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Case Studies Slovenia. Julija Kutin [email protected] i METIS Workshop on the Statistical Business Process and Case Studies 11-13 March 2009. Outline. Introduction. Statistical metadata systems and the statistical business process. System and design issues. - PowerPoint PPT Presentation
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Case Studies Case Studies SloveniaSlovenia
Julija Kutin Julija Kutin [email protected]@gov.sii
METIS Workshop on the Statistical Business METIS Workshop on the Statistical Business Process and Case StudiesProcess and Case Studies
11-13 March 200911-13 March 2009
OutlineOutline
1.1. Introduction.Introduction.
2.2. Statistical metadata systems and the Statistical metadata systems and the statistical business process.statistical business process.
3.3. System and design issues.System and design issues.
4.4. Organizational and workplace culture Organizational and workplace culture issues.issues.
5.5. Lessons learned.Lessons learned.
IntroductionIntroduction
Case Study was prepared by Joza Klep Case Study was prepared by Joza Klep and Julija Kutin.and Julija Kutin.
Situation at SORS end February 2009: Situation at SORS end February 2009: there are 386 employees. 198 of them there are 386 employees. 198 of them have graduate or post-graduate degree. have graduate or post-graduate degree.
SORS as a production process oriented SORS as a production process oriented institution headed by director general and institution headed by director general and two deputy directors.two deputy directors.
SORS organisation schemeSORS organisation scheme
The main goalThe main goal
The main goal of SORS in the field of The main goal of SORS in the field of metadata is to develop an efficient and metadata is to develop an efficient and effective, standardized and integrated effective, standardized and integrated system for collecting and editing metadata system for collecting and editing metadata as an important part of the statistical as an important part of the statistical information system. information system.
Metadata in SORSMetadata in SORS
A centralised, corporate metadata repository (metadata about A centralised, corporate metadata repository (metadata about surveys, publications, statistical terminology, classifications and surveys, publications, statistical terminology, classifications and nomenclatures, advance release calendar);nomenclatures, advance release calendar);
For each statistical survey methodological explanations have For each statistical survey methodological explanations have been developed;been developed;
This year the metadata repository has been developed This year the metadata repository has been developed (questionnaires, variables and connections to databases);(questionnaires, variables and connections to databases);
The next step will be to connect those two parts with the The next step will be to connect those two parts with the repository for reference metadata;repository for reference metadata;
In the centralised metadata repository metadata will be In the centralised metadata repository metadata will be reusable.;reusable.;
Metadata will be disseminated through our website.Metadata will be disseminated through our website.
Metadata on the webMetadata on the web
Program of statistical surveys.Program of statistical surveys. Action plan.Action plan. Methodological Explanations. Methodological Explanations. SORS' release calendar.SORS' release calendar. Classifications.Classifications. Questionnaires. Questionnaires.
SDMX standardsSDMX standards
SODI project ("push" method).SODI project ("push" method). Technical and a content problem.Technical and a content problem. Group for SDMX:Group for SDMX:
to monitor the development of the SDMX;to monitor the development of the SDMX; to collaborate in different Eurostat activities in to collaborate in different Eurostat activities in
the field of development and implementation the field of development and implementation of the SDMX;of the SDMX;
to prepare suggestions on how to take steps to prepare suggestions on how to take steps to implement the SDMX;to implement the SDMX;
to acquaint the wider interested public with to acquaint the wider interested public with the SDMXthe SDMX. .
Statistical Metadata System and the Statistical Metadata System and the Statistical Business ProcessStatistical Business Process
The most important activities which enable the Slovenian statistical system to complete the mission are: modern approach to total quality management; competency of the staff; up-to-date harmonization with the international environment; user-orientation; modernisation of processes; improvement of working conditions.
Statistical business process model Statistical business process model
The thorough process of analyzing processes (from 2006 to spring 2007).
The breakdown of processes (structure) presents a sound basis.
Around 150 meetings and workshops from January 2007 to November 2008 helped clarify objectives of the project.
There were more challenges revealed.
