Statistical Classifications as the Basis for Metadata in Scientific Research
Abstract
It has been determined that international statistical classifications play the role of standard classifications in one or several statistical areas. The role of the central authority for coordinating work on all statistical classifications is played by the Group of Experts on International Statistical Classifications, created to improve cooperation in the field of improving international classifications, ensuring harmonization and convergence betwe en classifications in the family classes of the International Statistical Classes.
It has been determined that the reference structure of information objects that allows universal description of the definition, management and use of data and metadata in scientific research is the GSIM (Generic Statistical Information Model).
It has been determined that international statistical classifications play the role of standard classifications in one or several statistical areas. The role of the central authority for coordinating work on all statistical classifications is played by the Group of Experts on International Statistical Classifications, created to improve cooperation in the field of improving international classifications, ensuring harmonization and convergence between classifications in the family classes of the International Statistical Classes.
It has been determined that the reference structure of information objects that allows universal description of the definition, management and use of data and metadata in scientific research is the GSIM (Generic Statistical Information Model).
According to the terminology of the Model of Statistical Classifications, which includes GSIM, the cases of using the term «classification» in statistics are considered.
It was specified that the classification can be linear or have a hierarchical structure.
The principles of statistical classification, which must be observed during its construction, include: mutually exclusive, completeness, statistical expediency are provided.
The GSIM structural chart of the Statistical Classification Model is given, which provides a conceptual basis for the development of the classification database. The GSIM model of statistical classifications defines a concept in a two-level structure of object types and attributes. It is indicated that on the first level, it defines the main types of objects in the classification database, and at the second level, it lists the attributes associated with each type of object.
The types of statistical classifications by the level of distribution are determined, among them: reference, related and derivative classifications.
Types of variants of statistical classifications: expansion, aggregation, regrouping are considered. It is noted that a particular version may include elements from more than one of these variants.
The main directions of activity of the Group of Experts on international statistical classifications at the present stage are indicated.
It has been determined that the main sources of information on international classifications are the RAMON server and the United Nations website.
Downloads
References
Sobolyev, V. M., Chala, T. G. and Korepanov O. S. (2017). Economic statistics [“Ekonomichna statystyka”]. In Sobolyev V. M. (Ed.). Kharkiv: V. N. Karazin Kharkiv National University.
Bank for International Settlements (BIS). (2018). The official site of Bank for International Settlements. [online] Available at: https://www.bis.org/ [Accessed 25 May 2018].
DDI Alliance. (2018). The official site of DDI Alliance. [online] Available at: https://www.ddialliance.org/ [Accessed 25 May 2018].
European Central Bank (ECB). (2018). The official site of European Central Bank (ECB). [online] Available at: https://www.ecb.europa.eu/ [Accessed 25 May 2018].
European Commission. (2018). «Eurostat». [online] Available at: http://ec.europa.eu/eurostat [Accessed 25 May 2018].
Generic Statistical Information Model (GSIM), UNECE. [online] Available at: https://statswiki.unece.org/display/gsim/Generic+Statistical+Information+Model [Accessed 25 May 2018].
UNECE. (2015). Generic Statistical Information Model (GSIM): Statistical Classifications Model. New York. [online] Available at: http://unstats.un.org/unsd/class/intercop/expertgroup/2015/AC289-22.PDF [Accessed 25 May 2018]
International Monetary Fund (IMF). (2018). The official site of International Monetary Fund. [online] Available at: www.imf.org/ [Accessed 25 May 2018].
European Commission. (2018). Metadata Classifications. RAMON – Reference And Management Of Nomenclatures. [online] Available at: http://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=LST_NOM&StrGroupCode=CLASSIFIC&StrLanguageCode=EN [Accessed 25 May 2018].
Organisation for Economic Co-operation and Development (OECD). (2018). The official site of Organisation for Economic Co-operation and Development. [online] Available at: http://www.oecd.org / [Accessed 25 May 2018].
United Nations. (2014). Report of the Expert Group on International Statistical Classifications Statistical Commission Forty-seventh session 8-11 March 2016. [online] Available at: https://unstats.un.org/unsd/statcom/47th-session/documents/2016-11-EG-on-International-statistical-classifications-E.pdf [Accessed 25 May 2018].
Eurostat. (2018). SDMX. [online] Available at: https://webgate.ec.europa.eu/fpfis/mwikis/sdmx/index.php/SDMX [Accessed 25 May 2018].
United Nations. (2018). Statistical Classifications. [online] Available at: https://unstats.un.org/unsd/classifications/ [Accessed 25 May 2018].
United Nations. (1999). Statistical Commission Report on the thirtieth session (1–5 March 1999). [online] Available at: http://www.un.org/documents/ecosoc/docs/1999/e1999-24.htm [Accessed 25 May 2018].
United Nations. (2018). United Nations Glossary of Classification Terms. Working document. [online] Available at: https://unstats.un.org/unsd/class/intercop/expertgroup/1999/AC75-8a.PDF [Accessed 25 May 2018].
United Nations Statistics Division (UNSD). (2018). The official site of United Nations Statistics Division. [online] Available at: https://unstats.un.org/home/ [Accessed 25 May 2018].
