Large-scale visualisation/analysis platform for climate data: Difference between revisions

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= Description =
= Description =
Many analysis tasks in climate research are mean and/or variance calculations over small (but many) netcdf files. Currently these
Many analysis tasks in climate research are mean and/or variance calculations over small (but many) netcdf files. Currently these
analysis tasks are done in Python using [http://www.numpy.org/ numpy] and [http://xarray.pydata.org/en/stable/ xarray]. The overarching goal of this project is to build an interactive web-framework for data analysis and discovery using the Python Visualization library [http://pyviz.org/ PyViz]. The groundwork for such a framework is already laid out in a former [https://github.com/ucyo/praktClimaAnalyse Praktikum].
analysis tasks are done in Python using [http://www.numpy.org/ numpy] and [http://xarray.pydata.org/en/stable/ xarray]. The overarching goal of this project is to build an interactive web-framework for data analysis and discovery using the Python Visualization library [http://pyviz.org/ PyViz].

= Groundwork =
The groundwork for a [https://github.com/ucyo/praktClimaAnalyse framework] is already laid out and can be build upon by the student.


= Task =
= Task =

Latest revision as of 15:50, 19 September 2019

Description

Many analysis tasks in climate research are mean and/or variance calculations over small (but many) netcdf files. Currently these analysis tasks are done in Python using numpy and xarray. The overarching goal of this project is to build an interactive web-framework for data analysis and discovery using the Python Visualization library PyViz.

Groundwork

The groundwork for a framework is already laid out and can be build upon by the student.

Task

The task for this semester is to integrate data streaming technology for visualization. There are several techniques already supported by the underlying technology e.g. AJAX data sources. Further it is possible to use RPC on different data hosting machines to move the computation to the data.

  • getting familiar with PyViz and the underlying technologies e.g. Bokeh
  • implement scripts that enhance the current framwork with streaming technologies such as AJAX
  • look into possibilties to use RPC for moving the computation to the data


Requirements

  • Programming experience in Python and some Javascript

Contact

Cayoglu@kit.edu