Towards Evidence-Based Ontology for Supporting Systematic Literature Review
This is an incremental improvement for software engineering researchers conducting SLRs, as it automates key activities using existing ontology methods.
The paper tackles the high effort required for Systematic Literature Reviews (SLR) in software engineering by proposing an ontology-based approach, resulting in significantly reduced effort while achieving the same conclusions as manual work.
[Background]: Systematic Literature Review (SLR) has become an important software engineering research method but costs tremendous efforts. [Aim]: This paper proposes an approach to leverage on empirically evolved ontology to support automating key SLR activities. [Method]: First, we propose an ontology, SLRONT, built on SLR experiences and best practices as a groundwork to capture common terminologies and their relationships during SLR processes; second, we present an extended version of SLRONT, the COSONT and instantiate it with the knowledge and concepts extracted from structured abstracts. Case studies illustrate the details of applying it for supporting SLR steps. [Results]: Results show that through using COSONT, we acquire the same conclusion compared with sheer manual works, but the efforts involved is significantly reduced. [Conclusions]: The approach of using ontology could effectively and efficiently support the conducting of systematic literature review.