Extensions of Temporal Representations for Ontology-based and Holistic Reasoning in the Mobile Quality of Life Domain

The concept of Quality of Life (QoL) involves several dimensions, such as physical health and psychological state, which can be assessed by mobile resources and integrated to support holistic processes of reasoning and interventions. Ontologies are the main approach to organise and integrate such data in the form of knowledge.

However, while temporal aspects are usually present in the health domain, modelling information evolving time/events in ontologies is a complex problem since temporal relations are ternary and cannot be directly handled by ontology languages.

This lack of expressiveness restricts the power of the reasoning processes because several time aspects, which are usually embedded in the QoL domain, cannot be employed.

This project aims to design a conceptual framework for representation and reasoning about temporal aspects, associated with an ontological engineering method to guide the use of this novel framework during the process of converting static ontologies to their temporal versions.

This approach will be used over the development of four case studies: (1) general QoL ontology to represent the data acquired by the Quality of Life technologies lab over its longitudinal mobile assessments; (2) specialization of the QoL ontology for the aging population; (3) use of the previous ontologies as background knowledge to support the generation of explanations for inductive reasoning; and (4) use of the previous ontologies for QoL deduction-based interventions.

The validation of these ontologies and their applications will consider technical (identification of inconsistencies and contradiction) and empirical (ability to provide answers for competency questions) methods.

As the main expected result, this project intends to deliver a pragmatic strategy to support the creation of knowledge-based resources that can in fact improve the QoL of the general public and be adapted to cover the particularities of specific population features.