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All (5)

All (5) ((5 results))

  • 1. Statistics Canada Quality Guidelines
    Surveys and statistical programs – Documentation: 12-539-X
    Description:

    This document brings together guidelines and checklists on many issues that need to be considered in the pursuit of quality objectives in the execution of statistical activities. Its focus is on how to assure quality through effective and appropriate design or redesign of a statistical project or program from inception through to data evaluation, dissemination and documentation. These guidelines draw on the collective knowledge and experience of many Statistics Canada employees. It is expected that Quality Guidelines will be useful to staff engaged in the planning and design of surveys and other statistical projects, as well as to those who evaluate and analyze the outputs of these projects.

    Release date: 2019-12-04
  • 2. Data Literacy: What It Is and How to Measure It in the Public Service Archived
    Articles and reports: 11-633-X2019003
    Description:

    This report provides an overview of the definitions and competency frameworks of data literacy, as well as the assessment tools used to measure it. These are based on the existing literature and current practices around the world. Data literacy, or the ability to derive meaningful information from data, is a relatively new concept. However, it is gaining increasing recognition as a vital skillset in the information age. Existing approaches to measuring data literacy—from self-assessment tools to objective measures, and from individual to organizational assessments—are discussed in this report to inform the development of an assessment tool for data literacy in the Canadian public service.

    Release date: 2019-08-14
  • 3. The value of data in Canada: Experimental estimates Archived
    Articles and reports: 13-605-X201900100009
    Description:

    In this paper a preliminary set of statistical estimates of the amounts invested in Canadian data, databases and data science in recent years are presented. The results indicate rapid growth in investment in data, databases and data science over the last three decades and a significant accumulation of these kinds of capital over time.

    Release date: 2019-07-10
  • 4. Measuring investment in data, databases and data science: Conceptual framework Archived
    Articles and reports: 13-605-X201900100008
    Description:

    This paper aims to expand the current national accounting concepts and statistical methods for measuring data in order to shed light on some highly consequential changes in society that are related to the rising usage of data. The paper concludes by discussing possible methods that can be used to assign an economic value to the various elements in the information chain and tests these concepts and methods by presenting results for Canada as a first attempt to measure the value of data.

    Release date: 2019-06-24
  • 5. Transition of Labour Force Survey Data Processing to the Social Survey Processing Environment (SSPE) Archived
    Surveys and statistical programs – Documentation: 75-005-M2019001
    Description:

    The production of statistics from the Labour Force Survey (LFS) involves many activities, one of which is data processing. This step involves the verification and correction of survey data when required in order to produce microdata files. Beginning in January 2019, LFS processing will be transitioned to a new system, the Social Survey Processing Environment. This document describes the development and testing that preceded the implementation of the new system, and demonstrates that the transition is expected to have minimal impact on LFS estimates and be transparent to users of LFS data.

    Release date: 2019-02-08
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Analysis (3)

Analysis (3) ((3 results))

  • 1. Data Literacy: What It Is and How to Measure It in the Public Service Archived
    Articles and reports: 11-633-X2019003
    Description:

    This report provides an overview of the definitions and competency frameworks of data literacy, as well as the assessment tools used to measure it. These are based on the existing literature and current practices around the world. Data literacy, or the ability to derive meaningful information from data, is a relatively new concept. However, it is gaining increasing recognition as a vital skillset in the information age. Existing approaches to measuring data literacy—from self-assessment tools to objective measures, and from individual to organizational assessments—are discussed in this report to inform the development of an assessment tool for data literacy in the Canadian public service.

    Release date: 2019-08-14
  • 2. The value of data in Canada: Experimental estimates Archived
    Articles and reports: 13-605-X201900100009
    Description:

    In this paper a preliminary set of statistical estimates of the amounts invested in Canadian data, databases and data science in recent years are presented. The results indicate rapid growth in investment in data, databases and data science over the last three decades and a significant accumulation of these kinds of capital over time.

    Release date: 2019-07-10
  • 3. Measuring investment in data, databases and data science: Conceptual framework Archived
    Articles and reports: 13-605-X201900100008
    Description:

    This paper aims to expand the current national accounting concepts and statistical methods for measuring data in order to shed light on some highly consequential changes in society that are related to the rising usage of data. The paper concludes by discussing possible methods that can be used to assign an economic value to the various elements in the information chain and tests these concepts and methods by presenting results for Canada as a first attempt to measure the value of data.

    Release date: 2019-06-24
Reference (2)

Reference (2) ((2 results))

  • 1. Statistics Canada Quality Guidelines
    Surveys and statistical programs – Documentation: 12-539-X
    Description:

    This document brings together guidelines and checklists on many issues that need to be considered in the pursuit of quality objectives in the execution of statistical activities. Its focus is on how to assure quality through effective and appropriate design or redesign of a statistical project or program from inception through to data evaluation, dissemination and documentation. These guidelines draw on the collective knowledge and experience of many Statistics Canada employees. It is expected that Quality Guidelines will be useful to staff engaged in the planning and design of surveys and other statistical projects, as well as to those who evaluate and analyze the outputs of these projects.

    Release date: 2019-12-04
  • 2. Transition of Labour Force Survey Data Processing to the Social Survey Processing Environment (SSPE) Archived
    Surveys and statistical programs – Documentation: 75-005-M2019001
    Description:

    The production of statistics from the Labour Force Survey (LFS) involves many activities, one of which is data processing. This step involves the verification and correction of survey data when required in order to produce microdata files. Beginning in January 2019, LFS processing will be transitioned to a new system, the Social Survey Processing Environment. This document describes the development and testing that preceded the implementation of the new system, and demonstrates that the transition is expected to have minimal impact on LFS estimates and be transparent to users of LFS data.

    Release date: 2019-02-08
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