TopBraid Discovery Workbench: Federated Data
Integration for the Life Sciences
Pharmaceutical companies are experiencing a growing
need to produce smarter drugs and to deliver them to market faster.
To achieve this they are becoming increasingly reliant on the
integration of the massive volumes of heterogeneous data being
generated across diverse areas and on the discovery of knowledge
from this data.
Life Sciences professionals need data of many kinds, from numerous
perspectives and on multiple topics ranging from gene expression
studies to clinical observations. They need to be able to simply and
readily bring such data together and view, explore, and analyze it.
To discover key information, relationships and patterns they need to
be able to search, query, and question any aspect of the data from
Such capabilities require a new generation of data access and data
integration solutions. TopBraid Discovery Workbench was conceived as
a solution that will free scientists from tedious data management
tasks and allow them to fully focus on their research.
Key Capabilities of Discovery
Discovery Workbench provides Life Sciences researchers with on
demand integrated access to both internal and external data sources,
with the following core features:
- Data selection and access –
from the variety of internal sources and the growing volume of public data from
the initiatives such as Bio2RDF, Linked Life Data, EMBL & EBI and OpenPHACTS
- Mapping - ID mapping and concept mapping leveraging and
cross-referencing internal identifiers and industry vocabularies such as SNOMED
- Discovery - intuitive navigation and exploration
allowing just in time discovery of information
Discovery Workbench is powered by Semantic Web technologies to
overcome barriers to data integration:.
- RDF provides a universal canonical data
format that has the flexibility to represent any data structure
- URI’s provide global identifiers that can be mapped across data
sources without requiring to have a single universal ID for each entity
- Ontologies help to categorize and represent the data concepts in a variety