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1. Introduction

1.1 Metadata strategy
Give an explanation of the overall strategy for managing metadata across the organization. For example, the mandate/programme providing framework for the project, and basic metadata management principles used.

1.2 Current situation
Outline the current metadata management project(s) being planned or implemented. This can be a short overview. The detail about the project will be provided in the following sections.

2. Modelling the Information and Processes of a Statistical Organization.

2.1 Statistical information model
Provide a diagram or explanation of the statistical information model used in your organization. Explain how/when it was developed.
If you don't have an integrated model of all information managed in your organization, you probably have partial models to manage independently statistical metadata, statistical methods, architectural principles, policy provisions and similar things. In this case, you can provide separate descriptions for these partial models.

2.2 Adoption of GSIM
Do you intend to adopt GSIM? Are you in the process of adopting it? If yes, do you intend to implement it as is, with possible extensions, or to map your own model(s) onto it?

2.3 Statistical business process model
Provide a diagram or explanation of the statistical business process model used in your organization. Explain how/when it was developed.
Illustrate how this maps to the Generic Statistical Business Process Model (1. Specify Needs, 2. Design, 3. Build, 4. Collect, 5. Process, 6. Analyse, 7. Disseminate, 8. Archive, 9. Evaluate, 10. Quality Management/ Metadata Management – a more detailed description of this model is published at www.unece.org/stats/gsbpm ).

2.4 Relation to other models
Do you intend to use GSIM in conjunction with GSBPM, or with your own statistical business process model? 
Do you intend to use GSIM in conjunction with an international implementation standard (for example, DDI and/or SDMX) or your own implementation standard?

3. Statistical Metadata in each phase of the Statistical Business Process

3.1 Metadata Classification
Describe the classification your organization uses to group metadata or differentiate between types of metadata.
Example groups of metadata are 1. Survey Metadata, 2. Definitional Metadata, 3. Methodological Metadata, 4. System Metadata, 5. Operational Metadata, 6. Quality

3.2 Metadata used/created at each phase
Clarify whether your organization manages metadata throughout the statistical business process, or only at particular phases (eg ‘Design’, or ‘Disseminate’). It is recognized that not all offices have “end-to-end” metadata systems. Please just provide information for those phases that are relevant to your project(s).
Describe the metadata used or created at each phase of the statistical business process.
The intention of this section is to provide some more detailed information about the metadata that is created, captured and reused at each point of the business process.

3.3 Metadata relevant to other business processes
Describe the metadata used for other business processes, such as management and budgeting, which may not be directly related to the statistical business process.

4.1 Metadata system(s)
Describe the current metadata system, or systems, that are the subject of this case study. Explain how they fit within other organizational systems and clarify which point they are at (i.e. scoping, planning, implementation, etc). Explain how the system(s) and the business process above are interrelated. Descriptions of planned changes and additions would also be helpful.
This section is intended as an overview of the system, and should not overlap with Section 5. It can contain links to more detailed descriptions of individual components if available.

4.2 Costs and Benefits
Describe the costs and benefits of the project(s). Costs should preferably be given in terms of human resources rather than money.

4.3 Implementation strategy
Explain if the project is being implemented with a step-wise or ‘big-bang’ approach. Provide a timeline of project milestones if possible.

5.1 IT Architecture
Provide an overall description of IT architecture (eg. Service Oriented Architecture) and architectural scheme.

5.2 Metadata Management Tools
List the tools used for metadata management.
Information about the tools and techniques used for data and metadata integration (to link metadata repositories to statistical processing tools and data).

5.3 Standards and formats
Describe the standards and file formats being used.

5.4 Version control and revisions
Describe approach to version control and managing revisions.

5.5 Outsourcing versus in-house development
Describe the current situation and planned developments by outsourcing or using resources in-house.

5.6 Sharing software components of tools
Please list and briefly describe any software components and/or tools that you would be willing to share with other statistical organizations. Please indicate if they are available free or for a charge.

5.7 Additional materials 
Links to additional materials such as data models

6.1 Overview of roles and responsibilities
Provide a list of roles involved in metadata/statistical business process management (e.g. subject matter statistician, survey manager, metadata manager etc.). Include details such as job title, responsibilities, organisation group (e.g. Subject matter, IT, methodology & standards, central metadata group etc), and reporting relationships.
It would be useful if you could also provide a list and contact information for all specialists in metadata management in your office.

6.2 Metadata management team
Describe the team/individuals involved in development and maintenance of metainformation systems.

6.3 Training and knowledge management
Explain strategies in place for training staff working on metadata projects and for knowledge management of metadata issues across the organization.

6.4 Partnerships and cooperation
Describe existing or planned cooperation with other organizations in relation to metadata management projects.

6.5 Other issues
Describe any other organizational and workplace culture issues that impact on metadata management.