Unit 1: Introduction to Transcoding Data
In this unit, we’ll explain how SDMX supports data management within the statistical ecosystem.
Data and statistics in a statistical ecosystem
In relation to this, data are often collected at a granular level and disseminated at an aggregate level to facilitate key messaging and understanding. In addition, data are repackaged according to the requirements of various international actors and projects, including BIS, OECD, IMF, ECB, Eurostat, World Bank, SDGs, UN Agencies, and many more.
As such, it is common that the same data needs to be described (structural model) in different ways for various processes and actors.
Data systems within a statistical ecosystem
It is often necessary to have a bridging strategy to facilitate implementing SDMX in some process areas and data domains while continuing business-as-usual elsewhere in the statistical system.
One important capability to support automation and data quality is the ability to codify these interconnections and transcode data from one data model to another as they move through the system. SDMX provides these capabilities in the form of structure maps.
Use case examples
SDMX assists in a variety of use case examples. There are capabilities in the SDMX standard and open source SDMX tools which support these use cases.
Select each use case example to learn more.
Use templates
Adopt SDMX XLSX templates and the benefits that they offer and then transcode the data to a model
supported by existing production systems.
Transcode existing data
With SDMX, easily transcode existing production data according to the requirements of data partners,
such as SDGs and other reporting agencies, in a straightforward and automated manner.
Transcode to another standard
With SDMX, transcode production data modelled according to one coding system (e.g., National Education
System, Internal country coding) to another standard (e.g. ISCED, ISO3, M49) for collection, reporting,
dissemination, or data production purposes.
Use transcoded data
Collect and produce statistics in the traditional manner and then transcode them into SDMX format and
according to the SDMX data model and use this transcoded data in SDMX-enabled processes and tools.
SDMX capabilities
The SDMX method uses SDMX structure maps and SDMX representation maps along with a tool, such as the FMR to implement transcodings required in the various use cases.
The FMR transformation feature supports:
- Testing the transcoding to ensure the expected results are realised
- Transcoding the data interactively using the FMR User Interface (UI)
- Transcoding the data in an automated manner using the FMR transformation web service (API)
What do you know?
Now that you’ve completed our introduction, try this.
Which of the following are considered SDMX capabilities?
Select all that apply and then select Submit.
Some of SDMX capabilities include the following:
- Adopting SDMX XLSX templates and the benefits that they offer and then transcoding the data to a model supported by existing production systems.
- Easily transcoding existing production data according to the requirements of data partners, such as SDGs and other reporting agencies, in a straightforward and automated manner.
- Transcoding production data modelled according to one coding system (e.g. National Education System, Internal country coding) to another standard (e.g. ISCED, ISO3, M49) for collection, reporting, dissemination, or data production purposes.
- Collecting and producing statistics in the traditional manner and then transcoding them into SDMX format and according to the SDMX data model and using this transcoded data in SDMX-enabled processes and tools (Note: Transcoding is not required for this process, but is a value add).
All options are correct.
Some of SDMX capabilities include the following:
- Adopting SDMX XLSX templates and the benefits that they offer and then transcoding the data to a model supported by existing production systems.
- Easily transcoding existing production data according to the requirements of data partners, such as SDGs and other reporting agencies, in a straightforward and automated manner.
- Transcoding production data modelled according to one coding system (e.g. National Education System, Internal country coding) to another standard (e.g. ISCED, ISO3, M49) for collection, reporting, dissemination, or data production purposes.
- Collecting and producing statistics in the traditional manner and then transcoding them into SDMX format and according to the SDMX data model and using this transcoded data in SDMX-enabled processes and tools (Note: Transcoding is not required for this process, but is a value add).
All options are correct.
Some of SDMX capabilities include the following:
- Adopting SDMX XLSX templates and the benefits that they offer and then transcoding the data to a model supported by existing production systems.
- Easily transcoding existing production data according to the requirements of data partners, such as SDGs and other reporting agencies, in a straightforward and automated manner.
- Transcoding production data modelled according to one coding system (e.g. National Education System, Internal country coding) to another standard (e.g. ISCED, ISO3, M49) for collection, reporting, dissemination, or data production purposes.
- Collecting and producing statistics in the traditional manner and then transcoding them into SDMX format and according to the SDMX data model and using this transcoded data in SDMX-enabled processes and tools (Note: Transcoding is not required for this process, but is a value add).
Coming next
In the next unit, you’ll learn about transcoding data and the various types of mappings typically used.
Need help finding something? I am an AI Assistant that's here to help!
Welcome to SDMX AI assistant
What are you looking for?
By using this AI-powered service ("Service"), you acknowledge and agree to the following:
This Service uses generative AI to assist with statistical analysis and research. While the Service strives to deliver useful information, the output ("Output") may contain inaccuracies, omissions, or biases. The Output is provided for informational purposes only and should not be considered professional advice. You remain responsible for how you interpret and use the Output.
The BIS makes no warranties regarding the accuracy or completeness of the Output and accepts no liability for any loss or damage resulting from its use.
Do not include or share personal, private, confidential or proprietary information when using the Service.
By using this technology, you agree to the Terms and Conditions.
How the assistant can help you
Understand SDMX standards
Ask and get clear explanations about SDMX standards.
Navigate the website
Find tools and documentation on website quickly.
Explore SDMX tools
Ask about API, software and libraries supporting SDMX.
Access documentation
Locate technical guides, specifications, and FAQs.