Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory. International Journal of Telemedicine and Applications

TL;DR

This paper introduces a category theory-based, ontology-driven approach to manage requirement volatility in a biomedical LIMS, enhancing understanding and traceability of dynamic requirements in complex clinical systems.

Contribution

It presents a novel agent-based framework utilizing category theory and ontologies to analyze and control requirement changes in biomedical software systems.

Findings

Improved understanding of requirement hierarchies.

Enhanced traceability of requirement changes.

Effective management of requirement volatility.

Abstract

Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.