Implicit JSON Schema Versioning Driven by Big Data Evolution in the τJSchema Framework

Author(s):  
Zouhaier Brahmia ◽  
Safa Brahmia ◽  
Fabio Grandi ◽  
Rafik Bouaziz
Author(s):  
Artem A. Balyakin ◽  
Marina V. Nurbina ◽  
Sergey B. Taranenko
Keyword(s):  
Big Data ◽  

2019 ◽  
Vol 40 (25) ◽  
pp. 1995-1996 ◽  
Author(s):  
Lee Kamlet
Keyword(s):  
Big Data ◽  

2018 ◽  
Vol 45 (3) ◽  
pp. 322-340 ◽  
Author(s):  
Deepak Gupta ◽  
Rinkle Rani

The world is already into the information age. The huge growth of digital data has overwhelmed the traditional systems and approaches. Big data is touching almost all aspects of our life and the data-driven discovery approach is an emerging paradigm for computing. The ever-growing data provides a tidal wave of opportunities and challenges in terms of data capture, storage, manipulation, management, analysis, knowledge extraction, security, privacy and visualisation. Though the promise of big data seems to be genuine, still a wide gap exists between its potential and realisation. In last few years, there is a huge surge in research efforts in academia as well as industry to have a better understanding of big data. This article discusses the following: (1) big data evolution including a bibliometric study of academic and industry publications pertaining to big data during the period 2000–2017, (2) popular open-source big data stream processing frameworks and (3) prevalent research challenges which must be addressed to realise the true potential of big data.


2019 ◽  
Vol 107 (12) ◽  
pp. 2294-2301 ◽  
Author(s):  
Bing Zhang ◽  
Zhengchao Chen ◽  
Dailiang Peng ◽  
Jon Atli Benediktsson ◽  
Bo Liu ◽  
...  

2016 ◽  
Vol 44 (7-8) ◽  
pp. 375-376 ◽  
Author(s):  
C. Mathelin ◽  
K. Neuberger ◽  
I. Ibnouhsein

2016 ◽  
Vol 22 (1) ◽  
pp. 34-39
Author(s):  
Andreas Schmid
Keyword(s):  
Big Data ◽  

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