Module: Ontology management

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Ontology Management

Introduction

The Optique platform only offers a limited ontology editor. Protege is the recommended tool for ontology development. The ontology file can be uploaded and vizualized in the Optique platform.

Exercice

Several ontologies and even version of the same ontology can be managed by the Optique platform.

1. Once Optique platform is installed (ref. installing Optique), navigate to the ontologies menu.

2. Select your ontology file from a location and import the ontology using the upload function.

ontology management in Optique

3. A build-in function to add VQS specific annotations is available. Press the VQS annotation icon.

4. After running this function, it is recommended to download the ontology with annotation definitions back to your ontology editor tool.

5. Edit the concepts and properties according to VQS requirements.

6. Upload the annotated ontology back to the Optique platform (see step 2).

Resources

Northwind tutorial module 2 Task 1. Ontology

Task 1 will guide you through the process of ontology modification. You will learn how to add two new concepts into an existing ontology class hierachy.

Note: running the tutorial with editing rights requires installation of the Northwind tutorial using method 2 or 3. To read the tutorial method 1 (public demonstrator) is sufficient.

Go to resource

Ontology Manager

This help describes the ontology formats supported, how to upload and download ontologies and management of versions.

Go to resource (use demo/demo as login/pwd if asked)

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Optique: a paradigm shift for data access

The project will provide a semantic end-to-end connection between users and data sources. The Optique platform will feature an intuitive, general, but adaptable end-user interface. Data can be integrated from multiple, also streaming, data sources, with the possibility for large-scale parallel cloud processing and storage.

Optique: a unique combination of technologies

The Optique project brings a unique combination of technologies to bear on Big Data challenges: An end-user-oriented query interface; scalable query rewriting from the end-user to the source vocabulary; temporal and real-time continuous stream processing; scalable storage and query evaluation using elastic clouds.