Ontologies and standards in bioscience research: for machine or for human

Abstract

Ontologies and standards are very important parts of today's bioscience research. With the rapid increase of biological knowledge, they provide mechanisms to better store and represent data in a controlled and structured way, so that scientists can share the data, and utilize a wide variety of software and tools to manage and analyze the data. Most of these standards are initially designed for computers to access large amounts of data that are difficult for human biologists to handle, and it is important to keep in mind that ultimately biologists are going to produce and interpret the data. While ontologies and standards must follow strict semantic rules that may not be familiar to biologists, effort must be spent to lower the learning barrier by involving biologists in the process of development, and by providing software and tool support. A standard will not succeed without support from the wider bioscience research community. Thus, it is crucial that these standards be designed not only for machines to read, but also to be scientifically accurate and intuitive to human biologists.

Keywords: ontology; standard; systems biology.

Figure 1

Biomedical research workflow. Human involvement is essential at each of the steps illustrated in this schematic diagram, while computer software and tools will greatly facilitate the process by better storing, representing, and analyzing the data. Thus, it is crucial to include ontologies and standards at each of these steps for unambiguous interpretation of data by both human and computers.