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This project aims to create a structural representation of similar nominal Java classes. A structural type is represented by an interface that contains property accessors for all properties that are defined by those classes. For each class, a projection class is generated that implements that interface for delegation to the nominal classes for which the structure was created. Additionally, a template implementation is created that implements the structural interface as a Java bean.

Provides a mapping from Event Admin events to Javascript Server Side Events (SSE). This bundle registers under /sse/1, the remaining path is treated as the topic. It will then send all matching events to the browser through SSE. The type of the event is org.osgi.service.eventadmin;topic=%s, the data payload is a JSON representation of the event properties.

Provides a mapping from Event Admin events to Javascript Server Side Events (SSE). This bundle registers under /sse/1, the remaining path is treated as the topic. It will then send all matching events to the browser through SSE. The type of the event is org.osgi.service.eventadmin;topic=%s, the data payload is a JSON representation of the event properties.

The Product Service provides access to data products. Products can be scientific datasets, images, documents, or anything with an electronic representation. The Product Service accepts standard query expressions (see the Query Expression component) and returns zero or more matching products. In addition, the product service can transform products from proprietary formats and into Internet standard formats or run other transformations, all without impacting local stores or operations.

Java Validation Framework (not a JSR-303 implementation). This framework allows to modify (correct) test values; supports validation of localized values; allows to convert values into and from text representation; formats error messages, depending on the context; supports metadata, which allows to check any entity types (not only Java Beans or POJOs) and more. Also this framework has long list of predefined validation components.

InteGraal has been designed in a modular way, in order to facilitate software reuse and extension. It should make it easy to test new scenarios and techniques, in particular by combining algorithms. The main features of Graal are currently the following: (1) internal storage to store data by using a SQL or RDF representation (Postgres, MySQL, HSQL, SQLite, Remote SPARQL endpoints, Local in-memory triplestores) as well as a native in-memory representation (2) data-integration capabilities for exploiting federated heterogeneous data-sources through mappings able to target systems such as SQL, RDF, and black-box (e.g. Web-APIs) (3) algorithms for query-answering over heterogeneous and federated data based on query rewriting and/or forward chaining (or chase)

InteGraal has been designed in a modular way, in order to facilitate software reuse and extension. It should make it easy to test new scenarios and techniques, in particular by combining algorithms. The main features of Graal are currently the following: (1) internal storage to store data by using a SQL or RDF representation (Postgres, MySQL, HSQL, SQLite, Remote SPARQL endpoints, Local in-memory triplestores) as well as a native in-memory representation (2) data-integration capabilities for exploiting federated heterogeneous data-sources through mappings able to target systems such as SQL, RDF, and black-box (e.g. Web-APIs) (3) algorithms for query-answering over heterogeneous and federated data based on query rewriting and/or forward chaining (or chase)