Scientific Lake service
The service is designed to collect, manage, and query heterogeneous scholarly content. It provides functionalities, components and open APIs to support research activities.
The service has the following components
Interlinking/federations of SKGs
SciLake's scientific knowledge graphs are built using semi-supervised tools and methods for interlinking data (ontology, entity, relationship, property). Based on recent work on graph generating dependencies (GGD), these methods will generate explainable fuzzy logical rules that capture expert knowledge and ML-driven measures of graph similarity. Rules based on GGD are used to resolve entities and relationships, to verify and enforce key values and to generate further knowledge based on expert or ML models.
Creation of scientific knowledge graphs (SKGs)
A set of automated and semi-automated tools for:
- Semantic modelling and maintenance of the primary (and auxiliary) ontologies for the SKGs; extraction of information (entity, relation, property) from unstructured raw data;
- Mapping of (semi-)structured data to a property graph schema, using relational data.