1. 11. The future of SDMX Introducing the SDMX Roadmap 2020
ESTP Training
Marco PELLEGRINO Eurostat, Unit B.5 Data and Metadata Standards and Services
Luxembourg, March 2017

2. SDMX Roadmap 2020 Endorsed by the SDMX sponsors
High-level strategy, strategic context for future work
4 priority areas for :
Strengthening the implementation of SDMX
Making data usage easier via SDMX
Using SDMX to modernise statistical processes, as well as continuously improving the standards and IT infrastructure
Improving communication in general, including a better interaction between international partners

7. SDMX Actions (2016-2018) SDMX Action Plan 2016-2018(
At the beginning of 2016, the SDMX sponsors approved a "Roadmap 2020" presenting a vision of where SDMX is heading in the next few years and outlining a series of strategic objectives. These priorities are further developed in the present Action Plan covering the period until end of 2018.
Each action is mapped to one of the four priority areas highlighted in the Roadmap, describing the work that can be deployed in a relatively short timeframe for:
Strengthening the implementation of SDMX
Making data usage easier via SDMX (especially for policy use)
Using SDMX to modernise statistical processes, as well as continuously improving the standards and IT infrastructure
Improving communication in general, including a better interaction between international partners
The SDMX organisations will monitor the progress of these actions on an annual basis, in particular for identifying gaps in the current implementation program and for discussing priorities and resources needed to support the actions. The Action Plan will be updated yearly, based on a rolling calendar.

8. Reinforcing the SDMX business case
To improve the exchange of statistical data and metadata, which is complex, resource intensive and expensive
To provide a standardisation layer replacing or reconciling specific approaches and solutions
To take advantage of opportunities related to new technologies for machine to machine exchange
In the ESS:
2007: Endorsement at ESS Committee
2008: UNSC recognition
: SDMX inserted in legal acts for data-metadata exchange

9. Eurostat: from the start-up phase…
Initial focus on data collection from countries
Shared DSDs with ESS countries for regular data exchange
SDMX-compliant reference metadata (ESMS, ESQRS,…)
DSDs for global use with international org. (ESA, BoP)
SDMX dissemination web services
This helped the integration of statistical processes in the European Statistical System.
SDMX-ML + EDI = 47.5% exchanged files. SDMX-EDI declining, XML increasing. CSV/Excel (mappable to SDMX)= 33.5%. Examples of lowering the burden to data providers, with webforms and CSV/SDMX
SDMX concepts and codes for creating Metadata Structure Definitions.
ESS Metadata Standards covering all Eurostat domains on the web
Dissemination chain: list of available datasets, structure definitions, download, customizing requests for data
Some issues:
Business buy-in slow, as considerable initial investment needed
Real advantages not clear enough for the business
Heavy project management needed

10. SPECIFY NEEDS
DESIGN
BUILD
COLLECT
PROCESS
ANALYSE
DISSEMINATE
EVALUATE
SDMX-RI infrastructure enabling buy-in and use of web services for exposing data
Loaded in
Exposed using
SDMX-RI
Data
DDB
Web dissemination
Census Hub: opened in December 2014
32 countries connected (EU & EFTA)
30 using the SDMX-RI
Census Hub

11. SDMX for Linked Open Data
SPECIFY NEEDS
DESIGN
BUILD
COLLECT
PROCESS
ANALYSE
DISSEMINATE
EVALUATE
SDMX for Linked Open Data
Single point of access to a growing range of data from the institutions and other bodies of the EU, free to use and reuse.
Innovative use. Transparency and accountability of EU institutions.
Managed by the Publications Office of the European Union. EU's open data policy is the responsibility of the Directorate-General for Communications Networks, Content and Technology of the Commission.
Based on RDF (Resource Description Framework - a family of specifications published by W3C allowing for machine-actionable, semantically rich linking of things found on the Web)
Main RDF vocabulary for statistical data: → Data Cube Vocabulary (simplified version of the SDMX model covering data structures)

12. …towards a maturity phase
SPECIFY NEEDS
DESIGN
BUILD
COLLECT
PROCESS
ANALYSE
DISSEMINATE
EVALUATE
…towards a maturity phase
 Standard metadata layer for the description and use of data and metadata throughout the process (broadening the scope)

13. Better support for multiple measures in registers Extending code lists
VTL-based Validation-Transformation services in SDMX (rule sets, queries, web services, information model, integration with GSIM, etc.)
Better support for multiple measures in registers
Extending code lists
Modelling artefacts (fine-tuning)
Facilitating reference metadata exchange
Describing more formats (CSV, JSON) …
Mapping to other standards (RDF Linked Open Data, DDI, XBRL, GeoStat,…)
Better documentation and training
More guidelines on modelling

14. Thanks for your attention!
SDMX Roadmap: The new vision
Thanks for your attention!