AbstractThis paper describes the development of an integrated vocabulary of energy terminology and it explores the potential for a fully developed energy vocabulary conversion guide. Eleven vocabularies were analyzed and integrated: AIP, CA, API, GA, INIS, TEST, GEOR, El, PA, DDC, and NASA.The following major concepts were considered within the scope: energy sources (fuels); derived products; exploration, production and processing; energy conversion; energy transportation, transmission and distribution; energy consumption, utilization, and conservation; power generation; energy storage; energy policy and legislation; environmental impacts; transportation modes (land, air, sea); propulsion systems; consuming sectors and economics; and international supply and consumption.The methodology consisted of 1) establishing term selection criteria, 2) analyzing individual system vocabularies for energy‐related terms, 3) processing energy subsets and 4) reviewing the integrated product and generating a final vocabulary.Three broad problem areas were identified during the study: 1) energy definition, 2) analyst viewpoint variances, 3) thesaurus format/convention variances. The conceptualization, identification, and selection of energy terms was especially difficult in several subject disciplines, including such areas as engineering materials, mathematics, electronics, explosives, psychology and other social sciences. Five types of synonym construction were encountered.It was concluded that vocabulary conversion, which permits subject switching, offers some degree of inter‐system compatibility. Conversion is the ability to retrieve all documents on a given subject from all available (and appropriate) data bases with a single query. When coupled with development of a standard system protocol, full information‐resource utilization will be possible.A prototype conversion guide (synonym table) was constructed for further study. One of the significant findings was that, without any additional intellectual efforts, conversion can be increased from 28 percent (exact match only) to 46 percent using exact match plus singular‐plural equivalencies, plus synonym expansion.