1
Quality Management / Metadata Management
1 Specify needs
2 Design
3 Build
4 Collect
5 Process
6 Analyse
7 Disseminate
8 Archive
1.1 Determine need for
information
1.2 Consult and confirm need
1.3 Establish
output objectives
1.4 Check data availability
1.5 Prepare
business case
2.1 Outputs
2.2 Frame
and sample methodology
2.4 Data
collection
2.5 Statistical processing
methodology
2.6 Processing
systems and workflow
3.1 Data
collection instrument
3.2 Process
components
3.3 Configure workflows
3.4 Test
3.5 Finalise
production systems
4.1 Select sample
4.2 Set up
collection
4.3 Run collection
4.4 Load data
into processing
environment
5.1 Standardi-
ze and anonymize
5.2 Integrate
data
5.3 Classify and code
5.4 Edit and impute
5.5 Derive new variables
5.7 Calculate
aggregates
6.1 Acquire domain
intelligence
6.2 Prepare draft
outputs
6.3 Verify outputs
6.4 Interpret and
explain
6.5 Disclosure
control
6.6 Finalize
outputs for disseminati-
on
7.1 Update output
systems
7.2 Produce products
7.3 Manage release
of products
7.5 Manage customer queries
7.4 Market and
promote products
8.1 Define archive
rules
8.2 Manage archive
repository
8.3 Preserve data and
associated metadata
8.4 Dispose of data and
associated metadata
5.6 Calculate weights
2.3 Variables
9 Evalua
te
9.1 Gather evaluati
on inputs
9.2
Prepare evaluati
on
9.3 Agree action plan
1.6 Methodology
analysis
1.7 Incorporation
annual program of
statist.surveys
2.7 Agreements with other institutions
9.4 Analyse process
data
GSBPMGSBPM SORS modelSORS model SORS useSORS use
®® ®® ®®
®® ®®
®®
®® ®®
SBPM as an input in ISISSBPM as an input in ISIS
The analysis of The analysis of processes was processes was one of the one of the inputs into the inputs into the project ISIS.project ISIS.
SPM – STATISTICAL
PROCESSING MODULE ADMINISTRATION
(ADMINISTRATION)
SBRM -STATISTICAL BUSINESS
REGISTRY MODULE(REGISTRY)
DCM -DATA COLLECTION
MODULE(RESPONDENT LIST,
E-REPORTING)
SDM -SURVEY DESIGN MODULE
(VARIABLES, QUESTIONNAIRES)
SPM – STATISTICAL
PROCESSING MODULE(SURVEYS AND DATA)
Current system Current system
ISIS
Connection
KLASJE
Replications
METIS
Classifications
Variables, questionnaires, address lists, process metadata.
Integrated Statistical Information System
Annual programme of statistical surveys, survey
instances, activities, working plan with
activities, publications, release calendar
Costs and Benefits Costs and Benefits
The current metadata system was gradually The current metadata system was gradually developed, starting in 1997.developed, starting in 1997.
"Modernisation and development of the statistical "Modernisation and development of the statistical information system in Slovenia“ (February - information system in Slovenia“ (February - September 1997 ) – September 1997 ) – short short term missions to SORS term missions to SORS by experts from Statistics Sweden.by experts from Statistics Sweden.
StatCop98 project - Development of conceptual, StatCop98 project - Development of conceptual, technical and software solutions of common technical and software solutions of common (infrastructure)(infrastructure) importance importance..
Project STAT200Project STAT20000 - focus on dissemination - focus on dissemination procedures.procedures.
IT architecture IT architecture
Key goals for the realisation of the tasks Key goals for the realisation of the tasks in ISISin ISIS:: well computerised and efficient statistical well computerised and efficient statistical
process, supported by general user-friendly process, supported by general user-friendly information solutions;information solutions;
efficient and satisfied internal and external users efficient and satisfied internal and external users of information services;of information services;
competent IT experts;competent IT experts;
electronic storage and archiving.electronic storage and archiving.
Shared servers and dedicated ISIS Shared servers and dedicated ISIS serversservers
Proposed Proposed system system
architecturearchitecture
??
SURS in ISISSURS in ISIS
Input data into MetisInput data into Metis
Respondent list preparation
Respondent list preparation
DCM-respondent list
DCM-respondent list
Questionnaire preparation
Questionnaire preparation
Release of questionnaire
Release of questionnaire
SDMSDM
Data capture from different sources
Data capture from different sources
DCM- E reporting.
