Research data often becomes trapped in technology silos that make it difficult to collaborate across research groups. Massive data sets need effective data management to extract the business value, reduce storage costs, and accelerate tiering between storage.
- Data from instruments or parallel file systems difficult to access, protect, and share
- Limited data insights: critical research data may go undiscovered and underutilized
- Improper metadata classification orphans data and prevents accurate data provenance for study results
- Applying custom taxonomies is labor-intensive and often incomplete
- Correlation & collaboration of data is difficult or non-existent