The HUMIT system enables the management and integration of research data. The project addressed drug discovery as an application domain, but the system is not limited to a particular domain. Data can be semantically enriched by using annotations. The use case considered in the project applied the MIABAO (Minimal Annotation Bio Assay Ontology) for semantic annotations. The ontology annotations enable the linking of the data of the HUMIT system with external data. The comprehensive view of related data is a major benefit compared to the classical labor-intensive, manual process of analysis of single screens, and could support the identification of active ingredients. The integration of data from different experiments (screens) is the basis for further data analysis, using methods from artificial intelligence or deep learning. A comprehensive set of raw data with high data quality is required for such an analysis; the HUMIT system enables the provision of such data.
ExtractionData and metadata can be extracted semi-automatically from data sources.
IntegrationData from heterogeneous sources with various data types and formats can be integrated.
Secure Data Repository
Data and metadata are managed in dataspaces and projects, for which detailed role-based access restrictions can be defined.
Semantic AnnotationData and metadata can be annotated with arbitrary annotations. Templates can be defined for specific data types to restrict the annotations to a specific ontology.
SearchData and Metadata can be queried by a keyword search and facette-based search.
A demonstration video illustrating the most important features of the HUMIT system is also available.
The final report of the HUMIT project (in German) gives a more detailed description of the system and its implementation.