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The eagle-i ontology drives the data collection and search user interfaces and internal mechanisms, and is used for structuring and validating data in the repository and for indexing resources. This design choice allows applications to seamlessly adapt to ontology evolution, and provides ontology developers with a mechanism to rapidly test and refine their models. Figure 1 depicts an eagle-i network at a high level.
Figure 1. Architecture of an eagle-i network
The eagle-i software stack
Figure 2 shows a more detailed view of the software stack at an eagle-i node.
Figure 2. Details of the eagle-i stack
Repository
The eagle-i repository provides a REST API for storage and retrieval of eagle-i resource descriptions. It internally uses the Sesame RDF store. The repository functionality includes role-based access control, transactional CRUD operations on eagle-i instances [1], a data staging mechanism in the form of a curation workflow, a harvesting mechanism for incrementally communicating updates aimed at building search indices and a general purpose SPARQL query endpoint.
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Figure 3 illustrates our ontology-driven approach.
Figure 3. Ontology-driven approach
Terminology
[1] eagle-i resource instance - a collection of RDF statements about the same subject or about an embedded instance [2] subject, plus the display labels of all predicates and objects used in these statements.
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Overview
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