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'Benerator' is a framework for creating realistic and valid high-volume test data, used for testing (unit/integration/load) and showcase setup. Metadata constraints are imported from systems and/or configuration files. Data can imported from and exported to files and systems, anonymized or generated from scratch. Domain packages provide reusable generators for creating domain-specific data as names and addresses internationalizable in language and region. It is strongly customizable with plugins and configuration options.

This service implements the Indexer and Searcher interface of WebLab and connect to a remote SOLR engine in order to realize the functions. The connection is mandatory and thus the remote SOLR server should be started beforehand. Configuration of the SOLR server URL is found in src/main/webapp/WEB-INF/cxf-servlet.xml . See in particular "indexerServiceBean" and "searcherServiceBean". Moreover, the service implements several "Analyser" services that could be included in a complete search chain in order to: - enrich a ResultSet with metadata about Hits (see resultSetMetaEnricherServiceBean) - highlight snippet in ResultSet (see highlighterServiceBean) - provide facets related to the current results (see facetSuggestionServiceBean) - suggest spell correction of the original query (see spellSuggestionServiceBean)

rapiddweller 'Benerator' is a software solution to generate, anonymize, pseudonymize and migrate data for development, testing and training purposes. rapiddweller 'Benerator' is easy to learn, integrates into CI Tools like Jenkins and Gitlab CI and allows to create data models on the most abstract level. rapiddweller 'Benerator' allows creating realistic and valid high-volume test data, used for testing (unit/integration/load) and showcase setup. Metadata constraints are imported from systems and/or configuration files. Data can imported from and exported to files and systems, anonymized or generated from scratch. Domain packages provide reusable generators for creating domain-specific data as names and addresses internationalizable in language and region. It is strongly customizable with plugins and configuration options. rapiddweller 'Benerator' is build for Java 1.8 and Java 11. The development is ongoing for Java 11.

Apache Spatial Information System (SIS) is a free software, Java language library for developing geospatial applications. SIS provides data structures for geographic features and associated metadata along with methods to manipulate those data structures. The library is an implementation of GeoAPI 3.0.2 interfaces and can be used for desktop or server applications. The SIS metadata module forms the base of the library and enables the creation of metadata objects which comply with the ISO 19115 international standard. The SIS referencing module enable the construction of geodetic data structures for geospatial referencing as defined by ISO 19111 standard, along with the associated operations which enable the transformation of coordinates between different reference systems. The SIS storage modules provide a common approach to the reading and writing of metadata, features and coverages applicable to simple imagery as to many dimensional data structures.

Luzzu is a Quality Assessment Framework for Linked Open Datasets. It is a generic framework based on the Dataset Quality Ontology (daQ), allowing users to define their own quality metrics. Luzzu is an integrated platform that: - assesses Linked Data quality using a library of generic and user-provided domain specific quality metrics in a scalable manner; - provides queryable quality metadata on the assessed datasets; - assembles detailed quality reports on assessed datasets. Furthermore, the infrastructure: - scales for the assessment of big datasets; - can be easily extended by the users by creating their custom and domain-specific pluggable metrics, either by employing a novel declarative quality metric specification language or conventional imperative plugins; - employs a comprehensive ontology framework for representing and exchanging all quality related information in the assessment workflow; - implements quality-driven dataset ranking algorithms facilitating use-case driven discovery and retrieval.