Bednar, Kathrin, Winkler, Till. 2020. Ontologies and knowledge graphs: A new way to represent and communicate values in technology design. In: Societal challenges in the smart society, Hrsg. Mario Arias-Oliva, Jorge Pelegrín-Borondo, Kiyoshi Murata, Ana María Lara Palma, 257-269. Logroño: Universidad de La Rioja.

RIS

@INBOOK{Bednar2020,
title = {Ontologies and knowledge graphs: A new way to represent and communicate values in technology design},
author = {Kathrin Bednar and Till Winkler},
publisher = {Universidad de La Rioja},
year = {2020},
isbn = {978-84-09-20273-7},
address = {Logroño},
url = {https://dialnet.unirioja.es/servlet/libro?codigo=769585},
publisher = {Universidad de La Rioja},
language = {EN},
pages = {257-269},
series = {Societal challenges in the smart society},
abstract = {A promising pathway towards an ethically aligned design of technology is to consider human values such as “privacy” and “autonomy” in the design process. Value-oriented approaches have inspired the development of several unique methods for identifying stakeholders, values, and design requirements. However, none of these methods focus solely on the representation of values and the communication of value knowledge. In this paper, we outline a methodology that is inspired by techniques from the semantic web community. Based on a case study, we demonstrate how building an ontology can be used to represent and visualize value knowledge. The underlying empirical data comes from a sample of students who applied Value-based Engineering to elicit and analyse values for a telemedicine communication system. In spite of the specifics of this case study, the techniques for representing and communicating the resulting value data are compatible with any value-oriented approach. Furthermore, they support quality criteria that are essential when dealing with values both in research and design. The formal representation of value knowledge in form of semantic data ensures a high level of detail while respecting context-specificity. The underlying ontology helps to represent key concepts and their relations and supports the transparency of data analysis, including the initial coding of the value-related data. The resulting knowledge base can be shared with stakeholders and researchers, supporting the joint evolution of value-oriented approaches and technology.},
}