Czech Statistical Office: use of GSBPM

Statistical survey life cycle

SMS is an integral part of SIS.
The main goal of the SMS is to support the statistical business process (collection, production and dissemination of statistical information).
The following scheme demonstrates the structure of the process: 

Main functions of individual phases of SBP:

Users´ requirements

Assessment and evaluation of users' requirements in link with already existing statistical tasks. Consideration of capacity requirements, etc. This phase includes an evaluation by subject-matter departments and methodology department. It also includes decision-making by the top management of the CZSO. It results in approval or disapproval of users´ requirements.
  
\ Definition of statistical task (DESIGN)
In case of a new ST, a specification of the content, organisation and technology of the ST is made. This includes the proposal of task concept, definition of statistical variables, definition of statistical samples, outputs, definition of statistical questionnaires, other input data sets (from administrative data sources, from other statistical tasks), calculation description over the data (imputation methods, aggregations, calculation of derived statistical variables), time-table for ST preparation and implementation, etc. 
In case of an existing ST, its update should be prepared.
This phase is in the responsibility of subject-matter department and methodology department.
Preparation of data processing (BUILD)
Namely the following activities should be made: 

• selection of samples,
• preparation and distribution of questionnaires (incl. electronic questionnaires),
• training of interviewers and staff responsible for individual phases of production,
• getting data sets from administrative and other external data sources.

This phase is in the responsibility of data processing department and subject-matter department.

Data collection (COLLECT)
Namely the following activities are included:

• collection of questionnaires and input data capture,
• data validation,
• use of data from other data sources (incl. data validation),
• imputation and creation of input data sets for further processing.

This phase is in the responsibility of data processing department and subject- matter departments.

Data processing (PROCESS)
Namely the following activities are included:

• building of input database,
• imputation of missing records,
• grossing up to statistical population,
• processing of aggregates,
• adjustment for seasonal effects,
• database update.

This phase is in the responsibility of data processing department in cooperation with subject-matter departments.

Data analysis and output production (ANALYSE)
Namely the following activities are included:

• application of mathematical and statistical methods,
• processing of required outputs,
• data quality assessment,
• approval of data for publication,
• public database update.

This phase is in the responsibility of subject-matter departments.

Dissemination (DISSEMINATE)
This phase focuses on the following forms of data dissemination:
- web pages,
- public database,
- printed publications,
- electronic outputs,
- ad hoc outputs.

Other activities:
- users´satisfaction surveys,
- analyses of the use of disseminated statistical information,
- statistical confidentiality.

This phase is in the responsibility of dissemination department and selected subject-matter departments. 
The basic scheme of the statistical business process (survey life cycle) has been updated according to the draft Statistical Business Process Model prepared by the UNECE Statistical Division (Oct. 2008)

The aim of the SMS is to support all phases of SBP as set out in point 2.3. The SMS is an end-to-end system.
The subsystems store, update and use metadata items in individual phases of SBP, as shown in the following table.

Due to progress of work on the SMS (see point 4.1) we take an example of detailed information on metadata kept in subsystems CLASS, VAR and TASKS that are being developed.

Subsystem CLASS is based on the Neuchâtel model of statistical classifications. It allows creation, storage, update and use of statistical classifications, which are necessary for data processing. There is basic metainformation kept on each classification incl. its history, e.g. the title and coordinator of classification, validity and contents of classification/code-list in language versions (CZ, EN) etc.These characteristics on code-lists are stored in the SMS database.

• identification code of the code-list,
• code-list item code,
• full and short name of the code-list item,
• names for presentation,
• validity of the code-list item (from-to),
• definition of the code-list item,
• attributes of the code-list item (voluntary),
• links to the other code-list and its items.

Subsystem VAR is based on a unique model for description of statistical variables at micro data and macro data level. The model was developed in the CZSO using experience of Work Session on Metadata UNECE. Metadata are aimed at description of the contents of statistical data. The most important metainformation is the statistical concept, statistical function, title, definition, and unit of measure and subject-matter breakdown. Also metainformation on the coordinator, subject-matter area, validity, etc., is kept on statistical variable.

. Following characteristics of a variable are kept in SMS database:
•    identifier,
•    structural description,
•    full and short name,
•    definition,
•    validity (from-to),
•    set of compulsory and voluntary attributes,
•    names for presentation,
•    remarks

Subsystem TASKS contains metainformation on functional and technological specifications of STs. Mainly the following metainformation is kept:
•    basic characteristics of a task,
•     statistical questionnaire content a structure definition,
•     input data sets,
•    annex to the decree on annual programme of statistical surveys (list of surveys with response duty),
•    data item validation rules, auto-correction rules, transformation rules, derivation rules
•    definition of statistical samples,
•    specifications of imputation methods,
•    quality requirements,
•    aggregations rules,
•    estimates procedures,
•    specification of users,
•    time-tables for preparation of a task, for user tests and for statistical production,
•    applied code-lists,
•    legislation base for a task,
•    data flow and organization of the collection and processing,
•    documentation (user and technological). 

The division of life cycle of the statistical task (part 2.3) will also be used for cost controlling purposes. Metainformation on the history of a statistical task, especially time-table of processing, will be used when considering labour intensity of individual phases/activities of the process.

Information on statistical data quality obtained in the history of processing will be used for quality of work assessment of the CZSO's departments responsible for design and implementation of statistical tasks. This information can also be used to assess the quality of work of the entire Office. The method applied is European Foundation for Quality Management (EFQM).

Subsystem TASKS is designed to allow specification of non-statistical tasks such as controlling, other administrative subsystem or development tasks.