The challenge of scientific data
The life science research industry is faced with an enormous data challenge. The cost of automation and sequencing has fallen 100x over the past decade, leading to explosive data growth. The pace of generation outstrips Moore's Law in some cases, and requires new approaches for collection, aggregation, and analysis.
Key barriers to utilizing rapidly growing data sets:
- Access to data
- Interoperability across systems
- Ability to reuse data
Tooling that addresses these issues and allows effectively democratized access to research data and the information that results from analyzing that data is crucial. Such tools must enable FAIR data principles, which are geared toward enabling comprehensive data usage, in order for organizations to fully utilize internal data and to enrich it with public data sets.