This paper reviews and compares the main methodologies, tools, and languages for building ontologies, as well as their relationships. Ontology technology is now mature, with many methodologies, tools, and languages available. Future work should focus on creating a common integrated workbench for ontology developers to facilitate development, exchange, evaluation, evolution, and management of ontologies. This workbench should integrate existing technologies rather than being built from scratch. The paper discusses the definitions of ontologies, their methodologies, and the relationships between them. Ontologies aim to capture consensual knowledge in a generic and formal way, and can be reused and shared across applications and groups. Ontologies are usually built cooperatively by a group of people in different locations. Several methodologies for building ontologies are presented, including METHONTOLOGY, On-To-Knowledge, and others. These methodologies vary in their approach, with some being application-dependent, semi-application-dependent, or application-independent. The paper also discusses ontology development tools, such as Ontolingua Server, OntoSaurus, WebODE, OntoEdit, and Protégé 2000, which support various aspects of ontology development. Ontology languages such as KIF, Loom, OCML, FLogic, and RDF(S) are discussed, along with their features and expressiveness. These languages are continuously evolving, and their relationships are shown in a stack of ontology markup languages. The paper concludes that there is no direct correspondence between ontology building methodologies and tools, except for METHONOLOGY and WebODE, and On-To-Knowledge and OntoEdit. Most tools focus on a few activities of the ontology lifecycle. Ontology markup languages are still in development, and it is difficult to have up-to-date technology for managing them. The main problem in ontology tool development is the lack of integrated environments for ontology development. Future work should focus on creating a common workbench for ontology development that facilitates the entire ontology life cycle, including knowledge acquisition, edition, browsing, integration, merging, reengineering, evaluation, translation, and interchange of content with other tools. This workbench should also include middleware services to support the use of ontologies in other systems.This paper reviews and compares the main methodologies, tools, and languages for building ontologies, as well as their relationships. Ontology technology is now mature, with many methodologies, tools, and languages available. Future work should focus on creating a common integrated workbench for ontology developers to facilitate development, exchange, evaluation, evolution, and management of ontologies. This workbench should integrate existing technologies rather than being built from scratch. The paper discusses the definitions of ontologies, their methodologies, and the relationships between them. Ontologies aim to capture consensual knowledge in a generic and formal way, and can be reused and shared across applications and groups. Ontologies are usually built cooperatively by a group of people in different locations. Several methodologies for building ontologies are presented, including METHONTOLOGY, On-To-Knowledge, and others. These methodologies vary in their approach, with some being application-dependent, semi-application-dependent, or application-independent. The paper also discusses ontology development tools, such as Ontolingua Server, OntoSaurus, WebODE, OntoEdit, and Protégé 2000, which support various aspects of ontology development. Ontology languages such as KIF, Loom, OCML, FLogic, and RDF(S) are discussed, along with their features and expressiveness. These languages are continuously evolving, and their relationships are shown in a stack of ontology markup languages. The paper concludes that there is no direct correspondence between ontology building methodologies and tools, except for METHONOLOGY and WebODE, and On-To-Knowledge and OntoEdit. Most tools focus on a few activities of the ontology lifecycle. Ontology markup languages are still in development, and it is difficult to have up-to-date technology for managing them. The main problem in ontology tool development is the lack of integrated environments for ontology development. Future work should focus on creating a common workbench for ontology development that facilitates the entire ontology life cycle, including knowledge acquisition, edition, browsing, integration, merging, reengineering, evaluation, translation, and interchange of content with other tools. This workbench should also include middleware services to support the use of ontologies in other systems.