The Ontology of Biological and Clinical Statistics (OBCS) for standardized and reproducible statistical analysis.

Journal: Journal of biomedical semantics
Published Date: Sep 14, 2016

Abstract

BACKGROUND: Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem.

Authors

  • Jie Zheng
    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China.
  • Marcelline R Harris
    Division of Systems Leadership and Effectiveness Science, University of Michigan School of Nursing, Ann Arbor, MI, 48109, USA.
  • Anna Maria Masci
    Department of Immunology, Duke University, Durham, North Carolina, United States of America.
  • Yu Lin
    Research School of Computer Science, Australian National University, Canberra, 2601, ACT, Australia.
  • Alfred Hero
    Department of Electrical Engineering and Computer Science, Department of Biomedical Engineering, and Department of Statistics, Michigan Institute of Data Science, University of Michigan, Ann Arbor, MI, 48109, USA.
  • Barry Smith
    Department of Philosophy, University at Buffalo, NY, USA.
  • Yongqun He
    University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, and Comprehensive Cancer Center, University of Michigan Medical School, 1301 MSRB III, 1150 W. Medical Dr., Ann Arbor, MI 48109 USA.

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