DCM- E reporting.
Statistical analysisStatistical analysis
SPMSPM
SURS in ISISSURS in ISIS
ISIS databaseISIS database
Data file system
Data file system
ISISISIS
METISMETIS
Capture metadata about surveys and
activities from Metis
Capture metadata about surveys and
activities from Metis
KlasjeKlasje
Capture classiffications
from Klasje
Capture classiffications
from Klasje
SPM-Administration
SPM-Administration
Review the survey process and administration of the
application
Review the survey process and administration of the
application
DCM-Respondent
list
DCM-Respondent
list
Respondent list preparation and
contacts with units
Respondent list preparation and
contacts with units
SDMSDM
Metadata about surveys,
questionnaires release
Metadata about surveys,
questionnaires release
Metis Activities
Metis Activities
OutsourcingOutsourcing
Outsourcing versus in-house development:Outsourcing versus in-house development: use both internal and external human resources;use both internal and external human resources;
SORS will focus on the internal management of SORS will focus on the internal management of the statistical core business;the statistical core business;
SORS will outsource when this is cost-efficient SORS will outsource when this is cost-efficient and/or presents an opportunity to expand and/or presents an opportunity to expand internal know-how.internal know-how.
Sharing software Sharing software components ocomponents orr tools tools
Scripts, guidelines, manuals for: Scripts, guidelines, manuals for: classification database;classification database; advance release calendar;advance release calendar; WebCMS;WebCMS; registry of statistical surveys and survey registry of statistical surveys and survey
instances;instances; planned activities within survey instances.planned activities within survey instances.
Organisational and workplace Organisational and workplace culture issuesculture issues
Responsible unit for metadata Responsible unit for metadata should beshould be unit for unit for general methodology and standardsgeneral methodology and standards (not at the (not at the moment)moment);;
EDP infrastructure and technologyEDP infrastructure and technology is responsible for is responsible for SDMX and archiving;SDMX and archiving;
There is no permanent metadata management team There is no permanent metadata management team for the moment;for the moment;
Training and knowledge management:Training and knowledge management: constant education,constant education, IT requires trained experts.IT requires trained experts.
Partnerships and cooperation Partnerships and cooperation
Participating in relevant international meetings Participating in relevant international meetings (METIS, OECD and Eurostat);(METIS, OECD and Eurostat);
PC-Axis reference group;PC-Axis reference group;
The classification server was developed with The classification server was developed with thorough documentation from Statistics New thorough documentation from Statistics New Zealand;Zealand;
PHARE projects (COP98, STAT2000, cca 2,5 mio PHARE projects (COP98, STAT2000, cca 2,5 mio Euro) and 2005 Transition Facility Program (ISIS, Euro) and 2005 Transition Facility Program (ISIS, cca 1,2 mio Euro);cca 1,2 mio Euro);
Studying solutions developed elsewhereStudying solutions developed elsewhere is the is the primary source of knowledge in the metadata fieldprimary source of knowledge in the metadata field. .
Lessons learned Lessons learned
Participation in expert conferences and bilateral Participation in expert conferences and bilateral cooperation with foreign officescooperation with foreign offices is necessary is necessary;;
Total quality management priorities;Total quality management priorities;
The preparation of internal methodological manuals;The preparation of internal methodological manuals;
SORS attempts to increase interest in implementing SORS attempts to increase interest in implementing the quality standards of the ESS among authorised the quality standards of the ESS among authorised producers of national statistics. producers of national statistics.
Lessons learned Lessons learned - - ISIS final report ISIS final report Project ISIS is too complex;Project ISIS is too complex;
User specifications were too general;User specifications were too general;
Detail specifications preparation together with business Detail specifications preparation together with business process redesign;process redesign;
Fluctuation of the consultant's staff;Fluctuation of the consultant's staff;
Remote access to the SORS test environment;Remote access to the SORS test environment;
Organizational adaptation of SORS;Organizational adaptation of SORS;
Organization of user testing and bug repairOrganization of user testing and bug repair on some on some modules not efficientmodules not efficient;;
Split future complex projects into two or three smaller Split future complex projects into two or three smaller projects!projects!