DISQOVER integrates data from a variety of disparate data sources using the powerful concept of an ontology-based knowledge graph. All data is linked, relying on a unified nomenclature. This means that the data becomes understandable and informative, and you can search and analyze the entire integrated data set without having to worry about the particularities of the original data sources.
Understanding intent and context
The semantic search extends the standard search capabilities by looking at the intent of the searcher as well as the context of the search, resulting in more-refined and precise search results.
Discovering unexpected new insights is a core objective of DISQOVER. At any time, the knowledge graph allows you to follow links to additional, related information for a result set revealed by your search. For example, if you have performed a keyword search revealing several publications, with a single click, you can retrieve a list of authors for these publications. Another click, and you can retrieve these authors’ organizations.
A visual pipeline makes it easier to communicate the choices made during data integration, resulting in increased transparency and auditability, and fewer chance of error. Stakeholders with only basic IT knowledge can understand, review, challenge, and contribute to the data integration process.
With DISQOVER, you can create an enterprise-wide data catalog where end-users can find and (re-)analyze data in one data ecosystem. Specifically, DISQOVER combines automation for data cleansing and semantic integration with guided search and analytics in one easy-to-use interface.