Creating Semantic Web Contents with Protégé-2000

today. We need a Semantic Web to express information in a precise, machine-interpretable form, so software agents processing the same set of data share an understanding of what the terms describing the data mean.1 Consequently, we’ve recently seen an explosion in the number of Semantic Web languages developed. Because researchers and developers haven’t yet reached a consensus on which language is the most suitable, which features each language must have, or which syntax is the most appropriate, we are likely to see even more languages emerge. We need to develop tools that will let us experiment with these new languages so we can compare their expressiveness and features, change language specifications, and select a suitable language for a specific task. In this article, we describe Protégé-2000, a graphical tool for ontology editing and knowledge acquisition that we can adapt to enable conceptual modeling with new and evolving Semantic Web languages. Protégé-2000 lets us think about domain models at a conceptual level without having to know the syntax of the language ultimately used on the Web. We can concentrate on the concepts and relationships in the domain and the facts about them that we need to express. For example, if we are developing an ontology of wines, food, and appropriate wine–food combinations, we can focus on Bordeaux and lamb instead of markup tags and correct syntax. Naturally, designing a new tool specifically for a new language could be better than adapting an existing tool. We can offer several reasons, however, for adapting an existing tool at the stage where no single language has emerged as the winner. First, we can experiment with emerging languages without committing enormous amounts of resources to creating tools that are custom-tailored for these languages—only to decide later that the languages are not suitable. Second, Protégé-2000 already provides considerable functionality that a new tool will need to replicate, both at the modeling and user-interface levels. Third, using different customizations of the same tool to edit ontologies in different languages gives us most of the translation among the models in the languages “for free.” Translating a model from one language to another becomes as easy as selecting a “save as...” item from a menu.