داشبورد علم داده جمعیتی؛ چیستی، چرایی و چگونگی

نوع مقاله : مقاله پژوهشی با اصالت

نویسنده

استادیار، دانشکده پیامبر اعظم (ص)، دانشگاه جامع امام حسین (ع)، تهران، ایران.

چکیده

استفاده از داده‌هایی که جمعیت‌های انسانی را پوشش می‌دهند به طور فزاینده‌ای برای تحقیق و تصمیم‌گیری در حال افزایش است. با این حال، پرداختن به این داده‌ها بصورت علمی، که مشخصه اختصاصی جمعیت را در تفاوت با سایر انواع داده‌ها دارند، موضوعی است که در عصر علم داده و کلان‌داده، بصورت تخصصی کماکان مغفول مانده است. علم داده‌های جمعیتی بصورت میان رشته‌ای از تجمیع علم داده و علم جمعیت با نگاه تخصصی به داده‌های جمعیتی قابل طرح است. از آنجاییکه پتانسیل کامل داده‌های جمعیت اغلب تنها زمانی قابل دستیابی است که چنین داده‌هایی به پایگاه‌های داده دیگر مرتبط شوند، نگاه کلی‌نگر و اساسی به موضوع علم داده‌های جمعیتی یکی از ملزومات اساسی در حوزه جمعیت است. در این مقاله تلاش شده است تا با بیان چیستی و چرایی این علم، چگونگی پیاده‌سازی معماری مفهومی مبتنی بر کلان‌داده و رایانش ابری با تکیه بر دانش روز حوزه علم داده در قالب مدل پیشنهادی داشبورد مدیریتی علم داده جمعیتی نشان داده شود.

کلیدواژه‌ها


عنوان مقاله [English]

Population Data Science Dashboard; What, Why and How

نویسنده [English]

  • Yaser Khorrami
Assistant Professor, Faculty of the Great Prophet, Imam Hossein University, Tehran, Iran.
چکیده [English]

The use of data covering human populations is increasingly used for research and decision-making. However, dealing with these data in a scientific manner, which has the specific characteristics of the population in contrast to other types of data, is a subject that has been neglected in the age of data science and big data. Population data science can be designed as an interdisciplinary form of combining data science and population science with a specialized view of population data. Since the full potential of population data can often only be achieved when such data are linked to other databases, a comprehensive and basic look at the subject of population data science is one of the basic requirements in the field of population. In this article, it has tried to show what and why this science is, how to implement the conceptual architecture based on big data and cloud computing, relying on the current knowledge of the field of data science in the form of a proposed management dashboard model of population data science.

کلیدواژه‌ها [English]

  • Population data
  • Cloud computing
  • Population data science
  • Data science
  • Big data
  • Management dashboard model

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