Call for Papers

Big data has become a key asset in modern societies, economies, and governmental organizations. Big data encompasses various kinds of complex and large scale information that are beyond the processing capabilities of conventional software and databases. The increasing volume and velocity of the data, captured by business organizations, web repositories, social media, data centres, cloud and IoT, have resulted in the exponential growth of big data.

Big data provides a key basis for innovations in various domains and applications. It can benefit data managers, developers, companies and various kinds of organizations to carry out useful analysis of data pattern and trends, make intelligent decisions, and solve complex problems that can help societies and economies and speed up innovations.

The aim of the Innovate-Data conference is to promote the state of the art in scientific and practical research of big data and to bring together researchers and practitioners from academia, industry, and public sector in an effort to present their research work and share research and development ideas.

CONFERENCE TOPICS:

Big Data Storage, Representation and Processing
Data storage; Data representation and structures; Data management; Data processing; Data engineering and design; Storages and network requirements

Big Data Security, Privacy and Trust
Data Security; Data Privacy; Data Trust; Data protection and integrity; Legal and ethical issues; Identity theft; Data loss and leakage

Big Data Models, Infrastructure and Platforms
Data models; NoSQL databases; Data consistency and availability; Fault tolerance and reliability; Network models and protocols; Performance evaluation; Resource management; Transaction management; RDBMS and big data; Memcached systems and techniques

Visualisation of Big Data
Data visualisation, Visual representation; Usability and user interaction; Graphs models and techniques for big data; Data acquisition and cleaning

Big Data Analytics and Metrics
Analytics models; Tools and technologies; Data patterns; Business intelligence and decision making; Optimization of resources and cost; Customer relations and satisfaction; Data economics; Metrics for big data; Analysis of online reviews

Big Data Science
Big data science models; Data searching and mining; Methodologies and use cases; Machine learning and deep learning; Algorithms and formal models; Mathematical and Statistical models for big data; Interdisciplinary approaches and methods

Big Data Applications and Innovations
Business applications; Social media and networks; Healthcare applications; Government and public sector systems; Multimedia and data streaming; Personal data logging and quantified-self; Context-aware data; Big data in cloud and IoT; Personalisation of data; Open and linked data