Aims and Scopes

World Conference on Big Data aims to bring together academicians, researchers, engineers, system analysts, software developers, graduate and undergraduate students with government and non-government organizations to share and discuss both theoretical and practical knowledge about  cloud computing turning computing and software into commodity services, everything as a service in other words, it leads to not only a technology revolution but also a business revolution. Insights and impacts of various types of services (infrastructure as a service, platform as a service, software as a service, and business process as a service) have to be re-examined.

The scope of the conference includes, but is not limited to; the following major topics;

• ALGORITHMS FOR BIG DATA:
  – Data and Information Fusion
  – Genetic Algorithms
  – Machine Learning
  – Natural Language Processing
  – Signal Processing
  – Scalable Algorithms
  – Simulation and Modeling
  – Data-Intensive Computing
  – Parallel Algorithms (including the map-reduce paradigm)
  – Testing Methods
  – Dimensionality Reduction Techniques
  – Multidimensional Big Data
  – Multilinear Subspace Learning
  – Sampling Methodologies
  – Streaming
• BIG DATA FUNDAMENTALS:
  – Novel Computational Methodologies
  – Algorithms for Enhancing Data Quality
  – Models and Frameworks for Big Data
  – Graph Algorithms and Big Data
  – Computational Science
  – Computational Intelligence
• INFRASTRUCTURES FOR BIG DATA:
  – Cloud Based Infrastructures (applications, storage & computing resources)
  – Grid and Stream Computing for Big Data
  – High Performance Computing, Including Parallel & Distributed
  Processing – Autonomic Computing
  – Cyber-infrastructures and System Architectures
  – Programming Models and Environments to Support Big Data
  – Software and Tools for Big Data
  – Big Data Open Platforms
  – Emerging Architectural Frameworks for Big Data
  – Paradigms and Models for Big Data beyond Hadoop/MapReduce, …
• BIG DATA MANAGEMENT AND FRAMEWORKS:
  – Database and Web Applications
  – Federated Database Systems
  – Distributed Database Systems
  – Distributed File Systems
  – Distributed Storage Systems
  – Knowledge Management and Engineering
  – Massively Parallel Processing (MPP) Databases
  – Novel Data Models
  – Data Preservation and Provenance
  – Data Protection Methods
  – Data Integrity and Privacy Standards and Policies
  – Data Fusion and Integration
  – Data Science
  – Novel Data Management Methods
  – Crowdsourcing
  – Stream Data Management
  – Scientific Data Management
• BIG DATA SEARCH & MINING METHODS:
  – Multimedia and Big Data
  – Data Mining
  – Social Networks
  – Data Science
  – Web Search and Information Mining
  – Scalable Search Architectures
  – Cleaning Big Data (noise reduction), Acquisition & Integration
  – Visualization Methods for Search
  – Time Series Analysis
  – Recommendation Systems
  – Graph Mining and Other Similar Technologies
• SECURITY & PRIVACY IN THE ERA OF BIG DATA:
  – Cryptography
  – Threat Detection Using Big Data Analytics
  – Privacy Threats of Big Data
  – Privacy Preserving Big Data Collection
  – Intrusion Detection
  – Socio-economical Aspect of Big Data in the Context of Privacy and Security
• APPLICATIONS OF BIG DATA:
  – Big Data as a Service
  – Big Data Analytics in e-Government and Society
  – Applications in Science, Engineering, Healthcare, Visualization, Business, Education, Security, Humanities, Bioinformatics, Health Informatics, Medicine, Finance, Law, Transportation, Retailing, Telecommunication, all Search-based applications, …