Assets Used & Produced

In a research software management plan, various assets are used and produced (also known as input and output) to ensure effective management and development of research software, some common assets include:

Assets Used

1. Version Control System

   A version control system is used to track changes made to the software code over time. It allows developers to collaborate, manage different versions of the software, and maintain a history of all modifications and contributions.

2. Issue Tracking System

   An issue tracking system (JIRA, GitHub Issues e.g.) is used to manage and track software issues, bugs, feature requests, and other tasks related to the software development process. It helps organize and prioritize tasks, assign them to team members, and track their progress.

3. Research Data

   Research software often deals with data and datasets used for experimentation, analysis, or training machine learning models. These assets can include raw data files, processed datasets, metadata, and documentation describing the data sources and preprocessing steps.

4. Other Software Packages/Libraries

   Third-party libraries are essential components of most software projects, and acknowledging their use is important for legal compilance reason. Since many third-party libraries/software packages come with specific licenses and usage terms that need to be adhered to. By documenting these libraries in the management plan, developers and stakeholders can ensure compliance with the licensing requirements and avoid potential legal issues related to intellectual property rights when selecting a licensing for the project.

Assets Produced

1. Source code

   The actual software code is a primary asset in any research software management plan. It includes all the program files, scripts, libraries, and configurations used to build the software.

2. Executable Software

   Compiled or packaged versions of the software that can be executed on different platforms. If applicable, pre-configured deployment packages or Docker images to facilitate the installation and setup of the software.

3. Documentation

   Comprehensive documentation is crucial for managing research software effectively. It includes various types of documentation such as user manuals, installation guides, API references, code comments, and README files. These documents provide instructions on how to use the software, explain its architecture and design choices, and offer guidance on contributing to and extending the software.

4. Licensing and Copyright Information

   Research software management plans should include details about the software’s licensing and copyright information. This ensures compliance with relevant open-source licenses or any restrictions placed on the software’s usage and redistribution.

5. Test Data and Test Suites

   Datasets used to validate the correctness of the software and the associated test suites to automate testing.

6. Research Outputs

   Depending on the nature of the research, the software may produce data, results, or other outputs that contribute to the research findings. As well as publications or reports that describe the research, including the software, algorithms, and methodologies used.

It is important to note that the specific assets used and produced in a Research Software Management Plan may vary depending on the project’s scope, goals, and requirements. The RSMP should be tailored to the research project’s needs and align with best practices for software development and management in the research domain.

---