This special issue aims to bring together recent research and experience of computer scientists, professionals, industrial practitioners and applied mathematicians working in the area of data analytics applied to engineering, business and scientific domains.
Data analytics is the science of examining raw data with the purpose of drawing conclusions from the information. It integrates theories and methods from computer science and engineering, mathematics, statistics and information science. Data analytics deal with four major areas: nature and quality of the data, information extraction from data, data-intensive computing theory, and managing big data.
The issue will carry revised and substantially extended versions of selected papers presented at the International Conference on Data Science and Engineering 2017, but we also strongly encourage researchers unable to participate in the conference to submit articles for this call.
Suitable topics include, but are not limited, to the following:
- Algorithms for large data sets
- Data-centric programming
- Statistical computing
- Machine learning and computational intelligence
- Big data mining and analytics
- Big data visualisation
- Big data curation and management
- Security, privacy, trust and legal issues for big data
- NoSQL data stores and DB scalability
- Storage and computation management of big data
- Mobility and big data
- Knowledge engineering
- Infoscience and computational informatics
- Web databases and information systems
- Parallel, distributed and cloud-based high-performance data mining
- Opinion mining and sentiment analysis
- High-performance scientific/engineering/commercial applications
Submission of manuscripts: 20 February, 2017
Notification to authors: 30 April, 2017
Final versions due: 30 June, 2017