support the requirements of all of these automation processes and technologies.
--1.
--11. (((
  == {{id name="_Toc38913"/}}3.3 Statistical Data and Metadata ==
--)))
  To avoid confusion about which "data" and "metadata" are the intended content of the SDMX formats specified here, a statement of scope is offered. Statistical "data" are sets of often numeric observations which typically have time associated with them. They are associated with a set of metadata values, representing specific concepts, which act as identifiers and descriptors of the data. These metadata values and concepts can be understood as the named dimensions of a multi-dimensional co-ordinate system, describing what is often called a "cube" of data.
@@ -145,10 +145,7 @@
   **Figure 1: High Level Schematic of Major Artefacts in the SDMX Information Model**
--1.
--11. (((
  == {{id name="_Toc38914"/}}3.4 The SDMX View of Statistical Exchange ==
--)))
  Version 1.0 of ISO/TS 17369 SDMX covered statistical data sets and the metadata related to the structure of these data sets. This scope was useful in supporting the different models of statistical exchange (bilateral exchange, gateway exchange, and data-sharing) but was not by itself sufficient to support them completely. Versions 2.0 and 2.1 provide a much more complete view of statistical exchange, so that an open data-sharing model can be fully supported, and other models of exchange can be more completely automated. In order to produce technical standards that will support this increased scope, the SDMX Information Model provides a broader set of formal objects which describe the actors, processes, and resources within statistical exchanges.
@@ -204,10 +204,7 @@
  As with data structures, the generic format for metadata sets provides a known document structure, whilst the structure specific format is derived specifically from a metadata structure definition and can perform a higher degree of schema validation.
--1.
--11. (((
  == {{id name="_Toc38915"/}}3.5 SDMX Registry Services ==
--)))
  In order to provide visibility into the large amount of data and metadata which exists within the SDMX model of statistical exchange, it is felt that an architecture based on a set of registry services is potentially useful. A “registry” – as understood in webservices terminology – is an application which maintains and stores metadata for querying, and which can be used by any other application in the network with sufficient access privileges (though note that the mechanism of access control is outside of the scope of the SDMX standard). It can be understood as the index of a distributed database or metadata repository which is made up of all the data provider’s data sets and reference metadata sets within a statistical community, located across the Internet or similar network.
@@ -222,10 +222,7 @@
  * //**Querying: **//The registry services have interfaces for querying the metadata contained in a registry, so that applications and users can discover the existence of data sets and reference metadata sets, structural metadata, the providers/agencies associated with those objects, and the provider agreements which describe how the data and metadata are made available, and how they are categorized.
  * //**Subscription/Notification:**// It is possible to “subscribe” to specific objects in a registry, so that a notification will be sent to all subscribers whenever the registry objects are updated.
--1.
--11. (((
  == {{id name="_Toc38916"/}}3.6 Web services ==
--)))
  Web services allow computer applications to exchange data directly over the Internet, essentially allowing modular or distributed computing in a more flexible fashion than ever before. In order to allow web services to function, however, many standards are required: for requesting and supplying data; for expressing the enveloping data which is used to package exchanged data; for describing web services to one another, to allow for easy integration into applications that use other web services as data resources.
@@ -238,9 +238,7 @@
  A normative list of common error codes: When web services are used, it is necessary to have error codes which can help to explain the situation when problems are encountered. Prior to version 2.1 of the SDMX standard, there was no set of agreed error codes for use with SDMX web services. Version 2.1 of the SDMX standard fills that gap.
--1. (((
  = {{id name="_Toc38917"/}}4 The SDMX Information Model =
--)))
  SDMX provides a way of modelling statistical data, and defines the set of metadata constructs used for this purpose. Because SDMX specifies formats in two syntaxes for expressing data and structural metadata, the model is used as a mechanism for guaranteeing that transformation between the different formats are lossless. All of the formats are syntax-bound expressions of the common information model. SDMX version 1.0 has based itself on GESMES/TS as an input to the model and formats, both to build on the proven success of this model for time series data exchange, and to ensure backward compatibility with existing GESMES/TS-based systems. Version 2.0/2.1 expands upon the version 1.0 basis to provide a more comprehensive model.
