SDMX: A brief introduction

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Presentation transcript:

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

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 (email, CD-ROMs, file uploads etc.); Data being stored in various places (USB, hard drive, servers, cloud etc.);

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;

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.

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

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 !

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

Modelling statistical data in SDMX

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)

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.