1. ESTP course on Statistical Metadata – Introductory course
Statistics Netherlands, The Hague,18-19 February 2013

2. at Statistics Netherlands
Implementation of the
Data Service Centre
at Statistics Netherlands
Harry Goossens
Programm Manager DSC 2

3. Agenda Why, What, How ? The CBS Metadata model
The CBS Business Architectuur
Steady States
Implementation
Daily practice
Demo 3

4. Data Service Centre: What is it ?
Fundamental corner stone of the CBS Business Architecture
Central ‘vault’ with Steady States, linking:
statistical data (facts & figures)
conceptual metadata (description)
technical metadata (user’s guide)
documentation
Implementation of the Dutch metadata model

5. DSC: The concept No data without metadata
Based upon dedicated metadata model
Strict distinction between the data that are actually processed and the metadata that describe the definitions, the quality and the process activities
Steady states are explicitly designed for re-use.
The metadata (of steady states) are generally accessible and are standardised as much as possible

6. Generic services: Catalogue: searching & finding Metadata management
DSC: What offers it ?
Generic services:
Catalogue: searching & finding
Metadata management
Centralised data distribution
Authorisation management
Automatic process interfacing
Archiving of statistical datasets
Version management

7. DSC: Conceptual metadata
Metadata that describes the data in a generic, non specific way,
in all the various phases of the statistical proces:
Input - description of received data; - terminology of the supplier (internal and external)
Processing - description of data produced in various statistical processes; - internal (and international) standards / guidlines
Output - description of publishable output data - definition of (sub)populations, outputvariables, object types content description,

8. DSC Metamodel (simplified)
Variable
Data Design
1 : 1
1 : n
Technical
Metadata file (XML)
Context
Variable
1 : n
Documentation
(Word, PDF,….)
Datasets
(ASCII CSV, Fixed)
Codelists
(XML)
1 : 1

9. Mission, Policy and Strategic Objectives
CBS Business Architecture (simplified)
Mission, Policy and Strategic Objectives
Design Process
Design Data
External users
with
information needs
DSC
Metadata
Catalogue
Metadata
Management
External
Suppliers
of data
Collect
Data
Process
Data
Disseminate
Data
DSC
Data storage
Data (steady states)

10. What are steady states ?
A steady state is a data set together with information for its correct interpretation.
Rectangular - Rows represent units (micro) or classes of units (macro) - Columns represent variables
Heading: population, time
Dataset design (vary time): in design phase
Dataset design is like a template of a table: only borders and heading
1 Dataset design, n Datasets

11. Why steady states ? Reduce storage: Secure the statistical proces:
Store once
Re-use many times
Secure the statistical proces:
Each steady state is a guaranteed fall back point
Improve consistency:
Every following process uses the same dataset
‘Single point of truth’ principle
Improve flexibility
Enables independent, generic proces design

12. Implementation Micro model simplyfied for practical use
Skip / Combine objects
Reduce attributes
Why Documentum ?
Completely object orientated,
enables to implement DSC metamodel
Largly configurable (user interface, authorisation, etc.)
Large flexibillity
Proven technology
TaskSpace

13. DSC system - Functionalities
Taylor made user interface (TaskSpace)
Maintenance of meta objects
Constraints mostly in interface, not in DB/repository
Specific flexible search engine
Various entrances, easy to extend
Import & Export of datasets
Modified according to model
Interface for bulk-import of metadata
Based on standard XML schema
Conceptual and technical meta

14. Daily practice - Challenges
Available metadata quality often poor
Great variety, each statistic own way of describing
Often tool based (SPSS), more technical then logical
Definition = question from survey
Minimum mapping with DSC model
No real urge
Although rated IMPORTANT, low priority
No clear ownership, resonsibility not felt
Extra work without direct gain (burden)

15. Daily practice - Road map
Explaining the concept & metadata model
Requirements, guidelines
Stocktaking
What meta is available ?
How extensive or poor ?
What quality, actuality ?
Re-usability
Mapping on the model
(Re)Design Datadesigns
Matching attributes

16. Daily practice - Chances
Look for added value
Problems ?
Wishes ?
(Long) Wanted improvements ?
Re-usability
Define pilot
Quick hands on experience, short cycle
Good estimation time & resources
‘Proof of the design pudding’

17. Daily practice – At work (1)
Excel template, Nesstar Publisher
Porch / Ballot
Visual check on guidelines
Automated check on completeness, inconsistencies,
relations VARIABLE – CONTEXT VARIABLE etc.
Advise for corrections/improvemnts: by owner (statistics) !
Define and set authorisations
Groups for import, export, metadata maintenance

18. Daily practice – At work (2)
Metadata in DSC-system
Define datadesign
Import TMF (xml)
Bulkimport Variables (xml)
Import dataset (s)
Search
Export data & metadata