1. Presentation to SISAI Luxembourg, 12 June 2012
GSIM 0.4 and beyond
Presentation to SISAI
Luxembourg, 12 June 2012

2. What is GSIM?
The Generic Statistical Information Model (GSIM) is a reference framework of information objects, which enables generic descriptions of the definition, management, and use of data and metadata throughout the statistical production process

3. GSBPM & GSIM: modular opproaches
GSBPM is a business process model GSIM models information on the process
GSBPM
Sub-process
Input
- Data
- Parameters
Output
Transformed data
Process metrics

4. GSIM 0.4 – Group Level Activity Production Information Conceptual
Describe each area
Describe the relationships between each area
Brief indication as to why we used this organisation scheme
Indicate what you would use this level for?

5. Dissemination Program
GSIM 0.4 – Set Level
Activity
Production
Conceptual
Information
Information Request
Process Control
Population Unit
Dataset
Acquisition Program
Process Component
Variable
Product
Useful for communicating with subject matter experts
Statistical Program
Rule
Classification
Service
Dissemination Program

6. GSIM 0.4 – Object Level
[Name] – for identifying and defining the individual information objects, and the relationships between them, used or produced in the statistical process

7. Example of detailed work
Process
Statistical Activity
GSIM Base
Data Structures
Data Sources
Statistical Products
[Name] – for identifying and defining the individual information objects, and the relationships between them, used or produced in the statistical process

8. Activity Production Information Conceptual Provision Agreement
Provision for formalisation of arrangements for data acquisition and dissemination
Provision Agreement
Process Step Definition
Provider
Production
Activity
Conceptual
Information
Methodology applies to processes in all areas
Methodology
Balanced support for all data acquisition channels
Information Request
Process Method
Acquisition Program
Dissemination Program
Process management for all areas of activity
Statistical Project
Process Step Design
Separation of Statistical, Acquisition, and Dissemination programs, with central role for Methodology
Balanced support for multiple dissemination channels
Statistical Program
Process Control
Process Step Execution
Statistical projects access shared data
Mapping of processes to support managed operations
Rule
Shared Data Resource, maintained corporately, for use by all statistical programs
Data Resource
Data Set
Statistical Products
Variable
Population Units
Concept
Data Structure
Cube Structure
Unit Data Structure
Basic infrastructure for critical base elements
Value Domain
Record Structures
Classification
All structures and relationships described in metadata to support automated processes

9. Activity Production Information Conceptual Provision Agreement
Provision for formalisation of arrangements for data acquisition and dissemination
Provision Agreement
Process Step Definition
Provider
Production
Activity
Conceptual
Information
Methodology applies to processes in all areas
Methodology
Balanced support for all data acquisition channels
Information Request
Process Method
Acquisition Program
Dissemination Program
Process management for all areas of activity
Statistical Project
Process Step Design
Separation of Statistical, Acquisition, and Dissemination programs, with central role for Methodology
Balanced support for multiple dissemination channels
Statistical Program
Process Control
Process Step Execution
Statistical projects access shared data
Mapping of processes to support managed operations
Rule
Shared Data Resource, maintained corporately, for use by all statistical programs
Data Resource
Data Set
Statistical Products
Variable
Population Units
Concept
Data Structure
Cube Structure
Unit Data Structure
Basic infrastructure for critical base elements
Value Domain
Record Structures
Classification
All structures and relationships described in metadata to support automated processes

10. Considerations for future work
The devil is in the detail
Manage expectations
Maintain the momentum
Continue to involve the right expertise
Communicate GSIM effectively
The devil is in the detail
Moving targets limit ability to map and test GSIM
Managing expectations
Maintaining the momentum when benefits not immediate
Involving the right expertise

11. Detailed roadmap has been developed
Next steps for GSIM V1.0
Detailed roadmap has been developed
Further model specification
Use cases
Governance and maintenance
Communication

12. Supporting the move away from silos Common, agreed terminology
GSIM V1.0 will enable
Supporting the move away from silos
Common, agreed terminology
Support for broad-based data capture
Support for diverse dissemination channels
Incorporation of processes
Consistency with existing standards and approaches
Improve communication between
disciplines involved in statistics production
users, producers and providers of official statistics
Generate economies of scale
reuse of information, methods and technology
Enable modern ways of making statistics
configurable, rule-based and modular
Provide a basis for flexibility and innovation
easy deployment of new statistical products
adoption of new types of statistical data sources
Supporting the move away from silos
Data acquisition and management separated from Statistical activities
Common, agreed terminology
so we can share across agencies
Support for broad-based Data Capture
not just focussed on surveys
Support for diverse Dissemination Channels
so we can have impact and stay relevant
Incorporates processes
so we can automate and industrialise
Consistent with existing standards and approaches
DDI, SDMX, CORE, ISO 11179, Neuchatel

13. Feedback on GSIM 0.4
By 15 June 2012 to or