Dear Colleagues,

In the digital age, data is the main source of information. If this information is handled correctly, it helps authorities make efficient inferences and apply them successfully. �Data Science� is recently recognized as an interdisciplinary field covering Mathematics, Computer Science, Statistics, Engineering and practically all technological disciplines by using data mining, data-bases, knowledge management, virtualization, high-performance and cloud computing to discover useful information from structured or unstructured data. �Data science� uses scientific algorithms, methods, systems, and processes to predict important information from large, structured or unstructured data, and focuses on applying knowledge learned from that data. Mathematics is very important in data science as mathematical concepts aid in identifying patterns and assists in creating algorithms. �Computational Mathematics� is the mathematics behind computations, especially computer algebra and algorithms. As it continues to advance the computational capabilities of modern computers, it also investigates the limit of what math-based computers can achieve and prove. In terms of data science, computational mathematics contributes to mathematical understanding of structured or unstructured data.

The main objective of this section is to play a leading role in establishing �Data Science� as an important discipline within "Computational Mathematics". However, considering its interdisciplinary structure and potential impact to scientific and technological development in almost all fields, the goal of the section is to publish research articles/reviews supporting the theoretical and algorithmic advancement of �Data Science� based on computational analysis. �Mathematics of Computation and

Data Science� provides an opportunity for the interaction among mathematicians, including computer scientists, statisticians and other scientists interested in the computational aspects of data science in branches such as natural science, formal science and life science.

It is important to collect the experiences of "Mathematics of Computation and Data Science". Seminal research articles and reviews in this area of study are welcome.

We look forward to receiving your contributions.

Dr. H�seyin Kamac?

Section Editor

Cloud Computing; Computational Mathematics; Data Analysis; Decision Science; Image Processing; Knowledge Management; Machine Learning; Linear Algebra; Numerical Analysis; Computational Complexity; Data Visualization.