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 and 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 raised 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.

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For all regular full papers, authors need to prepare an oral presentation. And for full papers, authors need to prepare a poster to show their work. Posters need to be printed and brought to the venue.

Presentation requirements:

Please make sure that your presentation file follows these guidelines:

Poster requirements:

Please make sure that your poster follows these guidelines:

Topics of 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
• Social 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 Retrieval
• 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

The materials presented in the papers should not be published or under submission elsewhere. Each paper is limited to 8 pages (or 12 pages with over length charge) including figures and references using IEEE Computer Society Proceedings Manuscripts style (two columns, single-spaced, 10 fonts). The review process of DSS 2024 is single-blind. All papers need to be submitted electronically through the conference submission website with PDF format:(https://edas.info/N32667)

Accepted conference papers will be published by IEEE (IEEE-DL and El indexed). At least one author of each accepted paper is required to register and present their work at the conference; otherwise the paper will not be included in the proceedings. Selected papers, after further extensions and revisions, will be recommended to special issues.