• Big Data
    • Architectures, Platforms, Ecosystems
  • Data-Intensive Analytics (Big Data Analytics)
    • Models and Modelling
    • Basic¬†Operations
      • Data Management
      • Data Preparation / Curation
      • Data Analysis
    • Processes / Workflows / Pipelines
    • Data Management Requirements
    • Ecosystems
  • Data Science
    • Principles (theories) and techniques (methods, guidelines, best practices)
    • Large-scale, industrial use cases
    • Workflows/Pipelines
    • Significance (21st Century statistics)
    • Veracity, Tuning, Error Bars
    • Probabilistic Results
  • Big Data, Data-Intensive Analysis Use Cases
    • Scientific Computing
      • Particle Physics, Biology, Astrophysics, …
    • Medical
    • Genomics