SEED will enable a FAIR aligned comprehensive semantic capture and translation of data across eLN providers at the point of entry. Output will be computer readable standard data, increasing capacity for provenance and attribute connection for insight and analysis
Project deliverables
Deliver a Pre-competitive guidance and working prototype solution on the usage of open standards and Ontologies to deliver FAIR aligned semantic structure to eLN data at the point of entry
Why is this important?
- Volumes of unstructured eLN content are exponentially growing
- Most eLN content is free text, unstructured information and thus challenging to identify common concepts, to effectively search and extract deeper Insights
- Retrospective data analysis and searching of generally unstructured content is a huge challenge
- Data Workflows to/from eLNs can be relatively restricted in approach. Connectivity to Study Registration systems to enable Scientists to reuse such metadata through API to eLN are a must
- Availability of persistent identifiers challenges the capability of making data to be digitally discoverable and hinders aggregation of data inter-applications
- Valuable insights are hampered by unstructured content which prevents deeper data analysis thereby losing competitive advantage
What will the project achieve?
Through collaboration and alignment across the pharma industry, the SEED project will create a standardized computer readable FAIR aligned data foundation.
A working prototype solution will be created to enable data discoverability/insights inter and intra eLN system.
How will the project do this?
- Comprehensive Pharma/eLN provider/ Semantic Provider representation
- Clear and aligned agreement across those representing
- Extensive Requirement gathering
- Phased usecases to prove the value of the approach
- Pharma endorsement and agreement of an Aligned Need
- eLN provider embracing and enabling the guidance from Pharma
- Defined stage gates of delivery of the project
