Paper submission due: September 15, 2023 (HST, Firm)

Author notification: October 15, 2023
Camera Ready due: October 30, 2023

Registration due: October 30, 2023
 

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.

Scope and Topics

Topics of particular interest include, but are not limited to:

 

I. Data Science

- Foundational Theories of Data Science
- Data Classification and Taxonomy
- Data Metrics and Metrology
- Data Analytics
- Complex Network Analysis and Mining
- Security, Privacy and Trust in Data

II. Data Processing Technology

- Data Representation and Processing
- Machine Learning and Deep Learning
- Graph Neural Networks
- Semi-supervised and Unsupervised Learning
- Statistical, Mathematical and Probabilistic Modeling and Theories
- Information visualization
- Data Visualization

III. Data Systems

- Storage and File Systems
- High Performance Access Toolkits
- Compiler and Runtime Support
- Real-time Data Intensive Systems
- Multi/Many-Core Platforms
- Big Data and Cloud Computing

IV. Data Applications

- Business and Finance Applications
- Industrial Data Applications
- Bioinformatics Applications
- Healthcare and Medical Services
- Applications in Soil and Water
- HPC Systems for Data Applications
- Future Data Applications
   
Submission Guidelines

Submissions must include an abstract, keywords, the e-mail address of the corresponding author and should not exceed 8 pages for main conference, including tables and figures in IEEE CS format. The template files for LATEX or WORD can be downloaded here. All paper submissions must represent original and unpublished work. Each submission will be peer reviewed by at least three program committee members. Submission of a paper should be regarded as an undertaking that, should the paper be accepted, at least one of the authors will register for the conference and present the work. Submit your paper(s) in PDF file at the submission site: http://www.swinflow.org/confs/2023/dss/submission.htm.

Publications

Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements. Authors of accepted papers, or at least one of them, are requested to register and present their work at the conference, otherwise their papers may be removed from the digital libraries of IEEE CS after the conference.

Accepted and presented papers will be included into the symposium proceedings. Distinguished papers presented at the conference, after further revision, will be published in special issues of selected journals.