1. MSDs and combined metadata reporting
Luca Gramaglia
Team Leader, SDMX implementation
Eurostat

2. Statistical Data and Metadata Exchange
S D M X
Statistical Data and Metadata Exchange
Structural metadata: Metadata that identify and describe data
Reference metadata: Metadata describing the contents and the quality of the statistical data
As the name indicates, SDMX is not just about data exchange: it is also about metadata.
Structural metadata are needed to identify, use, and process data matrixes and data cubes, e.g. names of columns or dimensions of statistical cubes. Structural metadata must be associated with the statistical data, otherwise it becomes impossible to identify, retrieve and navigate the data or reference metadata.
Reference metadata includes a) “conceptual” metadata, describing the concepts used and their practical implementation, allowing users to understand what the statistics are measuring and, thus, their fitness for use; b) “methodological” metadata, describing methods used for the generation of the data (e.g. sampling, collection methods, editing processes); c) “quality” metadata, describing the different quality dimensions of the resulting statistics (e.g. timeliness, accuracy).

3. Reference metadata Data
In Eurostat, we collect both data and reference metadata from EU Member States using SDMX.
Data

4. For every dataset… …harmonised metadata
We have established a common metadata reporting structure (in SDMX terms we created a common European MSD) that allows us to disseminate harmonised metadata for all of our published datasets.
We also have an increasing number of national metadatasets published for our different disseminated datasets.

5. Reference Metadata Data
But there is one issue: the production process for the reference metadata and for the data are done in parallel. The production of data usually follows standardised production procedures which are often automated. The production of reference metadata, on the other hand, is often hand-made.
Data

6. Reference Metadata Data
But that's not good enough. As long as we are keeping metadata and data production separate, we are not taking full advantage of the possibilities SDMX can offer.
We can link the metadata to the data in a much more structured manner, taking full advantage of the SDMX Information model. This would allow easier querying of the metadata related to data.
But perhaps more importantly, we can link the relevant process metadata coming from the data production systems to the reference metadata. Revision rates, validation issues, relevant parameters used in seasonal adjustment. SDMX is a great enabler to provide this integrated metadata reporting, by providing a standard way to exchange data and metadata. And in Eurostat we have started to do that.
Data

7. Closer integration between SDMX metadata and SDMX data
Development of global MSD by the SDMX community
When you think about SDMX for data… …don't forget about metadata