The annotation and the usage of scientific databases could be improved with public issue tracker software

Area of Science:

• Bioinformatics
• Scientific Databases
• Data Annotation

Background:

• Scientific databases are crucial for organizing biological information, translating literature into accessible data on genes and proteins.
• Despite advanced annotation, errors in public scientific databases can mislead researchers.
• Current error reporting mechanisms are often non-public, time-consuming, and discouraging for scientists.

Purpose of the Study:

• To propose the adoption of public error trackers for scientific databases.
• To enhance the quality and reliability of data in biological databases.
• To encourage community engagement and feedback on scientific data annotations.

Main Methods:

• Analysis of errors found in gene annotations within a well-known pathway across multiple biomedical databases.
• Examination of existing error reporting procedures in major scientific databases.
• Proposal of a public error tracking system inspired by open-source software development.

Main Results:

• Identified and helped resolve errors in gene annotations within key biomedical databases.
• Demonstrated that existing error reporting procedures are often not publicly visible, leading to inefficient and discouraging feedback loops.
• Highlighted the lack of acknowledgment for users reporting errors.

Conclusions:

• Public error trackers can significantly improve the accuracy of scientific database annotations.
• Implementing visible error tracking systems will foster greater community participation and data quality.
• Standardized, public error reporting is essential for reliable scientific data management.