Classification is a hierarchical categorisation of specific phenomena or processes (economic, social or demographic). Classifications are characteristic by the subdivision of phenomena and processes from general to more detailed ones. There is a relation of superiority and subordination among classification levels. In classifications, phenomena and processes are usually subdivided into classes and sub-classes, groups and sub-groups, divisions and sub-divisions. According to its individual levels, classification can be split into several code lists.
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Code list is an ordered enumeration of codes (numeric, alphabetic) and meanings attached to them. Usually, there is no hierarchy among individual items of a code list.

Code lists are integral part of the statistical metainformation system. Code lists are regularly updated.
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Statistical indicator defines the content of an observed phenomenon. The structure of an indicator contains texts and attributes. Every indicator has a unique identification code attached to it. There are several texts belonging to indicators, such as “full name”, “definition” and “synonyms” which are used in questionnaires and output tables. Attributes specify whether an indicator refers to a period or a date, whether the data are numeric (a number) or character (letters), whether it is quantitative (e.g. “the number of...”) or qualitative (e.g. “married”), whether it is the result of a survey or an estimate, whether it is a countable or not, and whether it belongs to a group of surveys (e.g. property or insurance).

There are three possible ways of how to search for an indicator: by alphabet, by string (full-text search), or by topic. Below the structure of an indicator, there is a list of closely related indicators. An example: I can find “Health expenditure of public health insurance system” under letter “H” or using the full-text search typing “public health”, and/or under the “health” topic of “Demographic and social statistics”.
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