United Nations Economic Commission for Europe Statistical Division

United Nations Economic Commission for Europe Statistical Division Applying generic view of statistical process to population census Steven Vale, Marlen Jigitekov Statistical Division, UNECE Geneva, 5 -6 July 2010

Managing Human Resources in Information Technologies v v Cooperating with other statistical organizations, creating of regional groups Maximizing involvement of statisticians to development of statistical products and minimizing involvement of software resources • Farmers and millers, but where are engineers? ! v Improving constantly work efficiency v Using open source software v Keeping balance between own IT staff and outsourcing 07. 06. 2021 - UNECE Statistical Division Slide 2

Generic Statistical Business Process Model 07. 06. 2021 - UNECE Statistical Division Slide 3

Standardized process descriptions Harmonised processes Rationalization of software Use of open source and shared components SDMX between components Convergence of business architectures 07. 06. 2021 - UNECE Statistical Division Slide 4

MSIS Project v v v MSIS – Management of Statistical Information Systems Objective is to promote joint statistical software development among national and international organizations Project presents Register of Statistical Software used in various statistical organizations Join the project! Web link to the project • http: //www 1. unece. org/stat/platform/display/msis/Home+Page 07. 06. 2021 - UNECE Statistical Division Slide 5

Multidimensional cubes is a standard for data dissemination! Age Country Year 07. 06. 2021 - UNECE Statistical Division Slide 6

Cubes with more dimensions can exist, but difficult to draw! 07. 06. 2021 - UNECE Statistical Division Slide 7

End-to-end data processing system based on the concept of multidimensional cubes 1. Create supercube 2. Fill in source data 3. Calculate and verify data 4. Create PC-Axis cube 07. 06. 2021 - UNECE Statistical Division Slide 8

Validate results v TSSL programming language is developed in UNECE to validate data • Example: value for coefficient of fertility should not exceed 6. • Another example: population percentages in the given age group should be within [0%. . 100%] range 07. 06. 2021 - UNECE Statistical Division Slide 9

7. Data dissemination v Most of applications are based on multidimensional cubes concept v Examples : PC-Axis, OECD. Stat v UNECE uses PC-Axis 07. 06. 2021 - UNECE Statistical Division Slide 10

What is PC-Axis? v v v International project, originally designed for population census in Sweden Objective is to develop statistical data dissemination system Project is managed by consortium 07. 06. 2021 - UNECE Statistical Division Slide 11

PC-Axis Consortium v Unites 39 national statistical agencies and organizations v Governing body is Statistical Bureau of Sweden v Objective: Develop statistical data dissemination system • Cooperate to avoid work duplication • 07. 06. 2021 - UNECE Statistical Division Slide 12

Data output v Projecting cubes to tabular format v Output of metadata v Simple calculations 07. 06. 2021 - UNECE Statistical Division Slide 13

Projecting cubes to tabular format 07. 06. 2021 - UNECE Statistical Division Slide 14

Data visualization, graphs 07. 06. 2021 - UNECE Statistical Division Slide 15

Data visualization, maps 07. 06. 2021 - UNECE Statistical Division Slide 16

Advantages of PC-Axis compared to other tools Cubes are ready for browsing, this means Easy to understand • Quick in data output • Complemented by metadata • Oriented towards public • 07. 06. 2021 - UNECE Statistical Division Slide 17

Data dissemination stages v 7. 1 Update output systems v 7. 2 Produce dissemination products v 7. 3 Manage release of dissemination products v 7. 4 Promote dissemination products v 7. 5 Manage user support 07. 06. 2021 - UNECE Statistical Division Slide 18

Examples v Annual and quarterly reports based on web statistics and Google Analytics v Annual user surveys v Follow-up of user requests v Promoting new products v Improving web site rating at leading search engines by publications, articles, reprots etc. 07. 06. 2021 - UNECE Statistical Division Slide 19

Influence of products promotion on popularity of web-site among users 07. 06. 2021 - UNECE Statistical Division Slide 20

Geography of users in Google Analytics 07. 06. 2021 - UNECE Statistical Division Slide 21

SDMX Standard v v v SDMX – standard of data and metadata exchange. Sponsors are international organizations Main challenge is metadata harmonization 07. 06. 2021 - UNECE Statistical Division Slide 22

Conclusion v v UNECE is ready to provide the technical aid, both in English and Russian, in implementing PC-Axis Questions? Steven. Vale@unece. org • Marlen. Jigitekov@unece. org • 07. 06. 2021 - UNECE Statistical Division Slide 23