Data Intensive Study of Accessibility of Edible Species and Healthcare Across the Globe

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  • WATANABE Satoshi
    Graduate School of Information Science, Nara Institute of Science and Technology
  • KYO Hoko
    Department of Complementary and Alternative Medicine Clinical R&D Kanazawa University Graduate School of Medical Science
  • Liu KANG
    Graduate School of Information Science, Nara Institute of Science and Technology
  • EGUCHI Ryohei
    Graduate School of Information Science, Nara Institute of Science and Technology NAIST Data Science Center, Nara Institute of Science and Technology
  • Md. Altaf-Ul-Amin
    Graduate School of Information Science, Nara Institute of Science and Technology
  • MORITA(Hirai) Aki
    Graduate School of Information Science, Nara Institute of Science and Technology
  • OHASHI Minako
    Graduate School of Information Science, Nara Institute of Science and Technology
  • ONO Naoaki
    Graduate School of Information Science, Nara Institute of Science and Technology NAIST Data Science Center, Nara Institute of Science and Technology
  • HUANG Alex Ming
    Graduate School of Information Science, Nara Institute of Science and Technology
  • ZHU Yanbo
    School of Management, Beijing University of Chinese Medicine
  • WANG Qi
    Center for studies in Traditional Chinese Medicine constitution Research and Reproductive Science, Beijing University of Chinese Medicine
  • DAI Zhaoyu
    School of Chinese Medicine, Hong Kong Baptist University
  • NAKAMURA Yukiko
    Institute of Psychology, University of Regensburg
  • Klaus W. LANGE
    Institute of Psychology, University of Regensburg
  • UEBABA Kazuo
    Faculty of human care, Teikyo Heisei University
  • HASHIMOTO Shintaro
    Daimyoumachi Skin Clinic
  • KANAYA Shigehiko
    Graduate School of Information Science, Nara Institute of Science and Technology NAIST Data Science Center, Nara Institute of Science and Technology
  • SUZUKI Nobutaka
    Department of Complementary and Alternative Medicine Clinical R&D Kanazawa University Graduate School of Medical Science

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  • データサイエンスから解明される世界の食用生物の多様性とヘルスケア

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Abstract

Variety of accessibility to edible species in different regions has climatic and historical roots. In the present study, we try to systematically analyze 28,064 records of relationships between 11,752 edible species and 228 geographic zones by hierarchical clustering. The 228 geographic regions were classified into 11 super groups named as A to K, which were further divided into 39 clusters (CLs). Of them, at least one member of each of 28 CLs is associated to 20 or more edible species according to present information of KNApSAcK DB (http://kanaya.naist.jp/KNApSAcK_World/top.jsp). We examined those 28 CLs and found that majority of the members of each of the 27 CLs (96%) have specific type of climate. Diversity of accessibility to edible species makes it possible to separate 8 geographic regions on continental landmasses namely Mediterraneum, Baltic Sea, Western Europe, Yucatan Peninsula, South America, Africa and Arabian Peninsula, Southeast Asia, and Arctic Ocean; and three archipelagos namely, Caribbean Islands, Southeast Asian Islands and Pacific Islands. In addition, we also examined clusters based on cultural exchanges by colonization and migration and mass movement of people and material by modern transportation and trades as well as biogeographic factors. The era of big data science or data intensive science make it possible to systematically understand the content in huge data and how to acquire suitable data for specific purposes. Human healthcare should be considered on the basis of culture, climate, accessibility of edible foods and preferences, and based on molecular level information of genome and digestive systems.

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