A view on big data and its relation to Informetrics

作     者：Ronald ROUSSEAU 

作者机构：Information and Library ScienceUniversiteit AntwerpenB-2000 AntwerpenBelgium Faculty of Engineering TechnologyKHBO (Association KU Leuven)B-8400 OostendeBelgium Department of MathematicsKU LeuvenB-3000 Leuven (Heverlee)Belgium 

出 版 物：《Chinese Journal of Library and Information Science》 (中国文献情报（英文版）)

年 卷 期：2012年第5卷第3期

页      面：12-26页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

主　　题：Big data CAP theorem Knowledge representation Data mining Ethical concerns 

摘      要：Purpose: Big data offer a huge challenge. Their very existence leads to the contradiction that the more data we have the less accessible they become,as the particular piece of information one is searching for may be buried among terabytes of other data. In this contribution we discuss the origin of big data and point to three challenges when big data arise: Data storage,data processing and generating ***/methodology/approach: Computer-related challenges can be expressed by the CAP theorem which states that it is only possible to simultaneously provide any two of the three following properties in distributed applications: Consistency(C),availability(A) and partition tolerance(P). As an aside we mention Amdahl s law and its application for scientific collaboration. We further discuss data mining in large databases and knowledge representation for handling the results of data mining exercises. We further offer a short informetric study of the field of big data,and point to the ethical dimension of the big data ***: There still are serious problems to overcome before the field of big data can deliver on its *** and limitations: This contribution offers a personal view,focusing on the information science aspects,but much more can be said about software ***/value: We express the hope that the information scientists,including librarians,will be able to play their full role within the knowledge discovery,data mining and big data communities,leading to exciting developments,the reduction of scientific bottlenecks and really innovative applications.