Biology and medicine are experiencing a nexus, where historical models of ?small science,? which served the academic community so well throughout the 20th century, can no longer scale. We are in an era of profound data, information, and knowledge explosion, most of which is pertinent to most research. While following, managing, and engaging this knowledge is challenging enough, integrating this proliferation into ongoing research poses challenges literally beyond human comprehension. We are in an era where machine-assisted data integration in cutting-edge biomedical discovery is not only desirable; it is becoming increasingly the only plausible way in which such research can be effectively conducted. Major team-based collaborations throughout NIH and HHS institutes in which the PI has been involved, such as caBIG, SHARP, BISTI, BD2K, eMERGE, CSER, IGNITE, Data Commons, and NCATS Translator, all recognized dependence on the comparable and consistent rendering of data, information, and knowledge to facilitate machine-assisted integration. Thus, terminologies and ontologies have become the crucial building blocks for large-scale data integration. In short, modern biomedical science cannot scale without leveraging well-formed ontological resources. These resources are now the major underpinning requirement for biomedical science in the 21st century. The world is awash in scholarly efforts about biomedical topics, predominantly in peer-reviewed periodical literature. Historically, textbooks have played the crucial role of synthesis and condensation. Regrettably, all too many such scholarly efforts languish in the metaphorical remainder bins of overpriced and inaccessible resources. The advent of open-access periodical production has broadened access to scholarly work to greater audiences. It is only recently that the same principle is being brought to synthetic monographs containing a coherent series of concise reviews. Given the crucial nature of ontology and terminology in biomedical science, it is time to consider an open-access monograph on these topics. The modular nature of such an effort will support periodic editing and updates. This proposal seeks funding to purchase open-access rights for a Springer monograph to be entitled Biomedical Terminologies: The Foundation for Biomedical Data Science A comprehensive review of biomedical terminologies, ontologies, and classifications
Biology and medicine are becoming more complex and require that scientists use terminologies and classifications to help them organize the global growth of data. We propose to author an open access book that describes terminologies and classifications, and use the grant funding to make the book available to everyone for free
