The potential of information-driven disciplines such as biology and clinical science can be realized only if those involved in the production and analysis of data can successfully build upon each other’s work. The quantity and heterogeneity of the data being produced raises challenges to this goal, and so also does the tendency of different communities to describe their data in different, sometimes ad hoc, ways. If computers are effectively to exploit the results of scientific research and enable interoperability among diverse data repositories, then a strategy is needed to counteract such tendencies to data-silo formation. The use of common, consensus-based, controlled vocabularies to tag or describe data is one such strategy. Applied ontology is the discipline which creates, evaluates, and applies such common vocabularies – called ‘ontologies’ – a discipline which involves contributions from philosophers, logicians, and computer scientists, working with researchers in specific scientific disciplines as well as with users and creators of data in extra-scientific fields. Ontologies provide not merely common terms, but also definitions of these terms expressed in a formal language to allow processing by computers. The book describes the concrete steps involved in building and using ontologies for purposes of tagging data. It documents principles of best practice and provides examples of different sorts of errors to be avoided. It also provides an introduction to a specific top-level ontology, the Basic Formal Ontology (BFO), and to the computational resources used in building and applying ontologies, including the Ontology Web Language (OWL).