## 5 Conclusions and Future Directions  
In this work, we have emphasised the importance of representing and reusing models through the use of word embeddings as a means of improving the systems development process. To validate the presented approach, a case study was conducted representing and indexing a dataset of physical models from Simulink. A set of queries was designed to measure the performance of the retrieval system using a similarity algorithm that compares the distances of concepts between the model and queries. Through this case study, we have demonstrated the feasibility of the proposed approach in effectively supporting the two first stages (abstraction and selection) of a reuse strategy for a physical model. In addition, this work provides insights into the performance of the similarity algorithm used in the process of reusing physical models. We found the algorithm to be effective in identifying relevant models for the queries as well as when the query contained terms that were not in the models; however, in certain cases irrelevant models were retrieved, leading to penalisation of the recall metric. As such, we suggest that future research focus on refining the algorithm to further improve its precision and recall values, for example, by readjusting the weights and penalty functions. The use of word embeddings and similar approaches for promoting the reuse of physical models has the potential to revolutionise the engineering industry. By reducing the need for engineers to create a domain ontology to represent the semantics of the terminology, this methodology can speed up development times, improve efficiency, and allow for more complex systems to be developed. As such, we believe that continued research in this area is essential to unlocking the full potential of these techniques and maximising their impact on the engineering discipline. However, as part of future work it is important to understand the specific purpose of a model and consider the viewpoints of stakeholders. To address potential confusion in terminology usage, frameworks such as LOTAR [37] have been developed to incorporate metadata that provide more precise definitions on the model's domain. This can help to clarify the intended purpose and perspective of the model, thereby reducing misinterpretations that may occur when diverse stakeholders hold varying viewpoints on the same concept. Overall, we believe that our approach has the potential to make a significant impact in the field of physical modelling by providing a more efficient and effective way to reuse existing models. We hope that our work will inspire further research in this area and that it will ultimately lead to new tools and methods that make it easier for engineers to build and maintain high-quality physical models. **Author Contributions:** Methodology, E.C. ; software, E.C. and R.M; validation, E.C., R.M. and J.M.A.-R.; formal analysis, E.C. ; investigation, E.C., R.M. and J.M.A.-R.; resources, E.C. ; data curation, E.C. ; writing--original draft preparation, E.C. ; writing--review and editing, J.M.A.-R.; visualisation, E.C. ; supervision, J.M.A.-R.; project administration, J.L. ; funding acquisition, J.L. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was partially funded by H2020-ECSEL \"Intelligent Reliability 4.0\" (IREL 4.0; grant agreement: 876659), H2020-ECSEL Joint Undertaking (JU) \"Arrowhead Tools for Engineering of Digitalisation Solutions\" (grant agreement: 826452), and specific national programs (AEI/10.13039/501100011033). **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The dataset of models used for conducting this case study is publicly available at [[https://github.com/edcisa/physicalModels](https://github.com/edcisa/physicalModels)]([https://github.com/edcisa/physicalModels](https://github.com/edcisa/physicalModels)). The dataset consists of 40 diverse and representative models created using Simulink.