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Not long ago, scientific data was collected almost entirely by professionals. Today, hundreds of thousands of volunteers contribute to research projects in their spare time, counting birds in their gardens, photographing plants and insects, recording rainfall or classifying images of distant galaxies on their home computers. This approach, known as citizen science, has grown rapidly with the spread of smartphones and the internet, which make it easy to submit observations along with a precise time and location. For researchers, the main attraction is scale. No university team could survey every park, river and backyard in a country, but a network of volunteers can, and long-running bird counts have revealed changes in migration timing and population size that would otherwise have gone unnoticed. Volunteers benefit too: many report learning a great deal about their local environment, and some projects have led to genuine discoveries, including astronomical objects first spotted by members of the public. The approach does have weaknesses. Untrained observers may misidentify species, and volunteers tend to record what is easy or interesting to find, so popular, accessible places are studied far more than remote ones. Well-designed projects address these problems by providing training and identification tools, asking several people to check each observation and using statistical methods to correct for uneven coverage. When these safeguards are in place, data gathered by the public can be as reliable as that collected by specialists, and far more extensive.