The National GSBPM Glossary: Methodology and Practice

Keywords: glossary, GSBPM, statistical business process, official statistics, statistical term, term definition.

Abstract

This study aims to contribute to the national statistical glossary compilation, namely a glossary supporting the Generic Statistical Business Process Model (GSBPM). The GSBPM is a standard framework that allows statistical authorities to use corporate and harmonized terminology for the statistical business process. In Ukraine, the implementation of the GSBPM in statistical practice puts forward the need for its terminological support. The glossary is a means of understanding among statisticians and contributes to professional vocabulary formation.

Statistical terminology today creates an independent terminological system. The system nature of statistical language is related to the professional limits and the interdependence of phenomena within these limits. As a subsystem of the general statistical system, the GSBPM has its vocabulary.

We argue a complex, non-linear, and dynamic interrelation between statistical business processes in the GSBPM. The business processes form some synergy and involve professional vocabulary for different business phases, implying a non-mechanical approach to glossary compilation.

According to studied international practice, there is no single approach to statistical glossaries construction and presentation. The choice of basiс international standards is crucial to ensure the GSBPM methodology and quality.

We formulated several experience-based requirements and principles for the GSBPM glossary. Identified problematic issues may be useful for further work on statistical terminology. The progress in official statistics, both international and national, significantly affects this work's qualitative aspects. An essential factor in bringing national statistical language closer to international standards is undoubtedly the dialogue between the academic community and statisticians-practitioners.

The development of glossaries for the General Activity Model for Statistical Organizations (GAMSO) and the Generic Statistical Information Model (GSIM) is outlined as a prospective area of further studies.

Downloads

Download data is not yet available.

