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Jitka Prokop, Czech Statistical Office. SMS-QUALITY T he project and application focused on metadata on quality. European conference on Quality in Official statistics 3-5 June 2014, Vienna. Introduction - aims, features, coverage, current state

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Jitka prokop czech statistical office

Jitka Prokop, Czech Statistical Office

SMS-QUALITY

The project and application

focused onmetadata on quality

European conference on Quality in Official statistics

3-5 June 2014, Vienna


Jitka prokop czech statistical office

  • Introduction - aims, features, coverage, current state

  • Architecture - Q-attributes, hierarchical structure, design, preparation, data retrievals and inputs, functionality, stability of values and updates

  • Benchmarking

  • Challenges

  • Topics


Jitka prokop czech statistical office

Starting points

  • Horizontal way of management

  • Demands for quality reporting & relevant metadata ‚standardisation‘

  • Standardisation of quality reports & adjustments for domain statistics

    Tool for managers

  • Semi-interactive cross-cutting overviewsabout quality of a survey (incl. assessments…)

  • Quality reporting

  • Application using web-browserenvironment

  • Reasons and Aims


Jitka prokop czech statistical office

  • Q reporting focused on a survey (of any kind) and groups of surveys

  • Cross-cutting info on quality of statistical process, outputdata and products

  • Data preferably retrieved from other source databases

  • Data monitoring, comparisons, aggregations, assessment, benchmarking

  • Flexibilityof metadata content and possibility of survey’s adjustments

  • Help to improve quality reporting and statistical quality itself

  • Encourage self-assessment, support auditing

  • Aims and main features


Jitka prokop czech statistical office

  • The application is integrated within the internal SIS and SMS systems

  • Meta-data values retrieved from databases or manually inputted

  • Design & preparation of various quality reports

  • Hierarchical structure (refers to ESQR, GSBPM, DESAP)

  • Publicvs. non-public – individual items or complete reports

  • Bilingual (multi-lingual) solution

  • Usual output formats PDF, HTML, XLS, DBF, DOC, not SDMX

  • User roles: admin, owner, editors, viewers (public vs. internal)

  • Features


Jitka prokop czech statistical office

Other SMS subsystems can provide certain knowledge on quality criteria e.g. accuracy, relevance, accessibility, clarity, timeliness, punctuality.

  • SMS SURVEYS: statistical processes (particular surveys)

  • SMS REQUIREMENTS: management of main user requirements

  • SMS DISSEMINATION, CATALOGUE OF PUBLICATIONS: dissemination, product quality, info service

    in some cases in relation to concrete surveys

  • Interlinks with other SMS-applications


Jitka prokop czech statistical office

Any statistical process processed or at least with its data stored in the central DWH.

  • Business statistics

  • Social and demography statistics

  • National accounts

  • Price statistics

  • Administrative data statistics.

  • Coverage


Jitka prokop czech statistical office

Type of info on quality - quantitative and qualitative:

  • Reference metadata

  • Info about process and its phases

  • Schedules

  • Quality performance indicators

  • Calculations

  • Benchmark results

  • Evaluation, (self-)assessments, commentaries

  • Textual, Numerical, Date

  • Q-attribute (item, meta-information, indicator)


Jitka prokop czech statistical office

  • Basic information (about a survey)

  • User requirements agenda

  • Methodology info

  • Time schedules; Timeliness; Punctuality

  • Statistical process phases

  • Data confidentiality and protection

  • Data sources; Frame; Sample

  • Outputs and dissemination

  • Individual quality criteria (i.e. quality dimensions)

  • Quality performance indicators

  • Categories of Q-attributes (info on…)


Jitka prokop czech statistical office

Relates to functionality (stability of values)

  • General

  • Statistical survey (key users, methodology, key statistical variables…)

  • Reference year

  • Processing (all reference periods processed or revised at one time)

  • Reference periods

  • Levels of Q-attributes


Jitka prokop czech statistical office

  • To provide relevant & up-to-date information

  • Validity for certain years, batches (i.e. processings), ref.periods

    • When generating data for new reference periods...

  • Metadata updates on each level

    • How to update the derived Q-Maps

    • Managers informed and decide via the application

  • Keeping history and updates

  • Updates of metadata structures and values


Jitka prokop czech statistical office

  • Structure (hierarchy): Sections, Sub-sections, Q-attributes

  • Q-Maps: monitoring, benchmarking

    General - > Specific -> Survey Q-Maps design, specifications

    Value Q-Maps output report

    • Q-Forms: also comparisons and aggregations…

      General QM for Q-Forms -> Q-Form -> Value Q-Form

      Q-Forms use (not only) ValueQ-Maps as the source of data

  • Q-Maps & Q-Forms


Jitka prokop czech statistical office

Comparisons, aggregations over

  • Statistical variables

  • Reference periods

  • Surveys

  • Years…

    Which data

  • Values

  • Benchmark results

  • Q-Forms - comparisons, aggregations


Jitka prokop czech statistical office

Design of a report

  • General Q-Map -> A type of report.

    General design, pre-setting of parameters.

  • Specific Q-Map -> A group of surveys.

    Selection of Q-attributes, way of benchmarking.

  • Survey Q-Map -> A survey

    Statistical variables, benchmark scales, links to data.

    Output report

  • Value Q-Map -> One reference period.

    Retrieval, editing, approval of values. Benchmarking.

  • Levels of Q-Maps - Hierarchy


Jitka prokop czech statistical office

  • Primarily for internal management purposes

  • Benchmarked values: numerical or textual

  • Adjustments of scales (boundaries) for particular surveys

  • Parameters

    • To benchmark or not to benchmark?

    • Manually (each value individually) or Automatically (pre-definitions)

    • Categories’ definition –number of categories, and either definition of boundaries or assignment of values from a nomenclature

    • Categories’ labelling –from a special nomenclature or directly in the app

  • Benchmarking


Jitka prokop czech statistical office

  • Deeper relations between subsystems

  • Revisions of quality attributes

  • Involvement of domain statisticians

  • Full implementation

  • ESS standard quality reports in SDMX

  • Challenges


Jitka prokop czech statistical office

Thank you for your attention.

Any questions?

[email protected]


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