Ontario

Facts

Contact Person

Kemele M. Endris

Email

kemele.endristibeu

Category

Computer Science, Data Science, Knowledge Engineering, Linked Data, Scientific Data Management

Technology Readiness Level

4

URL: https://labs.tib.eu/ontario

Ontario is an ontology-based data integration and semantic enrichment on-demand framework over Semantic Data Lakes. Ontario adds semantic layer on top of the source datasets which are stored as a raw format in a Data Lake. Ontario supports different data models (structured and semi-structured) such as Relational, CSV, TSV, JSON, XML, Document, and Graph. In addition, the following data management systems are supported: MySQL, Postgres, MongoDB, Neo4j, and distributed file systems Hadoop HDFS and S3. SPARQL is the global query language and currently RML mappings are supported.

Images

Ontario Dashboard
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