Conference Information
DSS 2018 : IEEE International Conference on Data Science and Systems
http://cse.stfx.ca/~dss2018/
Submission Date:
2018-03-23 Extended
Notification Date:
2018-04-15
Conference Date:
2018-06-28
Location:
Exeter, UK
Years:
4
Viewed: 2851   Tracked: 8   Attend: 0

Conference Location
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Call For Papers
INTRODUCTION

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. 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.

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.

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.
Last updated by Dou Sun in 2018-02-12
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