[jira] [Created] (AIRAVATA-3007) [GSoC] General plotting capabilities of experiment outputs

["Marcus Christie (JIRA)" <ji...@apache.org>]

Marcus Christie created AIRAVATA-3007:
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             Summary: [GSoC] General plotting capabilities of experiment outputs
                 Key: AIRAVATA-3007
                 URL: https://issues.apache.org/jira/browse/AIRAVATA-3007
             Project: Airavata
          Issue Type: New Feature
          Components: Django Portal
            Reporter: Marcus Christie


Add general plotting capabilities of computational experiment outputs to the Airavata Django Portal [1]. Portal admins that register an application should be able to specify what kind of visualizations should be provided to users for each file using a declarative configuration.  Code should not be required for simple charts, but for more complex use cases it should be possible to provide Python code needed to support it.

As an example, let's say there is an application that generates a CSV file with time series data. The admin user who is registering the application knows what sort of plotting is desired, which columns of data are needed from the CSV file, etc.  The admin user should be able to provide some JSON configuration that describe how to generate the plot. The Django Portal can then use this JSON configuration to process the CSV file and provide the data and configuration to a frontend UI component (implemented in Vue.js) that will then render the desired chart.  The charting technology should allow some interactive features so that users can explore the data easily.

Some charting libraries that look particularly interesting:
* https://plot.ly/javascript/
* http://echarts.apache.org/



[1] https://github.com/apache/airavata-django-portal



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