An ontology for defining and characterizing demonstration environments

Nie, Wei and De Vita, Katharina and Masood, Tariq (2023) An ontology for defining and characterizing demonstration environments. Journal of Intelligent Manufacturing. ISSN 0956-5515 (https://doi.org/10.1007/s10845-023-02213-1)

[thumbnail of Nie-etal-JIM-2023-An-ontology-for-defining-and-characterizing-demonstration-environments]
Preview
 Text. Filename: Nie-etal-JIM-2023-An-ontology-for-defining-and-characterizing-demonstration-environments.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (2MB)| Preview

Abstract

Demonstration Environments (DEs) are essential tools for testing and demonstrating new technologies, products, and services, and reducing uncertainties and risks in the innovation process. However, the terminology used to describe these environments is inconsistent, leading to heterogeneity in defining and characterizing them. This makes it difficult to establish a universal understanding of DEs and to differentiate between the different types of DEs, including testbeds, pilot-plants, and living labs. Moreover, existing literature lacks a holistic view of DEs, with studies focusing on specific types of DEs and not offering an integrated perspective on their characteristics and applicability in different contexts. This study proposes an ontology for knowledge representation related to DEs to address this gap. Using an ontology learning approach analyzing 3621 peer-reviewed journal articles, we develop a standardized framework for defining and characterizing DEs, providing a holistic view of these environments. The resulting ontology allows innovation managers and practitioners to select appropriate DEs for achieving their innovation goals, based on the characteristics and capabilities of the specific type of DE. The contributions of this study are significant in advancing the understanding and application of DEs in innovation processes. The proposed ontology provides a standardized approach for defining and characterizing DEs, reducing inconsistencies in terminology and establishing a common understanding of these environments. This enables innovation managers and practitioners to select appropriate DEs for their specific innovation goals, facilitating more efficient and effective innovation processes. Overall, this study provides a valuable resource for researchers, practitioners, and policymakers interested in the effective use of DEs in innovation.

CORE (COnnecting REpositories)