Error message

Deprecated function: The each() function is deprecated. This message will be suppressed on further calls in menu_set_active_trail() (line 2405 of /home/planni12/public_html/new/includes/

The Importance of Data Quality in the National Census

Thursday 10th September, 2020.
Source: Thursday Business Guardian
Author: Central Statistical Office


National census data are a public good. The data serve as a necessary information resource and are instrumental to the sustainable development of our nation, its political representation as well as private and public sector investment. Census data are also used to determine Standard of Living as well as the Gross Domestic Product (GDP) which affects Trinidad and Tobago´s global position and status.

Standard of living is measured using easily quantifiable factors such as income, poverty, cost of goods and services as well as life expectancy. Much of this information can be derived from high quality census data. Similar measures are used to determine a country's GDP or economic health. Both standard of living and GDP present foreign investors and policymakers with a snapshot of Trinidad and Tobago´s current social and economic reality. Given this reality it is critical that the data be of high quality and integrity.

High quality data can be used to inform the socio-demographic statistics needed to achieve subnational, national, regional and global developmental agendas. The quality of the data collected must comply with worldwide standards and satisfy rigorous examination. The fundamental aspects of data quality as defined by the Organisation for Economic Co-operation and Development (OECD) Glossary of Statistical Terms are:

  • Relevance
  • Accuracy
  • Credibility
  • Timeliness
  • Accessibility
  • Interpretability
  • Coherence.

For the purposes of this column, and to help build a deeper understanding of official statistics, here are the definitions for these terms.

Relevance is defined as the degree to which the data sought by users for a given purpose effectively meets their needs. The identification of users and their expectations is therefore necessary. In the Trinidad and Tobago context, domains for which statistics are available should reflect the needs and priorities expressed by the users of the Trinidad and Tobago Statistical system.

Accuracy in data quality is defined - as the closeness of computations or estimates to the exact or true values that the statistics were intended to measure. The accuracy of the data published is significantly determined by the accuracy of the data received from the contributing organisations and households. Underserved populations and unaddressed social inequalities can be thoroughly examined with accurate census data.

Credibility - The credibility of data products refers to the confidence that users place in those products based simply on how they perceive and extent to which they trust the producer of the data. This implies that the data are perceived to be produced professionally in accordance with appropriate statistical standards, and that policies and practices are transparent. Credibility is determined in part by the integrity of the production process.

Timeliness and punctuality in disseminating results is the provision of up-to-date figures which are published frequently and on time at pre-established dates. The timeliness of data products reflects the period to which the data relates. Punctuality of data products is also very important, both for national and international data providers and implies the existence of a publication schedule and reflects the degree to which data are released in accordance with it

Accessibility and clarity of the information: statistical data have most value when they are easily accessible by users, are available in the forms users desire and are adequately documented. The interpretability of data products reflects the ease with which the user may understand and properly use and analyse the data. The adequacy of the definitions of concepts, target populations, variables and terminology, underlying the data, and information describing the limitations of the data, if any, largely determines the degree of interpretability.

Coherence: The coherence of data products reflects the degree to which they are logically connected and mutually consistent. Coherence implies that the same term should not be used without explanation for different concepts or data items; that different terms should not be used without explanation for the same concept or data item; and that variations in methodology that might affect data values should not be made without explanation. Coherence in its loosest sense implies the data are "at least reconcilable."

National statistical systems form an important part of a nation´s data ecosystem which includes private and public sector partners, civil societies, the academic community, regional and international bodies. By subscribing to fundamental aspects of data quality described above, we can produce the high quality national census data necessary to improve the country's global ranking and competitive advantage.


Definitions from the

Quality Framework and Guidelines for OECD

Statistical Activities STD/QFS (2011)1