1. SDMX: A brief introduction
IPA WORKSHOP ON INTERNATIONAL TRADE IN SERVICES STATISTICS
Luxembourg, 2-3 June 2015

2. Background issues:
Data being collected in multiple ways (surveys, files, web queries, metadata etc.);
Data being transmitted in various formats (paper, excel, flat files etc.)
Data being transmitted in various media ( , CD-ROMs, file uploads etc.);
Data being stored in various places (USB, hard drive, servers, cloud etc.);

3. Multiple organisations collecting similar or same data;
Similar concepts in wording can have a different content;
Increasing burden on organisations (collection, maintenance and managing);
The intensive and manual nature of data and metadata collection;
Errors and inconsistencies;

4. So what is SDMX?
The 'Statistical Data and Metadata eXchange' is an international initiative aimed at developing and employing more efficient processes for the exchange and sharing of statistical data and metadata among international organisations and member countries.

5. So what is SDMX?
A model to describe statistical data and metadata
A standard for automated communication from machine to machine
A technology supporting standardised IT tools
for which statisticians agree to use common descriptions and guidelines
driven by these common descriptors for all to reuse
developed as wide-ranging open source software

6. SDMX is not just a transmission format !
SDMX Information Model
Content Oriented Guidelines
IT Infrastructure for exchange and sharing
SDMX is not just a transmission format !

7. Describe statistics in a standard way Objects and their relationships
Data Structure Definition (DSD), Concepts, Code List
Central management and standard access
SDMX Registry, SDMX Web Services
Cross Domain Concepts
Cross Domain Code Lists
Statistical Domains
Metadata Common Vocabulary
Push
Provider generates and sends file to receiver
Pull
Provider opens web service to data
Receiver downloads regularly
Hub
Special case of pull: receiver downloads on end user request

8. Modelling statistical data in SDMX

9. Data Set Structure
Computers need to know the structure of data in terms of:
Dimensionality
Additional metadata
Measures (Observation)
Concepts
Valid content
Code Lists
Non coded format (integer, date, text)

11. A DSD comprises
Dimensions that identify the observation value
Attributes that add additional information about the observation value (as a value or the context of the value)
Measures that are the observation values
Any of these may be
coded
text
date/time
number
etc.