On the way to plant data commons - a genotyping use case

Area of Science:

• Bioinformatics
• Genomics
• Data Science

Background:

• Life science data collection has surged, increasing demand for advanced bioinformatics solutions.
• Effective data management and analysis are essential throughout the data life cycle.
• Genotyping, particularly imputation, necessitates robust Research Data Management (RDM) strategies for data reuse.

Purpose of the Study:

• To present concepts for developing sustainable and reusable bioinformatics tools.
• To outline strategies for improving the interoperability and maintainability of data analysis services.
• To discuss the importance of community engagement in software development and maintenance.

Main Methods:

• Standardizing input/output formats for bioinformatics tools.
• Adopting open and widely-used file formats to enhance tool connectivity.
• Developing and fostering communities around bioinformatics software.

Main Results:

• Standardized formats improve tool reusability and interoperability.
• Open file formats facilitate the integration of different bioinformatics tools.
• Community involvement is key to long-term software sustainability and evolution.

Conclusions:

• Sustainable bioinformatics software relies on reusability, maintainability, and interoperability.
• Standardization and community support are critical for effective Research Data Management in genomics.
• The presented concepts provide a framework for developing robust imputation services.