| Resumo: |
A major challenge in bioinformatics, life sciences, and medicine is using correct and informative names. While this sounds simple enough, many different naming conventions exist in the life sciences and medicine that may be either complementary or competitive with other naming conventions. For a variety of reasons, proper names are not always used, leading to an accumulated semantic ambiguity that readers of the literature and end users of databases are left to resolve on their own. This ambiguity is a growing problem and the biocuration community is aware of its consequences. 

To assist those confronted with ambiguous names (which not only includes researchers but clinicians, manufacturers, patent attorneys, and others who use biological data in their routine work), we developed a generalizable semantic model that represents names, concepts, and exemplars (representations of biological entities) as distinct objects. By identifying each object with a Digital Object Identifier (DOI) it becomes possible to place forward-pointing links in the published literature, in databases, and vector graphics that can be used as part of a mechanism for resolving ambiguities, thereby “future proofing” a nomenclature or terminology. A full implementation of the N4L model for the _Bacteria_ and _Archaea_ was released in April, 2010. The system is professionally curated and represents a Tier III resource in Parkhill’s view of bioinformatic services. A variety of tools and web services have been developed for readers, publishers, and others (N4L Guide, N4L Autotagger, N4L Semantic Search, N4L Taxonomic Abstracts) and we are incorporating other taxonomies into the N4L data model, as well as adding additional phenotypic, genotypic, and genomic information to the existing exemplars to add greater value to end users.
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