@@ -256,9 +256,7 @@
  The SDMX Information Model is presented using UML, and is also described in prose. While the information model is not normative, it is a valuable tool for understanding and using the normative format specifications.
--1. (((
  = {{id name="_Toc38918"/}}5 SDMX-EDI =
--)))
  The SDMX-EDI format is drawn from the GESMES/TS version 3.0 implementation guide, as published as a standard of the SDMX initiative.
@@ -270,9 +270,7 @@
  EDIFACT syntax used for SDMX-EDI, and those found in the XML syntax of SDMXML. Since both syntactic implementations reflect the same logical constructs, SDMXEDI data and structural metadata messages can be transformed into corresponding SDMX-ML formats, and vice-versa. Thus, these standards provide for interoperability between the UN/EDIFACT-based and XML-based systems processing and exchanging statistical data and metadata.
--1. (((
  = {{id name="_Toc38919"/}}6 SDMX-ML =
--)))
  While the SDMX-EDI format is primarily designed to support batch exchange, SDMXML supports a wider range of requirements. XML formats are used for many different types of automated processing, and thus must support more varied processing scenarios. That is why there are several types of messages available as SDMX-ML formats. Each is suited to support a specific set of processing requirements.
@@ -289,56 +289,39 @@
  Because all of the SDMX-ML formats are implementations of the same information model, and all the data and metadata messages are derivable from the Structure message which describes a data set or metadata set, it is possible to have standard mappings between each of the similar formats. These mappings can be implemented in generic transformation tools, useful to all SDMX-ML users, and not specific to a particular data set’s key family or metadata set’s structure definition (even though some of the formats they deal with may be). Part of the SDMX-ML package is the set of mappings between the structure-specific data and metadata formats and the Structure Definition format from which all are derivable.
--1. (((
  = {{id name="_Toc38920"/}}7 Conformance =
--)))
  This section will contain a normative statement of what applications must do to be considered conformant with the SDMX version 2.1 specifications. This will address both the application functionality that must be supported, and the contents of an Implementer’s Conformance Statement regarding SDMX conformance.
--1. (((
  = {{id name="_Toc38921"/}}8 Dependencies on SDMX content-oriented guidelines =
--)))
  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 crossdomain concepts, terminology, and structural definitions. There are three major parts to this effort.
--1.
--11. (((
  == {{id name="_Toc38922"/}}8.1 Cross-Domain Concepts ==
--)))
  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.
  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.)
--1.
--11. (((
  == {{id name="_Toc38923"/}}8.2 Metadata Common Vocabulary ==
--)))
  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 ISO-compliant 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.
  The MCV provides definitions for terms on which the SDMX Cross-Domain Metadata Concepts work is built.
--1.
--11. (((
  == {{id name="_Toc38924"/}}8.3 Statistical Subject-Matter Domains ==
--)))
  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 SDMXconformant technical systems within and across statistical domains. The organisation of the content of such schemes is supported in SDMX as a Category Scheme.
  SDMX Statistical Subject-Matter Domains will be listed and maintained by the SDMX Initiative and will be subject to adjustment.
--1. (((
  = {{id name="_Toc38925"/}}9 Looking Forward =
--)))
  The SDMX initiative sees this set of data and metadata formats and registry services interfaces standards as useful in creating more efficient and open systems for statistical exchange. It is anticipated that SDMX will refine these standards further as they are implemented, so as to build on the interoperability enabled by having a set of standard formats and exchanges based on a common information model.
  The review process for version 2.0 and 2.1 has suggested that future work should take advantage of a wider participation of the SDMX user community (statistical offices, central banks and other national and international organisations dealing with statistics) in further enhancing the Technical Standards and improving its use.
--1. (((
  = {{id name="_Toc38926"/}}10 Validation and Transformation Language =
--)))
  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