Mixed reality participants in smart meeting rooms and smart home enviroments

Human–computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in a virtual meeting room, we discuss how remote meeting participants can take part in meeting activities and they have some observations on translating research results to smart home environments

Collective intelligence for OER sustainability

To thrive, the Open Educational Resource (OER) movement, or a given initiative, must make sense of a complex, changing environment. Since “sustainability” is a desirable systemic capacity that our community should display, we consider a number of principles that sharpen the concept: resilience, sensemaking and complexity. We outline how these motivate the concept of collective intelligence (CI), we give examples of what OER-CI might look like, and we describe the emerging Cohere CI platform we are developing in response to these requirements

Designing Traceability into Big Data Systems

Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.Comment: 10 pages; 6 figures in Proceedings of the 5th Annual International Conference on ICT: Big Data, Cloud and Security (ICT-BDCS 2015), Singapore July 2015. arXiv admin note: text overlap with arXiv:1402.5764, arXiv:1402.575

How Can You Verify that I Am Using AI? Complementary Frameworks for Describing and Evaluating AI-Based Digital Agents in their Usage Contexts

This essay explains complementary frameworks for understanding and managing AI in usage contexts. In contrast with broad generalizations about the nature and impact of AI, those frameworks focus on specific AI-based digital agents used by people and/or machines performing purposeful activities in business, home, or societal environments. The agent responsibility (AR) framework helps in describing roles and responsibilities of specific AI-based digital agents in their usage contexts. The agent evaluation (AE) framework identifies six criteria that different stakeholders might use for evaluating AI-based digital agents

A theoretical view on concept mapping

Auto‐monitoring is the pivotal concept in understanding the operation of concept maps, which have been used to help learners make sense of their study and plan learning activities. Central to auto‐monitoring is the idea of a ‘learning arena’ where individuals can manipulate concept representations and engage in the processes of checking, resolving and confirming understandings. The learner is assisted by familiar metaphors (for example, networks) and the possibility of thinking ‘on action’ while ‘in action’. This paper discusses these concepts, and concludes by arguing that maps are part of the process of learning rather than a manifestation of learning itself. Auto‐monitoring is suggested as an appropriate term to describe the process of engaging in the learning arena

An exploratory social network analysis of academic research networks

For several decades, academics around the world have been collaborating with the view to support the development of their research domain. Having said that, the majority of scientific and technological policies try to encourage the creation of strong inter-related research groups in order to improve the efficiency of research outcomes and subsequently research funding allocation. In this paper, we attempt to highlight and thus, to demonstrate how these collaborative networks are developing in practice. To achieve this, we have developed an automated tool for extracting data about joint article publications and analyzing them from the perspective of social network analysis. In this case study, we have limited data from works published in 2010 by England academic and research institutions. The outcomes of this work can help policy makers in realising the current status of research collaborative networks in England

The Role of Users in Prototypical and Infrastructural Systems Design

This theoretical study examines the role of users in an infrastructural systems design. We analyzed different perspectives and used theories on infrastructure, long-term factors in infrastructure, and the role of users in infrastructural systems design. By doing this we demonstrated how prototypical design has been used in infrastructural systems design and how the users’ role has been taken into account. This study summarizes infrastructuring modes, purposes, activities, and methods and also offers both theoretical and practical contributions. First, we offer a new view on prototypical design as it is conceptualized for infrastructural systems design. Second, as a practical contribution, this study provides valuable knowledge to end users and domain and information systems practitioners, especially regarding how information systems artefacts can contribute to infrastructural design and vice versa