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The emergence of the microarray data standards, especially the Minimum Information About a Microarray Experiment (MIAME), has spurred several organizations to develop their own standards for a myriad of technologies, including proteomics and metabolomics. These efforts have facilitated the creation of several large-scale gene expression repositories, including the toxicology-focused Chemical Effects in Biological Systems Knowledgebase at the National Institute of Environmental Health Sciences. Recently, efforts have been moved toward developing toxicogenomic data standards (e.g., MIAME-Tox), and the U.S. Food and Drug Administration and the U.S. Environmental Protection Agency either have developed or are developing regulatory guidance with respect to pharmaco- and toxicogenomics. However, for the toxicology community to be engaged in the process of standards development and approval, there needs to be a more thorough understanding of the terms associated with electronic data sharing and communication, especially with respect to defining the terms "standard," "controlled vocabulary," "object model," "markup language," and "ontology." This review will discuss these terms, especially as they pertain to toxicogenomics, how they relate to one-another, and what current efforts exist that may impact toxicology.

Clearing the Standards Landscape: the Semantics of Terminology and their Impact on Toxicogenomics