Combining public, 3rd party, and private data sources

When all available information is collected and assessed, gaining insight into the state of the art of specific disease areas is only possible – or at least done in the best possible way. Although much information is available in free public databases, the addition of commercial databases and own research data can significantly broaden scientific knowledge.

Publicly available information of almost 150 scientific databases is linked and structured by DISQOVER. This information is accessible to the public and covers a large data landscape: medicine, pharmacology, toxicology, bioinformatics, clinical development, patents, or chemistry. These help researchers by providing a large pool of knowledge they can draw from when developing new ideas or theories that might benefit many fields. This allows users to gain insights into targets, relevant biomarkers, available treatments, clinical trial designs, and much more scientific topics to support health care development in a fast and efficient way.


datasources-federation-illustration@2x-1DISQOVER uses semantic technologies to link different data types from multiple sources into an integrated knowledge base. This allows users to explore numerous resources simultaneously, i.e., linking chemical compounds with disease-related information or linking gene functions with drug targets. The underlying technology of DISQOVER is based on an ontology (i.e., a formal definition of terms) that links various entities in a structured way, enabling queries such as "Find all drugs that target this molecule". The ontology consists of a hierarchical set of terms annotating the linked datasets (chemical compounds or genes). The ontology also contains relationships between terms, e.g., links a gene to the associated diseases. These relationships enable users to discover what is known about a specific disease or information on a particular molecule or group of molecules.

DISQOVER ontology graph
DISQOVER, developed by ONTOFORCE, is a knowledge platform that provides semantic-enabled bioinformatics solutions to help Life Sciences researchers in their daily work. The aim is to provide an integrated view of information and knowledge about molecules, genes, and diseases, thereby supporting researchers in their decision-making processes when using data from different sources. DISQOVER is used in more than 10,000 sessions by researchers worldwide.



Go hands-on with the DISQOVER Community Edition to search, explore and visualize data from various public sources for free, or get in touch with our team to schedule a personalized demo. 



The term ‘big data’ seems old school now that ‘machine learning’, ‘deep learning’ and emerging concepts such as ‘edge AI’ are the hypes of the day. However, despite our general familiarity with the concept of big data, challenges related to data-driven decision making still remain.  Several key learnings have emerged over the last decade. How do we use our expensive data processing and analytics tools to generate actionable insights?