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Complete roadmap


graph TB;
    A[Development] --> B(Feedback from beta test)
    B --> C(Stable release v0.1)
    C --> D(Continuous updates)
    E[Engagement] --> F(Reach)
    E[Engagement] --> G(Outreach)
    E[Engagement] --> H(New contributors)
    F --> I(Feedback)
    G --> I(Feedback)
    I --> D
    H --> D
    D --> L(Release v1.0)


A roadmap is a collection of planned milestones and tasks that are necessary for the successful development and growth of the openhdemg project. It outlines the key steps and objectives that need to be achieved to meet the project's goals and deliver value to the community. The roadmap drives the project's evolution, ensuring that efforts are focused, organized, and aligned with the overall vision.

Milestones represent significant achievements and tasks are the actionable steps to reach those milestones. They provide a structured approach to project planning and execution, tracking progress and ensuring systematic completion. The roadmap is flexible, allowing us to incorporate users feedback and refine the plan based on community input.

Milestones

Legend for milestones status:

  Completed

  Ongoing

  Planned date

At this stage, we have identified and set six major milestones for the openhdemg project. These milestones are divided into two categories: three on the development side and three on the engagement side.

Development milestones

The development milestones focus on advancing the framework's functionality, improving existing features, and introducing new algorithms and analysis techniques. These milestones aim to enhance the capabilities and performance of openhdemg, providing a more powerful and comprehensive tool for analyzing High-Density Electromyography (HD-EMG) recordings.

Going public  

On 04/07/2023 the openhdemg project was released to the public with a beta release on PyPI, a public GitHub repository, a website and a Twitter page. This milestone marks the beginning of openhdemg as an open-source project.

Stable release v0.1    

Planned by end of 2023. While a beta release is meant for testing purpose, a stable release represents the transition to a production-ready version of the framework. The primary objective of this milestone is to ensure the reliability, robustness, and usability of openhdemg for a wide range of users.

Release v1.0  

The release of Version 1.0 is undoubtedly the most significant achievement for an open-source project like openhdemg, signifying a substantial enhancement in the project's completeness and usability. With this release, the project has achieved a level of maturity that fulfills the needs of a wide range of users in the field of HD-EMG.

Engagement milestones

On the engagement side, the milestones aim to enhance the reach and outreach of openhdemg and to bring new contributors in the project. These milestones focus on expanding the visibility and impact of openhdemg within the HD-EMG community and beyond.

Reach 1    

Planned by end of 2023. By leveraging preferred channels such as Twitter and congresses, we aim to engage with new individuals and organizations interested in HD-EMG analysis. Target to complete 'Reach 1' = 100 Twitter followers.

Outreach 1    

Planned by end of 2023. This milestone involves improving documentation, providing tutorials and educational resources, and enhancing user support. By achieving these milestones, we aim to empower users with the knowledge and tools they need to effectively utilize openhdemg and conduct their own HD-EMG analyses. Target to complete 'Outreach 1' = cover all the functionalities of the openhdemg framework with specific tutorials.

Increase contributors 1  

Bringing new contributors to the openhdemg project is fundamental to increase the functionalities of the framework and to build a collaborative community of experts. Target to complete 'Increase contributors 1' = 5 external contributors

Tasks

Development tasks

Stable release v0.1

  • Identify and address any critical bugs or issues reported during the beta testing phase.
  • Conduct extensive testing on different platforms and configurations to ensure the stability and reliability of the framework.
  • Incorporate user feedback and suggestions to improve the user interface, features, and overall user experience.
  • Create comprehensive documentation for installation, usage, and troubleshooting of openhdemg.

Release v1.0

  • Enhance the framework's performance and efficiency to handle larger datasets and complex analyses.
  • Implement additional algorithms and analysis techniques to broaden the capabilities of openhdemg.
  • Conduct thorough testing and validation of the framework's functionalities to ensure accuracy and reliability.
  • Document and communicate the major updates and improvements in the release to the user community.

Engagement tasks

Reach 1

  • Develop a social media strategy for openhdemg, including regular posting, engaging with relevant hashtags, and connecting with HD-EMG researchers and practitioners.
  • Share success stories, case studies, and relevant content about openhdemg on Twitter to attract a wider audience and increase followers.
  • Actively participate in HD-EMG-related congresses, conferences, and events to network with professionals in the field and promote openhdemg.

Outreach 1

  • Create comprehensive tutorials and educational resources that cover various aspects of HD-EMG analysis using openhdemg.
  • Improve the documentation to provide clear instructions, examples, and explanations of the framework's functionalities.
  • Establish a user support system, such as a forum or mailing list and promote the use of the openhdemg discussion section.

Increase contributors 1

  • Actively encourage contributions from the community by creating a contributor-friendly environment and providing guidance on how to get involved.
  • Identify specific areas where external contributors can make meaningful contributions, such as implementing new algorithms, improving existing features, or conducting performance optimizations.
  • Collaborate with potential contributors through issue discussions, pull request reviews, and effective communication channels to onboard them into the openhdemg community.