# Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments
## 1 Introduction  
Any ambient intelligence is immersed with events that are connected between them and with relevant information such as time, location, and actors [1]. An academic environment is not exempt from this situation, in which events are related to academic activities. They should be structured and readable by a machine since manual handling is time consuming and tedious [2]. Their automatic management can make it possible that the academic environment offers services based on events for professors, students, and visitors, such as voice interaction, question-answering systems, and search engines [3]. Enrichment and reasoning processes with events to discover new information, are impossible to carry out without a proper structure. It is important to have a model to represent events with their contextual information: Location (where?), time (when?), person (who?), and event category (what kind of event has happened?). In this manner, the model can execute reasoning with events and allow an enrichment process from context information in academic environments [4].  
Ontologies provide mechanisms to semantically structure the information. They achieve a high level of expressiveness in the concepts, allowing the addition of semantics to the domain model. Ontologies are developed on formal languages and semantics, allowing the execution of reasoning about ontological concepts in a particular domain. As a result, they are formal and machine-readable [5].  
Events have contextual information, such as time, actors, and location [6]. Research about the facts that have occurred in the real world and their representation as events has gained more interest in the computer science community.  
Events represented through ontologies have shown effectiveness and make it easy to model semantically a context for sharing and reuse of knowledge [7]. They also facilitate event processing such as detection, reasoning, enhancing, classification, and storing to provide services to users in ambient intelligence [8].  
In this paper, we present an event-driven approach based on a customized ontological model for context representation in academic domains. It supports event management, reasoning, enhancing, and evaluation. It offers the basis to develop a context-aware environment to provide user services (professors, students, and visitors). Event modeling has been addressed by modular ontologies as a representation mechanism. Later, they were integrated to compose an approach for context representation based on a customized ontological model. Context information is included, such as time, location, and person. A network module is integrated to detect people in a current physical space. In addition, context reasoning and enrichment processes are implemented with Semantic Query Enhanced Web Rule Language(SQWRL) and Semantic Web Rule Language (SWRL), respectively. This process is carried out to discover new knowledge to enhance the model.  
The rest of this paper is organized as follows. In Section 2, the related work is presented, focused on event enrichment, ontologies for context modeling, and context reasoning. In Section 3, the bases of context modeling centered on academic events and ontologies are given. Section 4 shows the reasoning and enrichment process over the events depicted in the ontological model. Section 4 also exhibits the evaluation process of our customized model, which is focused on use case scenarios, context reasoning questions, and principles of design. Finally, the conclusion and future work are given in Section 5.