This page acts as a 'notebook' for testing the different kinds of queries, directed towards the ENVRI Knowledge Base (ENVRI KB), that are needed to support different types of activity. Sample queries can be submitted to the live knowledge base, and results displayed.
This service is part of the ENVIRplus project's "Data for Science" theme. It makes use of the ontologies for Open Information Linking for Environmental Science Research Infrastructures (OIL-E), which itself uses the concepts and vocabulary introduced by the ENVRI Reference Model.
For the ENVRI Knowledge Base, we identified four key knowledge capabilities that application of the semantic linking framework can facilitate:
In the coming month (April 2018), we shall be updating the knowledge base and publishing a new set of sample queries on this page for demonstration purposes.
The following namespace declarations are automatically prefixed to all queries submitted via this page:
If necessary, these declarations can be edited (and reset by refreshing the page).
The following sample SPARQL queries can be submitted to the live knowledge base and their results viewed.
All query examples are fully editable, should you wish to experiment. All sample data is structured according to the OIL-E ontologies. At this point, only SELECT queries are supported.
Please be aware that all results regarding specific research infrastructures are provisional, and should not be taken as being approved in any way by the infrastructures themselves at this point in development.
This query extracts properties of the 'add metadata' information action defined by the ENVRI Reference Model:
The following query identifies the subset of RIs defined in the ENVRI Knowledge Base that are actually part of the ENVRIplus project, and provides some basic information about them:
This query can retrieve the technologies associated with particular services:
The following query can be used to identify concepts (both classes and individuals) described using the term 'catalogue':
The next query can be used to identify the capabilities provided by a catalogue service:
While this query can identify the capabilities required by a catalogue service:
A recent student project produced an ENVRI 'reference model visualiser'. The main idea behind this viewer was to provide recommendations of computational objects based on free-text requirements input by a user. It extracts nouns and verbs from the free-text inputs provided and searches the knowledge base for components that refer to those words in their label or description - a basic, initial example of combining natural language processing with information retrieval for the ENVRI Knowledge Base. The main queries supported are: