It is becoming more and more mission-critical for life science companies to manage and connect complex data and processes from scientific discovery to commercialization. Digitalization appears the best path forward for connecting the entire product life cycle. However, in order for digitalization to be successful, organizations must adopt informatics solutions that enable the centralization of well-described, standardized, and accessible data, and conform to community standards. FAIR data principles have become an international guideline for high-quality data stewardship on such a platform and serves as helpful reference points for the development of an effective data management strategy.
In this white paper, we discuss:
- What the FAIR principles are and the importance of them in improving productivity, collaboration, and data integrity
- How specific features in Benchling support an organization’s adoption of FAIR data principles and the corresponding impact