Matchmaking Implementation Sample Clauses

Matchmaking Implementation. The Federated Search is developed as a Spring Boot microservice. It consists of the Matchmaking Ontology and an API for accessing the indexed data. It hides the complexity using a full featured search engine (Apache SOLR3) and provides simplified access to the indexed data, supporting full text search and faceted search over the indexed data collections. Apache Solr is a scalable and fault tolerant search platform that provides distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. The Matchmaking Ontology in EFPF is the foundation of the SOLR data model and is inspired by the SKOS4 (Simple Knowledge Organization System) Ontology. SKOS is a common data model for sharing and linking knowledge systems using the Semantic Web technologies. In short, SKOS specifies the notion of concepts which might be connected by means of broader and narrower relationships. Concepts might be grouped together in concept schemes and allow for multilingual naming with preferred, (multiple) alternate and hidden names. Apache SOLR allows for storing arbitrary documents with flexible data models. However, to support the matchmaking and federated search processes, the EFPF Matchmaking Ontology has been defined (see Figure 22 below). Every data item of interest is categorized using arbitrary concepts or treated as an instance of a certain class. The Concept class specifies dedicated attributes which are commonly present. This is reflected in the Matchmaking Ontology with the Class/Category and the Property collections. As outlined in Figure 22, each indexed product (Item) might be annotated as an instance of a predefined Class/Category. The Class/Category however will then provide the relevant attributes which are expected to be present with the indexed product. These relationships (Item is instance of Class/Category; Class/Category has Properties) is important for providing search interfaces since the data items need to be presented in a human readable way. The Matchmaking Service is based on the Matchmaking Ontology that defines the internal data structure and format of the indexed data. This data structure must be adhered when using the services for storing and retrieving the data. 3 ▇▇▇▇▇://▇▇▇▇.▇▇▇▇▇▇.▇▇▇/ 4 ▇▇▇▇▇://▇▇▇.▇▇.▇▇▇/TR/swbp-skos-core-spec/ In the indexing workflow (see Figure 21), the base platform’s data stores provide their data to the Matchmaking Service. To align the distinct platform’s da...