729 research outputs found

    Comprehending 3D and 4D ontology-driven conceptual models: An empirical study

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    This paper presents an empirical study that investigates the extent to which the pragmatic quality of ontology-driven models is influenced by the choice of a particular ontology, given a certain understanding of that ontology. To this end, we analyzed previous research efforts and distilled three hypotheses based on different metaphysical characteristics. An experiment based on two foundational ontologies (UFO and BORO) involving 158 participants was then carried out, followed by a protocol analysis to gain further insights into the results of experiment. We then extracted five derivations from the results of the empirical study in order to summarize our findings. Overall, the results confirm that the choice of a foundational ontology can lead to significant differences in the interpretation and comprehension of the conceptual models produced. Moreover, the effect of applying a certain foundational ontology can cause considerable variations in the effort required to comprehend these models

    A comparative illustration of foundational ontologies : BORO and UFO

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    This paper investigates the differences that exist between a 3D and a 4D ontology. We examine these differences by comparing both ontologies through the metaphysical choices each ontology makes and explore the composing characteristics that define them. More specifically, the differences between the ontologies were illustrated through several modeling fragments that were derived from a modeling case presented at the 5thOntoCom workshop. Each of these modeling fragments focused on the metaphysical choices that the ontologies make –Essence and Identity, Relationships and Time. These comparisons highlighted the different ontological approaches and structures that exist between the ontologies. Moreover, depending on the ontology, the resulting conceptual model could differ substantially, confirming the impact and importance of the choice of a certain ontology. The observed differences between both ontologies eventually led us to formulate three discussion points that question the applicability of certain metaphysical choices in certain circumstances, and that can serve as a basis for future discussion or future research studies in the domain of ODCM

    Comparing traditional conceptual modeling with ontology-driven conceptual modeling: An empirical study

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    [EN] This paper conducts an empirical study that explores the differences between adopting a traditional conceptual modeling (TCM) technique and an ontology-driven conceptual modeling (ODCM) technique with the objective to understand and identify in which modeling situations an ODCM technique can prove beneficial compared to a TCM technique. More specifically, we asked ourselves if there exist any meaningful differences in the resulting conceptual model and the effort spent to create such model between novice modelers trained in an ontology-driven conceptual modeling technique and novice modelers trained in a traditional conceptual modeling technique. To answer this question, we discuss previous empirical research efforts and distill these efforts into two hypotheses. Next, these hypotheses are tested in a rigorously developed experiment, where a total of 100 students from two different Universities participated. The findings of our empirical study confirm that there do exist meaningful differences between adopting the two techniques. We observed that novice modelers applying the ODCM technique arrived at higher quality models compared to novice modelers applying the TCM technique. More specifically, the results of the empirical study demonstrated that it is advantageous to apply an ODCM technique over an TCM when having to model the more challenging and advanced facets of a certain domain or scenario. Moreover, we also did not find any significant difference in effort between applying these two techniques. Finally, we specified our results in three findings that aim to clarify the obtained results. (C) 2018 Elsevier Ltd. All rights reserved.This research has been funded by the Ghent University Special Research Fund (BOF 01N02014) and the National Bank of Belgium.Verdonck, M.; Gailly, F.; Pergl, R.; Guizzardi, G.; Franco Martins, B.; Pastor López, O. (2019). Comparing traditional conceptual modeling with ontology-driven conceptual modeling: An empirical study. Information Systems. 81:92-103. https://doi.org/10.1016/j.is.2018.11.009S921038

    Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality

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    Welcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants

    Putting the past in place : a conceptual data model for a 4D archaeological GIS

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