Soil moisture is an important variable in the climate system. Understanding and predicting variations of surface temperature, drought, and flood depend critically on knowledge of soil moisture variations, as do impacts of climate change and weather forecasting. An observational data set of actual in situ measurements is crucial for climatological analysis, for model development and evaluation, and as ground truth for remote sensing. To that end, we developed the Global Soil Moisture Data Bank, a web site (http://climate.envsci.rutgers.edu/soil_moisture) dedicated to collection, dissemination, and analysis of soil moisture data from around the globe. We currently have soil moisture observations for over 600 stations from a large variety of global climates, including the former Soviet Union, China, Mongolia, India, and the United States. Most of the data from outside the United States are in situ gravimetric observations of soil moisture; all extend for at least 6 years and most for more than 15 years. Most of the stations have grass vegetation, and some are agricultural. In the past several years, extensive networks of in situ soil moisture observations have been developed in the United States, using various automatic instruments. Here we present a survey of the existing data sets and examples of how these data are being used for all the purposes listed above. A global soil moisture data set is possible in the next decade, requiring a data assimilation system using validated land surface models, remote sensing, and in situ observations, but it will require continuing expanded, high-quality, in situ soil moisture monitoring.