Data collection
Data collection is the planned gathering of evidence, whether answers, measurements or observations, to answer a research question. It covers deciding what data is needed, choosing methods such as surveys, interviews, observation or experiments, and collecting it the same way for every participant.
How it works
A plan starts with the question and the decision it will inform, then defines what must be measured and from whom. Primary data is collected directly for the study, through surveys, interviews, focus groups, experiments or observation. Secondary data already exists, collected by someone else, such as government statistics, earlier studies or internal records.
The method follows the question: quantitative methods for how many and how much, qualitative methods for why and how. Quality depends on the sample, the instrument (clear, neutral questions), consistent procedures across participants and careful handling of the data. Many projects combine methods, collecting survey data at scale and interview data for depth.
A worked example
A public transit agency needs to decide where to add bus shelters. It combines secondary data (ridership at 900 stops) with primary data: a survey of 2,000 riders and 30 interviews. The data points to 45 stops where riders wait more than 10 minutes in bad weather, and those get shelters first.
Related
Automate this in Pulse
Data collection in Pulse can start from a link shared wherever the population already gathers, a newsletter, a help center or a community forum, as well as from a list a team uploads.