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Like many National Statistical Offices around the world, Statistics New Zealand faces a number of 'external' and 'internal' challenges in the years ahead. 'External' challenges include: the need to minimise respondent burden, improve timeliness of existing data releases, improve 'time to market' for new data releases, increased use of administrative data, and better access to data (incl. micro-data) by users. While 'internal' challenges include: provide a better work environment for staff, replace an ageing IT platform & application toolset, measure 'value for money' for the New Zealand tax-payer, develop a platform to support future growth.

In response to these growing demands, Statistics New Zealand developed its Business model Transformation Strategy (BmTS).

1.1 Current situation

The BmTS programme was started in July 2004, three years on we have largely developed the 'core platform' and see a positive way forward. The BmTS is the main platform that provides the framework for projects related to metadata to develop to. Most metadata related projects are being undertaken within the BmTS suite of projects, but those that are not are governed by the BmTS principles.

See 6. Lessons learned (New Zealand) for more information on our experiences developing and implementing this programme.

1.2 Delivering benefits

The BmTS is aimed at delivering a number of benefits to Statistics New Zealand, and provide a solid basis for growth and development, through:

  1. Abstracting the business users and their business processes from the underlying data structures and database systems, moving our statistical staff up the analytical 'value' chain and providing an environment that would facilitate the more challenging data integration and data analysis necessary to meet the increasingly complex policy and research needs of government and the wider research community.
  2. Creating the flexibility to respond to changes in user needs and demands, to make use of new data sources or methods and to provide a flexible range of information access methods; while also providing the ability to more easily match and confront data in order to increase the quality of Statistics NZ information.
  3. Reducing the time to design, build and process information sources, providing more time for analytical and dissemination processes.
  4. Building a professional environment that creates a more satisfying working experience.
  5. Increasing the use of administrative data, reducing the number of individual collections or the need for new collections to create new statistics.
  6. Providing a standard environment and uniform systems that will allow staff to quickly get up to speed with new subject matter. This will also simplify the migration of data and systems as underlying technologies change, while reducing the maintenance cost of separate subject matter systems.
  7. Standardising the skills sets and professional development costs of our staff.
  8. Utilising a smaller number of larger projects that are more likely to have a real rate of return through the reuse of the investment in a number of business areas.
  9. Allowing Statistics NZ to provide standard information management tools and services for official statistical purposes.

1.3 Metadata Strategy

The Business Model Transformation Strategy (BmTS) is designing a metadata management strategy that ensures metadata:

  1. fits into a metadata framework that can adequately describe all of Statistics New Zealand's data, and under the Official Statistics Strategy (OSS) the data of other agencies
  2. documents all the stages of the statistical life cycle from conception to archiving and destruction
  3. is centrally accessible
  4. is automatically populated during the business process, where ever possible
  5. is used to drive the business process
  6. is easily accessible by all potential users
  7. is populated and maintained by data creators
  8. is managed centrally

Established principles of metadata management
  • metadata is centrally accessible
  • metadata structure should be strongly linked to data
  • metadata is shared between data sets
  • content structure conforms to standards
  • metadata is managed from end-to-end in the data life cycle.
  • there is a registration process (workflow) associated with each metadata element
  • capture metadata at source, automatically (where possible)
  • establish a cost/benefit mechanism to ensure that the cost to producers of metadata is justified by the benefit to users of metadata
  • metadata is considered active
  • metadata is managed at as a high a level as is possible - managing at the lowest level is prohibitive
  • metadata is readily available and useable in the context of client's information needs (internal or external)
  • tracking the use of some types of metadata (eg. classifications)

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