Statistics Sweden: use of GSIM

Statistics Sweden’s adaptation of GSIM is intended to be used in all future development projects. The main use is going to be to describe the inputs to and outputs from activities in the production process, but also to work as a reference model for information and metadata requirements for creating common production tools for the statistical business process. It will also work as an agent for contents harmonization. Modernisation of statistical production is not a technical issue ‒ it covers business, methodology and IT. The main method to improve efficiency is by reusing already collected in­formation. Content harmonization in this aspect requires metadata to de­scribe the data. This also leads to a reduction of the respondent burden.

GSIM will be incorporated in Statistics Sweden’s information architecture and the information models will align with GSIM. The Inform­ation models are made available in Statistics Sweden's common model libraries. This model library can be seen as Statistics Sweden's corporate memory. Models are successively built and constantly developed and re­developed by requirements from projects and reused in other projects.

All development projects should require involvement from enterprise architects during start-up. A model library should be made for information models in order to promote reuse and further development. The models may also be further de­veloped during the projects and this information should then be documented in the model library after it has been quality assured by the enterprise architects. This will retain a holistic perspective, ensuring that basic modelling principles are followed. It also minimizes sub-optimization and unnecessary variations in support of the process-oriented approach.

The GSIM-based metadata model is going to be used for creating a coherent layer based documentation system for reference metadata that allows for different kinds of outputs based on user needs. This makes it possible to connect various forms of reference metadata (such as national and inter­national/Eurostat requirements). Process metrics can be used in the re­ference metadata. The goal is to create a documentation system that collects metadata as it is created making it possible to make successive document­ation during the production process - documenting the activities as they are conducted. This means that the core of the documentation is created during the design process.

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Statistics Sweden uses GSIM together with the Swedish version of GSBPM (see the GSPBM case study).

For business processes that are not part of the statistical business process Statistics Sweden has developed a process chart, in line with GAMSO.

Statistics Sweden´s process chart:

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Groups of objects

Statistics Sweden´s information architecture has several groups of objects that are used in other processes as well as those shared between several processes like Personnel and Organisation. The circled object groups are specifically used for the statistical production. The object group Structure can be used by other processes.

Highlighted object groups

Context variable

A Context variable is a Represented variable linked to a specific data source and a Population. This new object was created in order to make the link between concepts and structure.

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GSIM as such is not possible to be used directly of the shelf, it is a conceptual model and it requires a lot of work to adopt it to the NSI-level. It is difficult to connect the different parts of GSIM. As soon as you start the level of details required are very large. This does not mean that it is not useful, quite the opposite, it is extremely helpful in a lot of cases since it provides a solution to existing problems and can therefore be used as a reference. GSIM has proven very valuable as a foundation in discussions regarding a central metadata repository and has provided a common vocabulary in those discussions. It has been a source of inspiration in the efforts of constructing a production system for short term statistics (KLON, mentioned above). During this work a number of lessons has been learned.

Experiences in short:

• The importance of reusing metadata
  For example, allowing the user to use the names and codes of variables and value domains from "Concepts" in "Business" and "Exchange" to configure the design and also what will be delivered to internal and external users.
• Harmonized metadata
  It is not a prerequisite, but significantly facilitates the work. By giving the same code and name to variables and values that by definition conceptually are the same thing.
• Periodicity
  Often there are data with different periodicity available. In order to have a general production system there needs to be a property that describes the periodicity on transformable input and output. The periodicity may be different between input and output. E.g. monthly data can be transformed into both quarterly and yearly data so that the output out of a service can be all three types of periodicity.
• Classify variables
  In order to aid users of the production system, but also in the building of common services that can be used by more than one statistical program, is it useful that variables are classified as different types. A variable can be of a different type depending on the context of its use.
• Traceability - and reproducibility
  Not only for versioning of data, but also for metadata. This is closely tied to versioning of services.
• Codes (status and ”other” codes)
  By using process step as an attribute it is possible to monitor where in the business process a values is used, given that the process flow is defined. This means that a lot of often occurring status codes are not required. What is left are status codes for a specific values, these are considered as generic status codes.
• Exchanging data
  To a large extent data is exchanged between different statistical programs within a NSI. This is often done by hard coded database-to-database solutions. Or even worse, e-mail. One way to avoid that is to store data in the same structure. Harmonized metadata is necessary for this.