The International Conference on RDAAPS is an annual forum on research in the broadly defined area of data analytics. RDAAPS brings together researchers from academia, industry, and public sector to present and discuss various aspects of data analytics, including privacy, security, and automation. This venue is meant to bring together stakeholders whose interests lie at the interface of these concerns, providing a platform for integrating the needs of industry with the state-of-the-art scientific advancements, and inspiring original research on solving enterprise data challenges. RDAAPS seeks papers presenting original research in the areas included, but are not limited to:
Big Data Analytics for Decision Making
* New models and algorithms for data analytics
* Scalable data analytics
* Optimization methods in data analytics
* Theoretical analysis of data systems
* Analytical reasoning systems
* Decision making under uncertainty
* Learning systems for data analytics
* Large-scale text, speech, image, or graph processing systems
Accountable Data Analytics
* Privacy-aware data analytics
* Fairness in data analytics
* Interpretable and transparent data analytics
* Incorporating legal and ethical factors into data analytics
Strings in Data Analytics
* Patterns in Big Data
* Data compression
* Algorithms and data structures for string processing
* Useful data structures for Big Data
* Data structures on secondary storage
Security in Data Analysis
* Traceability of decision making
* Models for forecasting cyber-attacks and measuring impact
* Data usage in mounting security threats
* Data analytics for better situational awareness
Domain knowledge modeling and generation
* Novel ontology representations
* Scalability of domain-based reasoning on big data
* Modeling and analyzing unstructured data sets
Automation for data analytics, security, and privacy in manufacturing
* Application of data analysis in manufacturing
* Big data in Industry 4.0
* Privacy and security in manufacturing
Challenges of automation of data analytic processes
* Case studies of the automation of data analytics processes
* Architecture for data analytics and security
* Built-in privacy and security in data analytics automation
Successful papers will address real research challenges through analysis, design, measurement, and deployment of data systems. The program committee will evaluate each paper using metrics that are appropriate for the topic area. All submissions must describe original ideas, not published or currently under review for another conference or journal.
Submitted papers can include up to 8 pages (following the IEEE Guidelines), including references, appendices, and figures. All accepted papers will be published in IEEE conference proceedings. Submissions are to be through EasyChair.
Abstract submission will be due December 14th, 2020.
Paper submission will be due on December 21st, 2020.
Notification will be sent by February 22nd, 2021.
Camera ready paper will be due on March 15th, 2021.