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Metadata: Integral Part of Statistics Canada Quality Framework. International Conference on Agriculture Statistics October 22-24, 2007 . Marcelle Dion Director General, Agriculture, Technology and Transportation Statistics, Statistics Canada. Outline. Quality Assurance Management

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Metadata: Integral Part of Statistics Canada Quality Framework

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Metadata integral part of statistics canada quality framework l.jpg

Metadata: Integral Part of Statistics Canada Quality Framework

International Conference on Agriculture Statistics

October 22-24, 2007

Marcelle Dion

Director General, Agriculture, Technology and Transportation Statistics, Statistics Canada

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  • Quality Assurance Management

  • Integrated Metadata Base

  • Application to Agriculture Statistics

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Statistics Canada’s Quality Assurance Management

  • Three key elements:

    • Quality Assurance Framework

    • Policy on Informing Users of Data Quality and Methodology

    • Integrated Metadata Base

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Quality Assurance Framework

  • Defines quality as “fitness for use”

  • Identify six indicators of “fitness for use”

    • Relevance, accuracy, timeliness, accessibility, interpretability and coherence

  • Metadata: at the heart of the management of the interpretability indicator

    • Interpretability refers to the provision of information that help users understand the data released by Statistics Canada

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Policy on Informing Users of Data Quality and Methodology

  • One of the policies that governs Statistics Canada

  • Requires all statistical outputs to have information (metadata) on:

    • Concepts and definitions

    • Methodology used to produce the data

    • Data accuracy

  • Defines standards and guidelines

  • Identifies responsibilities

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Integrated Metadata Base

  • Definition of Metadata

  • Characteristics of the Data Base

  • Governance

    • Policy

    • Technical Assistance

    • Monitoring

  • Access

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Definition of Metadata

  • Metadata

    • inform users of the features that affect the quality of all data published by Statistics Canada.

    • provide a better understanding of the strengths and limitations of data, and how they can be effectively used and analyzed

    • are of particular importance when making comparisons with

      • data across surveys or sources of information

      • in drawing conclusions regarding

        • changes over time

        • differences between geographic areas

        • differences among sub-groups of the target populations of surveys

    • breed users’ trust

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Integrated Metadata BaseCharacteristics

  • Corporate repository of metadata

  • Metadata for 415 active and 400 inactive surveys (discontinued or one time)

  • Metadata for any survey instance since November 2000

  • Easily accessible online:

  • Metadata complies with policy

    • Minimum requirements

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Metadata: Policy’s Minimum Requirements

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Integrated Metadata BaseGovernance

  • Policy ensures compliance

  • Policy ensures coherence

  • Policy defines accountability

    • Managers of program areas

    • Methods and Standards Committee

  • Standards Division responsible for management

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Integrated Metadata BaseTechnical Assistance

  • Metadata Officers

  • Guidelines for author

  • Template

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Template – One SectionData Sources – Type of Surveys

  • Please highlight the terms that apply to this survey

  • (more than one source may apply)

  • Direct – data are collected directly from STC respondents with the use of a collection instrument

  • Administrative - data are extracted from administrative files provided by an external organization that collected them for reasons other than statistical purposes

  • Derived – Data were derived from other Statistics Canada programs or surveys and/or other sources (e.g. media, annual reports) ---------------------------------------------------------

  • Census – the intent is to collect information from all units of the survey population

  • Sample – information is collected from only a fraction of units of the survey population

  • ----------------------------------------------------------

  • Longitudinal – the same statistical units are followed over time

  • Cross-sectional – the statistical units are specific to one point in time

  • Cross-sectional with longitudinal follow-up – the statistical units which are specific to one point in time are also followed over time

  • -----------------------------------------------------------

  • Mandatory – respondents are required, under the Statistics Act, to answer all the survey questions

  • Voluntary – respondents may refuse to answer some or all of the survey questions

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Integrated Metadata BaseQuality Monitoring

  • Triggers for creating or updating records

  • Information loading: Template

  • Metadata officers’ review

    • Identify program areas needing assistance

  • Exhaustive review -

    • Four-point scale

    • Official notice to program areas’ managers

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Users’ AccessMetadata Flow

¤ CANSIM ¤Summary Table ¤ Analytical Studies

¤Online Catalogue ¤ Publication ¤Information for Survey Participants

¤The Daily ¤ Definitions, Data Sources and Methods

Web Page Generation of Documentation

  • Integrated Metadatabase

  • Definition of variable

  • Survey description/methodology/questionnaire/documentation

  • Data accuracy

IMDB Team in Standards Division


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Agriculture Statistics

  • Description of the program

  • Framework

  • Metadata

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Program Description

  • Monthly, quarterly, annual and/or seasonal data collection activities related to crop and livestock and farm finances as needed

  • Quinquennial Census of Agriculture with the Census of Population

  • Economic series on the agriculture sector

    • System of National Accounts (SNA) and agriculture GDP

  • Administrative data supplement limited survey taking in supply-managed agriculture sectors such as dairy and poultry

  • Taxation data for annual disaggregated financial information

  • Cost-recovery program (e.g. farm assets and liabilities, etc.)

  • Farm Register

    • Agriculture surveys’ frame

    • Large, complex agricultural operations’ profile

  • Joint collection agreements with most provincial and territorial departments of agriculture

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    Agriculture Statistics Framework

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    Agriculture Program Metadata

    • IMDB includes 45 separate records covering current survey activities

    • One step further: the statistical activity

      • IMDB structure that groups together surveys that share common processing system or conceptual framework

    • Agriculture statistics program statistical activity

      • would be organized around the farm income series structure

      • would facilitate users’ understanding of the interrelationships between the various components of the integrated program

      • Would increase users’ awareness that the “fitness for use” test of the farm income series should take into account the metadata information of all the farm income series’ inputs.

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    • Data quality is a survival issue for any statistical agency

      • loss of users’ confidence in data would render statistical agency ineffective

    • Metadata: openness and transparency about data –about their weaknesses just as much as about their strengths

    • IMDB – by making metadata easily accessible to users – helps build trust

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    For more information Pour plus de renseignements

    please contactveuillez contacter

    Marcelle Dion

    Director General Agriculture, Technology

    and Transportation Statistics Branch

    Statistics Canada

    13th Floor Section B-7, Jean Talon Building

    170 Tunney’s Pasture Driveway

    Ottawa (Ontario), Canada

    K1A 0T6


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