In order to propagate changes in, and between information nodes in the Web, a high-level architecture has been proposed for a reactive framework aligned with the goals and technologies of the Semantic Web - r3 (see http://rewerse.net/I5/r3/). As part of the validation of this framework, we have used Bioinformatics as a case study. This approach required the design and implementation of a service ontology for the Bioinformatics domain (B-Domain). The ontology describes both the static and dynamic concepts of the domain, enabling reasoning and rule composition, without disregarding language heterogeneity in the Semantic Web.
The concept was validated with 4 scenarios similar to the one presented in Fig. 1. This particular scenario shows a user being notified whenever a new dimer is published in PDB. To accomplish this task the scenario depicts the use of the B-Domain and SPARQL Brokers and of a Personalized Mirror. The first component integrates information sources relevant to bioinformatics exposing its features through B-Domain’s ontology. The second leverages the features of the SPARQL query language to the framework’s Enterprise Service Bus. The Event Condition Action (ECA) Engine is an r3 rule engine that allows the registration and execution of Event-Condition-Action rules. Finally, the Personalized Mirror is a simple component that allows users to store RDF/XML data. The external interfaces of each component are described using the r3 framework’s ontology. The execution of the validation scenarios showed that Bioinformatics would strongly benefit from the features provided by B-Domain. Its characteristics allow the description of the static and dynamic semantic features of the domain, enabling reasoning on top of those concepts. It also offers a way to create and deploy declarative rules (ECA), which can be chained to create complex meaningful rules. The running version of B-domain can be found at http://rewerse.net/I5/r3/TST/install/dev/other/b-domain/.