In the past years, significant progress has been made in the development and use of settings for collection of experimental data on tobacco exposure and the diseases induced by it. Despite the growing number of such data, there has been no community wide effort to facilitate the centralization and integration of tobacco exposure data scattered throughout a range of disparate sources. Moreover, to fulfill the aim of exposure and disease impact studies, it is of utmost importance to more reliably and efficiently establish the causal link to disease. Ontologies are structural frameworks for organizing knowledge, enabling information retrieval, and supporting data integration, data analysis, and exchange of knowledge within the community. Cigarette smoke exposure ontology (CSEO) was developed which is a specialized ontology with particular focus on the cigarette smoke exposure and related various experimental systems. Combining efforts of domain experts as well as novel computational methods, the ontology successfully describes exposure related terminology ranging from the scope and design definition of an experiment to its outcome with link to molecular events and ultimately to disease. After several iterations between the computational and domain expert groups, CSEO encompasses more than 20.000 concepts and classes. This ontology is represented in web ontology language (owl) format and is made freely available to the community through several channels.