A. Basic concepts
8.2. Statistical data processing and statistical information systems. As in other domains of official statistics, the compilation of international merchandise trade statistics involves collecting, processing, storing, retrieving, analysing and disseminating statistical data. In practice, these processes are structured according to particular institutional arrangements in countries and are mostly carried out with the help of information systems infrastructure (including database management systems). The resulting organizational and information systems architecture provides the framework within which different statistical compilation and dissemination processes and subsystems play their respective roles and interact with one another. While the architecture of a statistical data processing system will respond to the specific needs and constraints faced by each country, there are various general frameworks available which provide guidance and best practices, including the Generic Statistical Business Process Model (GSBPM) proposed by the joint Economic Commission for Europe (ECE)/Eurostat / Organization for Economic Cooperation and Development (OECD) work sessions on statistical metadata (METIS).[1]
8.3. Database management systems. The basic functions of a statistical database management system are to create, retrieve, update and delete (CRUD) specified data during the various stages of the statistical data processing cycle. These operations are performed by the database management system on data stored in a database according to a particular data model, such as the relational data model, which is the de facto standard for a wide variety of database management systems and database-related applications.[2] The Structured Query Language (SQL) is a widely accepted interface between relational database management systems and database-related applications.
[1] The Generic Statistical Business Process Model (GSBPM) provides standard terminology to describe and define the set of business processes needed to produce official statistics. The model can also be used in harmonizing statistical computing infrastructures, facilitating the sharing of software components, providing a framework for process quality assessment and improvement, etc. Further details are available from http://www1.unece.org/stat/platform/display/metis/METIS-wiki. See also United Nations Statistical Commission and Economic Commission for Europe, “Information systems architecture for national and international statistical offices: guidelines and recommendations”, Conference of European Statisticians Statistical Standards and Studies, No. 51 (Geneva, 1999). Available from http://www.unece.org/fileadmin/DAM/stats/ documents/information_ systems_architecture/1.e.pdf.
[2] Other models are the hierarchical model and the network model.