References

1. Opys natsionalnoi modeli statystychnoho vyrobnytstva v orhanakh derzhavnoi statystyky [Description of the Generic Statistical Business Process Model in State Statistics Bodies]. (2018). www.ukrstat.gov.ua. Retrieved from http://www.ukrstat.gov.ua/norm_doc/dok/nmsv.htm [in Ukrainian].
2. Pryntsypy diialnosti orhaniv derzhavnoi statystyky Ukrainy: zatverdzheni nakazom Derzhstatu vid 17.08.2018 r. No 170 [The Principles of Operation of the Official Statistics Bodies in Ukraine. Approved by Directive of the State Statistics Service of Ukraine of August 17, 2018, No 170]. (2018). www.ukrstat.gov.ua. Retrieved from http://www.ukrstat.gov.ua/prc_dk/prc_ddos.htm [in Ukrainian].
3. Uhoda pro asotsiatsiiu mizh Ukrainoiu, z odniiei storony, ta Yevropeiskym Soiuzom, Yevropeiskym spivtovarystvom z atomnoi enerhii I yikhnimy derzhavamy-chlenamy, z inshoi storony: ratyfikovano zakonom Ukrainy vid 16.09.2014 r. № 1678-VII, stanom na 30.11.2015 r. [Association Agreement between the European Union and its Member States, of the one part, and Ukraine, of the other part. Law of Ukraine of September 16, 2014 № 1678-VII as of November 30, 2015]. zakon.rada.gov.ua. Retrieved from https://zakon.rada.gov.ua/laws/show/984_011#Text [in Ukrainian].
4. Bacelar, S. (2009). Metadata Common Vocabulary: a journey from a glossary to an ontology of statistical metadata, and back. Joint UNECE/Eurostat/OECD Work Session on Statistical Metadata (METIS). 11–13 March, 2009. Lisbon. Retrieved from https://www.academia.edu/5896473/Metadata_Common_Vocabulary_a_journey_from_a_glossary_to_an_ontology_of_statistical_metadata_and_back
5. Annual report of the High-Level Group for the Modernisation of Official Statistics. ECE/CES/2019/10. Conference of European Statisticians. Sixty-seventh plenary session. 26–28 June, 2019. Paris. Retrieved from https://unece.org/fileadmin/DAM/stats/documents/ece/ces/2019/ECE_CES_2019_10_E.pdf
6. GAMSO. Generic Activity Model for Statistical Organisations. (2015). Version 1.0:1. United Nations Economic Commission for Europe (UNECE). Retrieved from https://ec.europa.eu/eurostat/cros/system/files/GAMSO%20%281%29.pdf
7. Generic Statistical Business Process Model. GSBPM (2019). Version 5.1. United Nations Economic Commission for Europe (UNECE). statswiki.unece.org. Retrieved from https://statswiki.unece.org/display/GSBPM/GSBPM+v5.1
8. Generic Statistical Information Model (GSIM). User Guide. (2012). Version 1.0. United Nations Economic Commission for Europe (UNECE). statswiki.unece.org. Retrieved from https://statswiki.unece.org/pages/viewpage.action?pageId=75563998
9. Getting the Facts Right. A guide to presenting metadata with examples on Millennium Development Goal indicators. (2013). New York, Geneva: UNECE. Retrieved from https://unece.org/fileadmin/DAM/stats/publications/2013/GettingFactsRightEnglish.pdf
10. Handbook on Methodology of Modern Business Statistics (2017). Retrieved from https://ec.europa.eu/eurostat/cros/content/handbook-methodology-modern-business-statistics_en
11. ISO/IEC 11179-4:2004. Information technology – Metadata registries (MDR) – Part 4: Formulation of data definitions. (2004). www.iso.org. Retrieved from https://www.iso.org/standard/35346.html
12. SDMX – Metadata Common Vocabulary (MCV). (2009). statswiki.unece.org. Retrieved from https://statswiki.unece.org/display/hlgbas/SDMX+-+Metadata+Common+Vocabulary
13. Metadata flows in the GSBPM. (2013). Working Paper. Work Session on Statistical Metadata (Geneva, Switzerland, 6–8 May 2013). Retrieved from https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.40/2013/WP22.pdf
14. SDMX Content-Oriented Guidelines. (2009). Annex 1: Cross-Domain Concepts. sdmx.org. Retrieved from https://sdmx.org/wp-content/uploads/2009/01/01_sdmx_cog_annex_1_cdc_2009.pdf
15. SDMX Content-Oriented Guidelines. (2009). Annex 4: Metadata Common Vocabulary. sdmx.org. Retrieved from https://sdmx.org/wp-content/uploads/2009/01/04_sdmx_cog_annex_4_mcv_2009.pdf
16. Statistical Metadata in a Corporate Context: A guide for managers. (2009). unece.org. Retrieved from https://unece.org/fileadmin/DAM/stats/publications/CMF_PartA.pdf
17. Thelen M. (2015) The Interaction between Terminology and Translation Or Where Terminology and Translation Meet. trans-kom, 8 (2), 347–381. Retrieved from http://www.trans-kom.eu/bd08nr02/trans-kom_08_02_03_Thelen_Terminology.20151211.pdf
18. Vale, S. (2009). Towards a Generic Statistical Business Process Model. Conference Paper: ISI World Statistics Congress. Retrieved from https://www.researchgate.net/publication/331021438_Towards_a_Generic_Statistical_Business_Process_Model
19. glossary. Cambridge Dictionary. dictionary.cambridge.org. Retrieved from https://dictionary.cambridge.org/fr/dictionnaire/anglais/glossary
20. glossaire. Larousse. www.larousse.fr. Retrieved from https://www.larousse.fr/dictionnaires/francais/glossaire/37201
21. Glossaire. Wikipedia. fr.wikipedia.org. Retrieved from https://fr.wikipedia.org/wiki/Glossaire
22. Merriam-Webster Dictionary. www.merriam-webster.com. Retrieved from https://www.merriam-webster.com/dictionary
23. Calque. Wikipedia. en.wikipedia.org. Retrieved from https://en.wikipedia.org/wiki/Calque
24. Transliteration. Wikipedia. en.wikipedia.org. Retrieved from https://en.wikipedia.org/wiki/Transliteration

Abstract views: 7
PDF Downloads: 5
Published
2020-12-08
How to Cite
Vasyechko, O. O. (2020). The National GSBPM Glossary: Methodology and Practice. Statistics of Ukraine, 90(4), 4-11. https://doi.org/10.31767/su.4(91)2020.04.01