Use of Statistical Service to Introduce Service Oriented Architecture of Statistical Production

  • Т. I. Lumpova
  • О. E. Ostapchuk National Academy of Statistics, Accounting and Audit
Keywords: Common Statistical Production Architecture, Statistical Production Process, Generic Statistical Business Process Model, Generic Statistical In formation Model, Service Oriented Architecture

Abstract

Issues of implementation of Common Statistical Production Architecture (CSPA) for modernization of the production process in the Ukrainian official statistics bodies (OSB) in keeping with the European standards are analyzed. Emphasis is made on introduction of the process scheme in the production setting, with separating statistical services as a tool to enhance the economic effectiveness through collaborative development, exchange and re-use of methods and tools. The position of statistical service in the production process and the importance of its description when introducing Service Oriented Architecture (SOA) in the Ukrainian OSB, which is the basis for CSPA from the IT perspective, are highlighted.

The conditions required to build CSPA for applications of Generic Statistical Business Process Model (GSBPM) and Generic Statistical Information Model (GSIM) have already been set in the Ukrainian OSB. They include the tool for planning and preparation of the production process, which is technological plan (program) of official statistical observations (TP OSO), built on the GSBPM basis with specification of process components (PC) in the sequence “process - sub-process - procedure - operation”; the release version of the Classifier of Processes and Processes Elements of Statistical Production Processes (Classifier) and Reference Book of TP OSO Performed Procedures and Operations Results (Reference Book), developed for TP OSO for 2014-2015 with consideration to future modernization of the information system. Results of the analysis show that the Ukrainian OSBs have the capacities required to develop the conceptual description of statistical services using the available database; recommendations on its composition are given, capabilities for identification of the aggregated statistical service and the information flow in it are illustrated.

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References

1. Postanova Kabinetu Ministriv Ukrainy vid 20 bereznia 2013 r. N 145-r. “Pro zatverdzhennia Stratehii rozvytku derzhavnoi statystyky na period do 2017 roku” [Decree of Cabinet of Ministers of Ukraine of March 20,2013 № 145-p “On approval of Strategy of state statistics development until 2017”]. www.zakon1 .rada.gov.ua. Retrieved from http://zakonl.rada.gov.ua/laws/show/ 145-2013-p [in Ukrainian ].

2. Common Statistical Production Architecture. Conference of European Statisticians. Sixty-second plenary session (Paris, 9-11 April 2014). www.unece.org. Retrieved from http://unstats.un.org/unsd/ nationalaccount/workshops/2016/ankara/cspa-eng.pdf [in English ].

3. Generic Statistical Business Process Model. Conference of European Statisticians. Sixty-second plenary session, (Paris, 9-11 April 2014). www.unece.org. Retrieved from http://www.unece.org/fileadmin/ DAM/stats/documents/ece/ces/2014/ECE_CES_2014_l-Generic_Statistical_Business_Process_Model. pdf [in English ].
4. Generic Statistical Information Model (GSIM): Communication paper for a general statistical audience. Conference of European Statisticians. Sixty-second plena
ry session (Paris, 9-11 April 2014). www.unece.org. Retrieved from http://wwwunece.org/fileadmin/DAM/stats/documents/ece/ces/2014/ ECE_CES_2014_2-Generic_Statistical_Information_Model.pdf [in English ].

5. Engdahl, J. (2010). An event-driven architecture for data collection. Meeting on the Management of Statistical Information Systems (MSIS 2010), (Daejeon, Republic of Korea, 26-29 April 2010). www.unece.org. Retrieved from http://www.unece.Org/stats/documents/ece/ces/ge.50/2010/wp.9.e.pdf [in English ].

6. Engdahl, J., Ireback, EL, & Holmberg, A. (2011). Tentative anatomy of a new generation of IT- architecture to support GSBPM-processes. Meeting on the Management of Statistical Information Systems (MSIS 2011), (Luxembourg, 23-25 May 2011). www.unece.org. Retrieved from http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.50/201 l/wp.4.e.pdf [in English ].

7. Engdahl, J. (2012). Guidance for Statistical Services. Meeting on the Management of Statistical Information Systems (MSIS 2012), (Washington, 21-23 May 2012). www.unece.org. Retrieved from http:// www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.50/2012/05_Sweden.pdf [in English ].

8. Seljak, R., & Smukavec, A. (2015). Modernisation of statistical processing at SURS. Workshop on the Modernisation of Statistical Production (Geneva, Switzerland, 15-17 April 2015). www.unece.org. Retrieved from http://wwwunece.org/fileadmin/DAM/stats/documents/ece/ces/ge.50/2015/Topic2_Slovenia_ paper.pdf [in English ].

9. Sowa, J. E, & Zachman, J. (1992). Extending and Formalizing the Framework for Information Systems Architecture. IBM SystemsJournal, Vol.31,3, 590-616 [in English ].

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Published
2016-06-20
How to Cite
LumpovaТ. I., & OstapchukО. E. (2016). Use of Statistical Service to Introduce Service Oriented Architecture of Statistical Production. Statistics of Ukraine, (2(73), 6-13. Retrieved from https://su-journal.com.ua/index.php/journal/article/view/74