Designing a User-Metaverse Interface for the Industrial-Metaverse

The Industrial-Metaverse will create interactions between the physical and virtual worlds to extend operations in the physical industry. This particularity and the demand for increasing immersion in the Metaverse require using XR technologies called User-Metaverse interfaces (UMI). How such a UMI must be designed for the industrial-Metaverse is unknown. This study adopts a design science approach to design a UMI based on social cognitive theory (SCT). According to SCT, creating user-generated Metaverse content is crucial to the UMI design. It empowers users to generate content through their efforts, leading to higher self-efficacy and user engagement. We formulate two theoretically based design principles and instantiate a software artifact, which we evaluate in a laboratory experiment with 57 participants. Our study shows the importance of belief in success in the design of future UMI. Furthermore, our design principles show significant positive outcome expectations of users in their interaction with the software artifact

Transdisciplinarity seen through Information, Communication, Computation, (Inter-)Action and Cognition

Similar to oil that acted as a basic raw material and key driving force of industrial society, information acts as a raw material and principal mover of knowledge society in the knowledge production, propagation and application. New developments in information processing and information communication technologies allow increasingly complex and accurate descriptions, representations and models, which are often multi-parameter, multi-perspective, multi-level and multidimensional. This leads to the necessity of collaborative work between different domains with corresponding specialist competences, sciences and research traditions. We present several major transdisciplinary unification projects for information and knowledge, which proceed on the descriptive, logical and the level of generative mechanisms. Parallel process of boundary crossing and transdisciplinary activity is going on in the applied domains. Technological artifacts are becoming increasingly complex and their design is strongly user-centered, which brings in not only the function and various technological qualities but also other aspects including esthetic, user experience, ethics and sustainability with social and environmental dimensions. When integrating knowledge from a variety of fields, with contributions from different groups of stakeholders, numerous challenges are met in establishing common view and common course of action. In this context, information is our environment, and informational ecology determines both epistemology and spaces for action. We present some insights into the current state of the art of transdisciplinary theory and practice of information studies and informatics. We depict different facets of transdisciplinarity as we see it from our different research fields that include information studies, computability, human-computer interaction, multi-operating-systems environments and philosophy.Comment: Chapter in a forthcoming book: Information Studies and the Quest for Transdisciplinarity - Forthcoming book in World Scientific. Mark Burgin and Wolfgang Hofkirchner, Editor

Entrepreneurship, Entry and Exit in Creative Industries: an explorative Survey

Series: Creative Industries in Vienna: Development, Dynamics and Potential

Experiential learning approach for requirements engineering education

The use of requirements engineering (RE) in industry is hampered by a poor understanding of its practices and their benefits. Teaching RE at the university level is therefore an important endeavor. Shortly before students become engineers and enter the workforce, this education could ideally be provided as an integrated part of developing the requisite business skills for understanding RE. Because much social wisdom is packed into RE methods, it is unrealistic to expect students with little organizational experience to understand and appreciate this body of knowledge; hence, the necessity of an experiential approach. The course described in this paper uses an active, affective, experiential pedagogy giving students the opportunity to experience a simulated work environment that demonstrates the social/design-problem complexities and richness of a development organization in the throes of creating a new product. Emotional and technical debriefing is conducted after each meaningful experience so that students and faculty, alike can better understand the professional relevancies of what they have just experienced. This includes an examination of the many forces encountered in industrial settings but not normally discussed in academic settings. The course uses a low-tech social simulation, rather than software simulation, so that students learn through interaction with real people, and are therefore confronted with the complexity of true social relationship

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

On Agent-Based Software Engineering

Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential to significantly improve the theory and the practice of modeling, designing, and implementing computer systems. Yet, to date, there has been little systematic analysis of what makes the agent-based approach such an appealing and powerful computational model. Moreover, even less effort has been devoted to discussing the inherent disadvantages that stem from adopting an agent-oriented view. Here both sets of issues are explored. The standpoint of this analysis is the role of agent-based software in solving complex, real-world problems. In particular, it will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level social interactions, and that can operate within flexible organisational structures