Dimensions of Quality in Data

There are seven categories (or dimensions) that are often used to assess the quality of national official data in terms of fitness for use.

What is fitness of use? Well, if data is described as fit for use, that means we can have confidence that it meets the data user's requirements and needs. If we are producing data from survey research that is unusable or answering questions no one needs or wants, then our data will not have good 'fitness of use'.

So what are those 7 categories and what do they mean? They are:

Accessibility: Can users easily obtain and analyze the data?

Accuracy: Is the data describing the phenomena that they were designed to measure?

Coherence: Does the data form a coherent body of information that can be rearranged or combined with other data or into a written report?

Comparability: Is the data from different countries or cultures of comparable quality to each other?

Interpretability: Does the data make sense in terms of users' hypotheses? Is there other data available to help with the analysis and data about the survey processes?

Relevance: Does the data meet the requirements of the client and users?

Timeliness and punctuality: How much time has elapsed between the end of the data collection and when the data is available for analysis? Is the data available when expected, based on client specifications?

Keeping these 7 factors and other contributing factors such as cost, burden on both the respondent and the interviewer, professionalism and instrument design in mind when preparing for a research effort will ensure the data gathered and disseminated will have overall fitness of use.
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