scholarly journals Big Data, Data Science and Emerging Analytic tools : Impact in social science

2019 ◽  
Author(s):  
Satabdi Saha ◽  
Tapabrata Maiti
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Social Science ◽  
Data Analytics ◽  
Data Science ◽  
Social Science Research ◽  
Big Data Analytics ◽  
Science Research ◽  
Data Sources ◽  
The Internet

Rapid advancement of the Internet and Internet of Things have led to companies generating gigantic volumes of data in every field of business. Big data research has thus become one of the most prominent topic of discussion garnering simultaneous attention from academia and industry. This paper attempts to understand the significance of big data in current scientific research and outline its unique characteristics, otherwise unavailable from traditional data sources. We focus on how big data has altered the scope and dimension of data science thus making it severely interdisciplinary. We further discuss the significance and opportunities of big data in the domain of social science research with a scrutiny of the challenges previously faced while using smaller datasets. Given the extensive utilization of big data analytics in all forms of socio-technical research, we argue the need to critically interrogate its assumptions and biases; thereby advocating the need for creating a just and ethical big data world.

Big Data Analytics in Bioinformatics

Biotechnology ◽  
2019 ◽  
pp. 1967-1984
Author(s):  
Dharmendra Trikamlal Patel
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Annual Growth ◽  
Predictive Analysis ◽  
The Internet ◽  
Data Generation ◽  
Intelligent Devices ◽  
The Internet Of Things

Voluminous data are being generated by various means. The Internet of Things (IoT) has emerged recently to group all manmade artificial things around us. Due to intelligent devices, the annual growth of data generation has increased rapidly, and it is expected that by 2020, it will reach more than 40 trillion GB. Data generated through devices are in unstructured form. Traditional techniques of descriptive and predictive analysis are not enough for that. Big Data Analytics have emerged to perform descriptive and predictive analysis on such voluminous data. This chapter first deals with the introduction to Big Data Analytics. Big Data Analytics is very essential in Bioinformatics field as the size of human genome sometimes reaches 200 GB. The chapter next deals with different types of big data in Bioinformatics. The chapter describes several problems and challenges based on big data in Bioinformatics. Finally, the chapter deals with techniques of Big Data Analytics in the Bioinformatics field.

Big Data Analytics in Bioinformatics

2018 ◽  
pp. 321-338
Author(s):  
Dharmendra Trikamlal Patel
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Annual Growth ◽  
Predictive Analysis ◽  
The Internet ◽  
Data Generation ◽  
Intelligent Devices ◽  
The Internet Of Things

Voluminous data are being generated by various means. The Internet of Things (IoT) has emerged recently to group all manmade artificial things around us. Due to intelligent devices, the annual growth of data generation has increased rapidly, and it is expected that by 2020, it will reach more than 40 trillion GB. Data generated through devices are in unstructured form. Traditional techniques of descriptive and predictive analysis are not enough for that. Big Data Analytics have emerged to perform descriptive and predictive analysis on such voluminous data. This chapter first deals with the introduction to Big Data Analytics. Big Data Analytics is very essential in Bioinformatics field as the size of human genome sometimes reaches 200 GB. The chapter next deals with different types of big data in Bioinformatics. The chapter describes several problems and challenges based on big data in Bioinformatics. Finally, the chapter deals with techniques of Big Data Analytics in the Bioinformatics field.

scholarly journals Big Data for Surveillance in Mobility Sector: Application and Opportunities

2020 ◽  
Vol 9 (8) ◽  
pp. 685-687
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Data Science ◽  
Scale Up ◽  
Big Data Analytics ◽  
Road Transport ◽  
Rapid Pace ◽  
Toll Plaza ◽  
Centralized System

Everyday technologies are evolving with rapid pace. Domain relevant innovations are the driving force in achieving new milestones in different technical sector. This paper resolves issues related to surveillance of Road Transport and Mobility Sector. There are a couple of domains which are marking their concrete existence in almost every field, like Big Data and Internet of Things (IoT). Big Data is an integral part of Data Science which deals with massive amount of data. When we talk about collecting data, there is no big source than internet. Internet of Things (IoT) plays a credible role in information generation from different locations using different devices and collecting the raw data to a centralized location, where the pennies will add up to a dollar, i.e. the small amount of data from different location when collected at one place will add up to the pool of data, which scale up from terabytes to 10s of petabytes, and thus we term it as Big Data. Road Transport and surveillance sector has a wide variety of problems, ranging from illegal breaching of vehicles without paying Toll taxes at Toll Plaza, to Violation of Traffic Signal law. All these problems can be eradicated by making use of hot technologies which uses a centralized system to handle these issues effectively and efficiently, Big Data is one such Technology. Big Data Analytics can help in optimizing operating procedure at such places.

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