The Azimuth Project
Azimuth Data Project (changes)

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Eventually, The we aspire to “give back” to the scientific and educational community, by:Azimuth Data Project is a collaboration to develop expertise in data sets for the Earth sciences, and in the surrounding areas of data engineering and the mathematics of data.

• Enhancing the value of existing datasets through further processing

• Contributing to the development of open-source data storage, access and analysis platforms

• Publishing selected datasets of educational interest

Like the Azimuth Code Project , this is an “umbrella” project – a loose framework within in which people can initiate specific projects projects. that interest them.

The data project can is be complementary symbiotic to with the code project. It can may provide generate goals needs for software to development, be developed by the code project. And it can provide data to be used inpute as to input for software models and simulators.

If you would like to participate, we need you! Leave a comment on (this thread) at theAzimuth Forum.

Areas

• Existing Understanding scientific data datasets sets for the Earth sciences

• Data methodology

• Ontologies Data engineering

  • Data representation technologies
  • Algorithms for data representation and transformation
  • Big Data technology

• Data engineering

  • Data representation technologies
  • Algorithms for data representation and transformation
  • Technology for Big Data

• Dataset production

• Mathematical Data foundations theory of data

  • Foundations Algebra in of relational data algebra, universal algebra, category theory, etc.
  • Categories, relations
  • Foundations of empirical data – probability, statistics, stochastic processes
  • Ontologies

• Data modelling, and applications of data within the sciences

• Data interfaces for simulation systems

Data Sets

• Climate data, index of selected climate data sets

Agenda

• Survey of selected data sets used in the Earth sciences

  • Create wiki pages

  • Blog article with survey results

• Conduct survey of what scientists are using what data sets for what purposes

• Solicit information on how the data sets can be improved through further processing

• Survey blog on software platforms for data storage and access, especially as applied to big data for the Earth sciences