Taxonomies are essential in science. By classifying objects or phenomena, they facilitate understanding and decision making. In this paper, we focus on the development of taxonomies for complex emerging technologies. This development raises specific challenges. More specifically, complex emerging technologies are often at the intersection of several areas, and the conceptual body of knowledge about them is often just emerging, hence the key role of empirical sources of information in taxonomy building. One particular issue is deciding when enough sources have been examined. In this paper, we use Nickerson et al's methodology for taxonomy development. Based on the identified limitations of this method, we extend it for the development of taxonomies for complex emerging technologies. We identify three types of information sources for taxonomies, and present a set of guidelines for selecting the sources, drawing on systematic literature review. The taxonomy development process iteratively examines sources, performing operations on taxonomies (e.g. addition of a dimension, splitting of a dimension…) as required to take new information into account. We characterize operations on taxonomies. We use this characterization, along with the typology of sources, to help decide when the process of source examination may be stopped. We illustrate our extension of Nickerson et al's method to the development of a taxonomy for business intelligence and analytics on the cloud.