1. The Data Cube Vocabulary: Deploying SDMX as RDF from Existing Systems
This paper has been amended from the January 2014 version by adding a scenario: SDMX web service returning RDF
Chris Nelson
Zurich November 2014
SDMX Technical Working Group

2. SDMX Technical Working Group
Presentation Scope
Revised Document Content and Organisation
Overview of RDF and the RDF Data Cube Vocabulary (mainly for newcomers to the TWG)
Use Case Scenarios
Recommendations for use with SDMX
Zurich November 2014
SDMX Technical Working Group

3. SDMX Technical Working Group
Presentation Scope
How RDF, the set of technology standards which underpin the Web of Linked Data, can provide a supplemental dissemination format for statistical agencies familiar with SDMX
avoiding:
Inconsistencies between parallel dissemination chains (e.g. in SDMX and in RDF format) from the same organization with different updates, or from different entities re-disseminating the same data;
Too many manipulations of the data;
Existence of a set of domain-specific, tailor-made software tools, which could be more efficiently replaced by one standardized and generic set of tools for working with SDMX-based RDF data and structures.
This document describes some deployment scenarios for organizations which are disseminating SDMX-ML today, and discusses how to best expose their SDMX data and metadata as RDF using the Data Cube Vocabulary.
Zurich November 2014
SDMX Technical Working Group

4. - presentation concentrates on this
Revised Document
Document Organisation ( = added)
Overview
Characterization of the RDF Standards 
The Intended Capabilities of the Data Cube Vocabulary 
Existing Data Cube Implementations
RDF and Other Standards (DDI, SDMX, GSIM) 
The Data Cube Vocabulary: Deploying SDMX as RDF from Existing Systems
Additional Considerations for Publishing RDF
Conclusions
Annex 1 – RDF Issues
Issue Remarks
- presentation concentrates on this
Zurich November 2014
SDMX Technical Working Group

5. SDMX Technical Working Group
Revised Document
Feedback:
Scenario B (SDMX Web Service masquerades as a SPARQL end point) was discarded in the version in June 2013 as it was not deemed to be the culture of the LOD community. As this scenario is being trialled by an NSI it is re-introduced
The possibility to stream RDF data to a file or Triple Store using the SDMX Open Source is included in the relevant scenarios
Zurich November 2014
SDMX Technical Working Group

6. What is LOD (linked open data)
In 2006 Tim Berners-Lee outlined four principles of Linked Data :
Use URIs to identify things
Use HTTP URIs so that these things can be referred to and looked up (dereferenced) by people and user agents
Provide useful information about the thing when its URI is dereferenced, using standard formats such as RDF/XML
Include links to other, related URIs in the exposed data to improve discovery of other related information on the Web
Slide reproduced from METIS 2013 WP 10
Zurich November 2014
SDMX Technical Working Group

7. RDF Primer: What is SKOS “Simple Knowledge Organization System”
Provides a model for expressing the basic structure and content of concept schemes such as:
thesauri,
classification schemes,
subject heading lists,
taxonomies,
folksonomies,
and other similar types of controlled vocabulary.
Slide reproduced from METIS 2013 WP 10
Zurich November 2014
SDMX Technical Working Group

8. RDF Primer: What is an RDF Triple
A standard knowledge model for making statements about resources based on a few elegant ideas:
Everything has a URI.
Knowledge is a series of Subject-Verb-Object statements (triples)
Slide reproduced from METIS 2013 WP 10
Joe
Smith
Zurich November 2014
SDMX Technical Working Group

9. SDMX Technical Working Group
First: New Terms
SKOS – simple knowledge organisation system
XKOS – Extended to SKOS developed by FAO, INSEE, BLS, GESIS, and others to better support statistical classifications
Used for concepts
SKOVO – statistical core vocabulary
has limitations so this is extended for Data Cube Vocabulary
TURTLE – terse RDF triple language
SPARQL - SPARQL protocol and RDF query language
FOAF – for organisations
Zurich November 2014
SDMX Technical Working Group 9

10. Data Cube Requirements/Design
DataCube uses a sub-set of the overall SDMX information model
It is only concerned with discovery and processing of data on the Web
As a result, it is a very simplified model
Use of the COG is mandatory in DataCube
If a concept exists, you are required to use it!
The burden of mapping to the COG is assumed by the data producer/publisher
Several existing RDF namespaces have been used (Dublin Core, FOAF, SKOS, SCOVO, etc.)
This is best practice in the Linked Data world
Zurich November 2014
SDMX Technical Working Group 10

11. The Data Cube Vocabulary

12. RDF Data Cube Vocabulary
structured by
SDMX Data Set
SDMX Data Structure Definition
dimensionality
RDF Data Cube Vocabulary

13. Data Cube: An Observation
DataCube is a W3C recommendation, and has gained some momentum
The data producers using SDMX can also publish in the Data Cube Vocabulary (DCV)
As with any other RDF publication the applications processing the RDF must understand the DCV data model to make sense of the data
Therefore applications wishing to process any additional information added to the DCV triples need to understand the model of the attached data
Zurich November 2014
SDMX Technical Working Group 13

