عناصر مشابهة
Big Data in Academic Libraries: Literature Review and Future Direction
| المصدر: | المؤتمر الرابع والعشرون: البيانات الضخمة وآفاق استثمارها: الطريق نحو التكامل المعرفي |
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| الناشر: |
جمعية المكتبات المتخصصة فرع الخليج العربي
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| المؤلف الرئيسي: | |
| مؤلفين آخرين: | |
| محكمة: | نعم |
| الدولة: | سلطنة عمان |
| التاريخ الميلادي: | 2018 |
| الصفحات: | 1 - 19 |
| رقم MD: | 870301 |
| نوع المحتوى: | بحوث المؤتمرات |
| اللغة: | English |
| قواعد المعلومات: | HumanIndex |
| مواضيع: | |
| رابط المحتوى: |
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| المستخلص: | Big Data in academic libraries has drawn substantial attention in recent years. Current researches on Big Data in academic libraries are highly interdisciplinary involving methodologies from different areas of science. However, Big Data analytics in academic libraries suffers from two fundamental challenges: owing to the huge volume, variety and velocity of data and the complexity of techniques and algorithms. The aim of this paper is to explore which Big Data analyzing techniques and tools can be applied in academic libraries; and moreover, to discover the benefits of Big Data in academic libraries. Besides, how to involved librarians in Big Data? What are the gaps in Big Data studies related to academic libraries? What are the Big Data research trends of the future? To provide a better understanding of the benefits of Big Data in academic libraries and their future trends, a systematic and comprehensive literature search of the published research papers from the past 7 years of Big Data research of academic libraries was conducted, and the resulting (37) literature papers were reviewed and analysed. The results have shown that despite the large amount of research conducted on the Big Data topic, few studies discussed the application of Big Data in academic libraries, including the analysing techniques and tools. The benefits of Big Data in academic libraries and its implications on methodology in future studies are discussed. The current research also sheds some light on the evolving field of Big Data research in academic libraries. |
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