Data Science Standards Committee

The Data Science Association Data Science Standards Committee is seeking members to join us in developing and setting standards for the professional practice of data science.

If you would like to join email Committee Chair  Michael Walker ( or contact us here.

Included are data science process and ethical standards. See Data Science Code of Professional Conduct.

Data science standards need to be developed for the following specialty domains:

  • Algorithm design and execution
  • Artificial intelligence
  • Big data cloud, mining and management
  • Big data storage, processing, sharing and visualisation
  • Big data systems, tools, theory and applications
  • Business analytics, intelligence and mathematics
  • Computer science, hacking skills
  • Data mining
  • Deep learning
  • Informatics and information systems and technology
  • Machine learning, web-based decision making
  • Management science, social sciences and statistics
  • Mathematical optimisation and mathematics of decision sciences
  • Multiple source data processing and integration
  • Natural language processing
  • Network and social-graph analysis
  • Neural networks
  • Optimisation, performance measurement
  • Security and privacy
  • System analysis and theory
  • Volume, velocity and variety of big data on cloud