Big Data Analytics in Internet of Things Environment

Dear Colleagues,

The growth of information technology and increase in the use of smart devices such as sensors, actuators, wearables, and other devices, has produced a massive amount of data. This data is available in various forms such as healthcare, medical records, data warehouses, and many others. This increase of information can yield to research issues and challenges, as extracting useful information becomes a challenging task for research. The useful insights once drawn in a successful way can ultimately be used for different purposes including analysis of data, managing the data, patient care, etc., which will provide effective solutions in the area. Big data is the data that need to be shaped for its volume, size, and shape in order to extract meaningful information for an explicit purpose. Data is ever playing a significant role in organization and industry for daily activities to smoothly function.

Keeping in view the importance of data and to extract significant information, the data need to be shaped in a structured way to mine the information and useful insights for the use of research and practice. Diverse approaches, methods, and mechanisms are in practice to tackle the issues of big data and its analytics. Scientific programming is considered as a key tool and plays a major role in facilitating solutions to the current and future issues that exist in the managing of large-scale data, such as by supporting in the processing of huge data volumes, complex system modelling, and sourcing derivations from data and its simulations. Programming tools, such as Tableau, Apache Hadoop, and Informatica PowerCenter, analyze and manage the data efficiently and allow the visualization of expressive comprehensions extracted from data.

Scientific Programming facilitates research forums for elaborating research results in, and practical experiences with, analyzing, programming tools, programming languages, and experienced models of computation in data science aimed specifically at supporting scientific research in the domain of data science.

This Special Issue invites original research articles and review articles that demonstrate the incorporation of technologies in data science based on scientific programming and its applications in the domain. Studies and research that consider technological and computational barriers to data science management are particularly welcome.

Prof. Iván García-Magariño
Dr. Shah Nazir
Guest Editors

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