14. SDMX Technical Working Group
The SDMX Perspective
If you are using SDMX today (GESMES or XML), what does this mean?
Most DataCube implementation today is being done by organizations that don’t use SDMX-ML
For statistical organisations there is an increasing interest in RDF and there is a need to be able to integrate DataCube as an alternative query and delivery sourced originally from existing SDMX-based systems
Zurich November 2014
SDMX Technical Working Group 14

15. SDMX to RDF Publishing Scenarios
 Publishing RDF triples as flat files to a Web Server
 Populating a SPARQL endpoint with triples
The enhancement of an SDMX-conformant RESTful web-service to support RDF
SDMX Web Service masquerades as a SPARQL endpoint
Or ??
SDMX Web Service outputs RDF: user system queries using SDMX web services
Zurich November 2014
SDMX Technical Working Group

16. SDMX and RDF: Scenario 
RDF File
Using SDMX Component Architecture
Data Cube Writer
SDMX
Writer Interface
JENA
Statistical
Dissemination
System
Either Or
SDMX-ML to RDF Transformer
SDMX-ML File

17. Scenario : Publish RDF triples as flat files
Publish to a server exposed to the web
Packaged in a meaningful way using named graphs e.g.
Data by data set
Structures
all in one file or
codelists and concepts in one file and DSDs in another file
Observations
Needs to be kept up to date
Either republish as a replace or as an incremental update
Simple Approach
But not easily queryable
Discovery and linking tools typically work with SPARQL endpoints
Zurich November 2014
SDMX Technical Working Group

18. SDMX and RDF: Scenario 
Using SDMX Component Architecture
Triple Store
(DataCube)
Data Cube Writer
Statistical
Dissemination
System
Either
SDMX
Writer Interface
JENA Or
SDMX-ML File to RDF Transformer
SDMX-ML
File
RDF Service
SPARQL

19. Use Case: Populate a SPARQL endpoint
Deploy RDF triple in a “triple store”
Dedicated database system that natively understands SPARQL queries
Supported by many RDF tools
Some support variety of flavours of RDF
XML, TURTLE, N-Triples
Data could be updated at level of the dataflow
Observations
Good support for linking (the reason for LOD)
Good support for cross dataflow queries
Data with some common dimensions
Zurich November 2014
SDMX Technical Working Group

20. (Reintroduced) SDMX and RDF: Scenario 3
SDMX-ML
SDMX-ML to RDF Transformer Or
Statistical
Dissemination
System
Either
DataCube
Writer
SDMX REST Query
SPARQL
Web Service
RDF Service

21. (Reintroduced) SDMX and RDF: Scenario 3
SDMX-ML
SDMX-ML to RDF Transformer Or
Statistical
Dissemination
System
Either
DataCube
Writer
SDMX REST Query

22. Use Case: Populate a SPARQL endpoint
Enable an SDMX system to act as a SPARQL endpoint
database system that has a web service that transposes a SPARQL query to an SDMX query
Observations
Data are kept up to date
Web service could extend support to many RDF tools
Some support variety of flavours of RDF
XML, TURTLE, N-Triples
BUT
No support for linking (major reason for LOD)
No native SDMX support for cross dataflow queries
Zurich November 2014
SDMX Technical Working Group

23. SDMX Technical Working Group
Considerations
If RDF is treated as a completely separate syntax, then the burden of data management is doubled
If it is treated as a delivery format (just another data writer), then it is relatively easy to implement
Up-front cost for tools development
Low ongoing maintenance
The benefits of RDF-based technology are realized in a cost-effective manner
Zurich November 2014
SDMX Technical Working Group 23

24. SDMX Technical Working Group
Note on Identifiers
Retaining a mechanism to enable same object to be expressed in different syntaxes is deemed to be important for SDMX
All identifiers in RDF are URIs and optimally these must be resolvable URLs
Structure identifiers in SDMX are URNs and these can be transformed to URIs
Data set can be identified using data set Id and timestamp (in ISO format)
Zurich November 2014
SDMX Technical Working Group

25. SDMX Technical Working Group
Related Work
One of the SDMX ESSNet projects has created a formal ontology out of the Common Metadata Vocabulary
This work is really a first draft, but it is very promising
It would combine well with DataCube to help people find the data they are looking for
SKOS (Simple knowledge organization system) extensions (XSKOS) enable support for statistical classifications as part of DDI-RDF
There is work to describe microdata in RDF, based on DDI
Zurich November 2014
SDMX Technical Working Group 25

26. Recommendation for SDMX Systems
Publish data and structures (DSD, Concepts, Code Lists) as RDF
Preferably publish in a Triple Store
Keep update mechanisms in current systems
Add new data versions or replace wholesale existing versions
Linked data (3rd party links to the data) can still work if URLs do not change
Base URLs on SDMX URN (for structures) and data set Id plus time stamp (for data)
Zurich November 2014
SDMX Technical Working Group