DSS 2018 - 4th IEEE International Conference on Data Science and Systems (DSS-2018)

Welcome Message
In parallel with Petrol as a driving resource in this world, Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Gradually and steadily, it is being world-wide recognized that data and talents are playing key roles in modern businesses.
As an interdisciplinary area, Data Science draws scientific inquiry from a broad range of subject areas such as statistics, mathematics, computer science, machine learning, optimization, signal processing, information retrieval, databases, cloud computing, computer vision, natural language processing, etc. Data Science is on the essence of deriving valuable insights from data. It is emerging to meet the challenges of processing very large datasets, i.e. Big Data, with the explosion of new data continuously generated from various channels, such as smart devices, web, mobile and social media.
Data Systems are posing many challenges in exploiting parallelism of current and upcoming computer architectures. Data volumes of applications in the fields of sciences and engineering, finance, media, online information resources, etc. are expected to double every two years over the next decade and further. With this continuing data explosion, it is necessary to store and process data efficiently by utilizing enormous computing power. The importance of data intensive systems has been raising and will continue to be the foremost fields of research. This raise brings up many research issues, in forms of capturing and accessing data effectively and fast, processing it while still achieving high performance and high throughput, and storing it efficiently for future use. Innovative programming models, high performance scalable computing platforms, efficient storage systems and expression of data requirements are at immediate need.
DSS (Data Science and Systems) was created to provide a prime international forum for researchers, industry practitioners and domain experts to exchange the latest advances in Data Science and Data Systems as well as their synergy. 2018 is the 4th event following the success in 2015 (DSDIS-2015), 2016 (DSS-2016), and 2017 (DSS-2017).
DSS-2018 will be hosted in Exeter, the capital city of Devon and provides the county with a central base for education, medicine, religion, commerce and culture. The city is also home to the magnificent Exeter Cathedral, which dates back to Norman times. Exeter is also ideally placed to base a trip to branch out visiting places such as the famous Dartmoor National Park and the unspoilt beaches of the North and South Devon coastlines.
Prospective authors are invited to submit their papers to DSS-2018. All accepted papers are expected to be included in IEEE Xplore and will be indexed by Engineering Index (EI). The authors of selected best papers will be invited post conference to extend their contributions for special issues of prestigious journals to be planned in conjunction with the conference.
Scope and Topics
Scope and Topics:
Topics of interest include, but are not limited to:
I. Data Science
Foundational theories and models of data science
Foundational algorithms and methods for big data
Data classification and taxonomy
Data metrics and metrology
Machine learning and deep learning
Data analytics
Data provenance
Fault tolerance, reliability, and availability
Security, privacy and trust in Data
II. Data Processing Technology
Data sensing, fusion and mining
Data representation, dimensionality reduction, processing and proactive service layers
Data capturing, management, and scheduling techniques
Stream data processing and integration
Knowledge discovery from multiple information sources
Statistical, mathematical and probabilistic modeling and theories
Information visualization and visual data analytics
Information retrieval and personalized recommendation
Parallel and distributed data storage and processing infrastructure
MapReduce, Hadoop, Spark, scalable computing and storage platforms
Security, privacy and data integrity in data sharing, publishing and analysis
Replication, archiving, preservation strategies
Stream data computing
Meta-data management
Remote data access
III. Data Systems
Storage and file systems
High performance data access toolkits
Programming models, abstractions for data intensive computing
Compiler and runtime support
Future research challenges of data intensive systems
Real-time data intensive systems
Network support for data intensive systems
Challenges and solutions in the era of multi/many-core platforms
Green (power efficient) data intensive systems
Data intensive computing on accelerators and GPUs
Productivity tools, performance measuring and benchmark for data intensive systems
Big Data, cloud computing and data intensive systems
IV. Data Applications
HPC system architecture, programming models and run-time systems for data intensive applications
Innovative applications in business, finance, industry and government cases
Data-intensive applications and their challenges
Innovative data intensive applications such as health, energy, cybersecurity, transport, food, soil and water, resources, advanced manufacturing, environmental Change, and etc.