Today, Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. It involves many domains, such as signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, etc. High Performance Computing typically deals with smaller, highly structured data sets and huge amounts of computation. Data Science has emerged to tackle the problem of creating processes and approaches to extracting knowledge or insights from gigantic, unstructured data sets.
The 2nd International Workshop for Data Science and Computing (DSC'17) aims to provide a forum that brings together researchers, industry practitioners and domain experts for discussion and exchange of ideas on the latest theoretical developments in Data Science and Computing as well as on the best practices for a wide range of applications.
Topics of Interests
General areas of interest to DSC'2017 include but are not limited to:
1. Architecture, management and process for data science
2. Cloud computing and service data analysis
3. Data warehouses, cloud architectures
4. Mathematical Issues in Data Science
5. Big Data Issues and Applications
6. Large-scale databases
7. High performance computing for data analytics
8. Large scale optimization
9. Data-driven Scientific Research
10. Security, trust and risk in big data
11. Privacy and protection standards and policies
12. Data Quality
13. Evaluation and Measurement in Data Science
14. Big Data Mining and Knowledge Management
15. Case Study of Data Science