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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

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

  • Quality Assurance Management
  • Integrated Metadata Base
  • Application to Agriculture Statistics
statistics canada s quality assurance management
Statistics Canada’s Quality Assurance Management
  • Three key elements:
    • Quality Assurance Framework
    • Policy on Informing Users of Data Quality and Methodology
    • Integrated Metadata Base
quality assurance framework
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
policy on informing users of data quality and methodology
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
integrated metadata base
Integrated Metadata Base
  • Definition of Metadata
  • Characteristics of the Data Base
  • Governance
    • Policy
    • Technical Assistance
    • Monitoring
  • Access
definition of metadata
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
integrated metadata base characteristics
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
integrated metadata base governance
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
integrated metadata base technical assistance
Integrated Metadata BaseTechnical Assistance
  • Metadata Officers
  • Guidelines for author
  • Template
template one section data sources type of surveys
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
integrated metadata base quality monitoring
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
users access metadata flow
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


agriculture statistics
Agriculture Statistics
  • Description of the program
  • Framework
  • Metadata
program description
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
agriculture program metadata
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.
  • 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
For more information Pour plus de renseignements

please contact veuillez 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