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Public package repository for the Datagrok.ai platform

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This public repository contains API, tools, and packages for Datagrok, a web-based data analytics platform. It offers support for scientific domains, applications, connectors to web services, visualizations, file importing, scientific methods in R, Python, or Julia, file metadata extractors, custom predictive models, platform enhancements, and more. The open-source packages are free to use, with restrictions on server computational capacities for the public environment. Academic institutions can use Datagrok for research and education, benefiting from reproducible and scalable computations and data augmentation capabilities. Developers can contribute by creating visualizations, scientific methods, file editors, connectors to web services, and more.

README:

Datagrok package repository

This is a public repository for the API, tools, and packages available for Datagrok™, a next-generation web-based data analytics platform. The platform is very extensible, and almost anything could be implemented as a package:

These open-source packages are free to use by anyone, although for the public environment there are some restrictions related to the server computational capacities. Organizations that deploy Datagrok on their premises also can access public packages. In addition to that, enterprises typically establish their own private repositories that contain proprietary extensions.

For developers: check out getting started and contributor's guide.

Academia

Datagrok grants free license to academic institutions to use it in any context, either research or educational. Moreover, publishing scientific methods as Datagrok packages provides a number of unique benefits that are specifically important to academia:

For academic collaborations, please email [email protected].

Ideas for contributions

If you want to get familiar with the platform, here are some ideas. Pick whatever interests you, and reach out to Andrew ([email protected]) or post on our community forum.

  • Visualizations
    • Gantt chart
    • Port visjs-based network diagram from Dart to JavaScript
    • WebGL-based rendering of the 2D scatter plot to work with 10M+ points
    • Event drops
  • Scientific methods
    • Statistical hypothesis testing
    • Bayesian statistics
    • Computer vision
    • NLP
  • File editors and viewers
  • File metadata extractors (see Apache Tika)
  • WASM-based support for digital signal processing
  • Domain-specific algorithms
  • Connectors to web services and open datasets
  • Bioinformatics
  • Telecom
  • Fintech

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