Principles
This document provides a summary of the overarching principles of NCVER’s Data quality policy.
Scope
The following principles apply to the VET administrative collections and surveys for which NCVER is the data custodian on behalf of the State and Territory and Commonwealth Governments. They also apply to the use of NCVER data in NCVER research, including work commissioned under the National Vocational Education and Training Research (NVETR) Program.
Data quality principles
The data quality principles that underpin NCVER’s data collection processes align with the Australian Bureau of Statistics Data Quality Framework’s dimensions of quality. More information about the quality dimensions is available on the Australian Bureau of Statistics website.
1. Institutional environment
This principle refers to the institutional and organisational factors that may have a significant influence on the effectiveness and credibility of NCVER in developing, producing and disseminating statistics and research publications. Issues relevant to this principle are professional independence, mandate for data collection, adequacy of resources, quality commitment, statistical confidentiality, impartiality and objectivity.
2. Relevance
The relevance of statistical information reflects the degree to which it meets the needs of users. Assessing relevance is a subjective matter dependent upon the varying needs of users. NCVER’s challenge is to weigh and balance the conflicting needs of current and potential users to produce a program that goes as far as possible in satisfying the most important needs within given resource constraints. Issues relevant to this principle are the scope and coverage, classifications and statistical standards, reference period, geographic detail, and concepts measured.
3. Timeliness and punctuality
The timeliness of statistical information refers to the delay between the reference point (or the end of the reference period) to which the information pertains, and the date on which the information becomes available. It is typically involves a trade-off against accuracy. The timeliness of information influences its relevance.
Data should be released in a timely and punctual manner, the periodicity of which takes into account user requirements as much as possible. When considered useful, preliminary results of acceptable aggregate accuracy may be released.
4. Accuracy
Accuracy refers to the degree to which the data correctly describe the phenomenon they were designed to measure. This is an important component of quality which has clear implications for how useful and meaningful the data will be for interpretation or further analysis. Accuracy may also be described in terms of the major sources of error that potentially cause inaccuracy (e.g. coverage, sampling, nonresponse and response).
5. Coherence and comparability
Coherence refers to the degree to which statistical information can be successfully brought together with other statistical information within a broad analytic framework and over time. The use of standard concepts, classifications and target populations promotes coherence, as does the use of common methodology across statistical collections. Coherence does not necessarily imply full numerical consistency, rather consistency in methods and collection standards.
6. Interpretability
The interpretability of statistical information refers to the availability of supplementary information and metadata necessary to interpret and use the data appropriately. This information normally covers the underlying concepts, variables and classifications used, scope, the methodology of data collection and processing, and indications of the accuracy of the statistical information.
7. Accessibility
Accessibility refers to the ease with which statistical information can be accessed by users. This includes the ease with which the existence of information can be ascertained, as well as the suitability of the form or medium through which the information can be accessed. The cost of the information may also be an aspect of accessibility for some users. Data should be presented in a clear and understandable form, released in a suitable and convenient manner, and made available and accessible on an impartial basis with supporting metadata and guidance.