1. 1 Case Study Integrated Metadata Driven Statistical Data Management System (IMD SDMS) CSB of Latvia Julija.Drozdova@csb.gov.lv METIS 2010

2. 2 Outline The main steps for IMD SDMS creation IMD SDMS fundamental elements Costs & benefits IMD SDMS implementation strategy GSBPM versus SBPM of CSB Current situation and further developments The main lessons learned Proposal for GSBPM

3. 3 The main steps for IMD SDMS creation (1) Data and metadata collection (1999) Thoughtful analysis of data and metadata flows (1999) To set the requirements to the system (1997- 1999)

4. 4 The main steps for IMD SDMS creation (2) the main requirements to IMD SDMS were: covers full cycle of statistical data processing; uses process oriented approach; IMD SDMS must be: - standardized; - integrated; - meta data-driven; - allows automated generation of user application forms (incl. web); - centralized; - has a modular structure; - transparent;

5. 5 IMD SDMS fundamental elements (1) Core Meta data base module handles all processes of IMD SDMS Structure of Micro data [Bo Sundgren model] Objects characteristics: Co = O(t).V(t) where: O - is an object type; V - is a variable; t - is a time parameter. Every results of observations is a value of variable (data element) – Co Two types of tables Structure of Macro data

6. 6 IMD SDMS fundamental elements (2) Structure of Micro data (an example)

7. 7 IMD SDMS fundamental elements (3) Two types of tables: - fixed table (data matrix); - open table (data matrix with various number of rows or columns); Questionnaire consists of chapters and chapters consist of tables.

8. 8 IMD SDMS fundamental elements (4) Structure of Macro data The estimations are made on the basis of a set of Micro data. Statistical characteristics: Cs = O(t).V(t).f where: O and V - is an object characteristics; t - is a time parameter, f – is an aggregation function (sum, count, average, etc) summarizing the true values of V(t) for the objects in O(t).

9. 9 Costs & benefits Standardization of statistical data production processes The basis for the CSB regional restructuring (2003-2004): 5 Data Collection and processing centres replaced previously existing 26 Statistical Regional offices and city Riga office; Decreasing of statisticians from 180 to 115

10. 10 IMD SDMS implementation strategy (1) Step-wise approach 1997 – 1999 CSB and PricewaterhouseCoopers experts were prepared General Technical Requirements for the project “Modernisation of CSB – Data Management System”

11. 11 IMD SDMS implementation strategy (2) The main requirement: Meta data should be used as the key element in statistical data processing Additional requirements: - Increase efficiency of the production of statistical information; - Avoid hard code programming via standardisation of procedures and use of Meta data within the statistical data processing; - Increase the quality of the information produced; - Improve processes of statistical data analysis; - Modernise and increase the quality of data dissemination;

12. 12 GSBPM versus SBPM of CSB GSBPM versus SBPM of CSB (draft version) ~51 %

13. 13 ADS Current situation (1)

14. 14 Current situation (2)

15. 15 Further developments Since 2009 a project has been launched for the IMD SDMS to cover Social statistics domain. Starting from: - Population Census; - Agricultural Census; - Labour Force Survey; - EU-SILC …

16. 16 The main lessons learned (1) Design of the new information system should be based on the results of deep analysis of statistical surveys: - statistical questionnaires and variables; - statistical processes and data flows; Statistical data processes and “Variables and questionnaires system” must be harmonized and standardized before creation of the new system;

17. 17 The main lessons learned (2) The system should provide a full cycle of statistical data processing; The system should be: - standardized; - integrated; - meta data-driven; - allows automated generation of user application forms (incl. web); - centralized; - has a modular structure; - transparent;

18. 18 The main lessons learned (3) Motivation of the statisticians to move (from stove-pipe to process oriented) to the new data processing environment is essential; To establish Metadata group; Data electronic archiving reduces human resources, expenses of CSB for deposition in the State Archives, time of archiving and physical amount of archiving information (In 2000, Population Census - 21 m 3 = 4 DVD)

19. 19 Proposal for GSBPM (1) Extension of phase 4 – Collect, between sub- processes 4.1 and 4.2 Extension, between sub-processes 4.3 and 4.4 Why ?: - statistician’s work with respondents and with the list of respondents is a very difficult, heavy process and time consuming process (…; sending of letters to respondents; conduction of the respondents lists; creation of the sample Matrix; clarifications; response control; reminding process; …); - sometimes statistician’s work is pressed for time (…Business tendencies survey…)

20. 20 Proposal for GSBPM (2) Survey’s integration Sample Matrix List of indicators From analytic’s view From statistician’s view: -amount of work -respondents burden -statisticians burden -response control - etc. From mathematician’s view …