Knowledge Engineering Experimentation Management System for Collaboration

The article of record as published may be located at http://dx.doi.org/10.1007/978-90-481-3658-2_100This paper presents a methodology and system for the analysis of complex experiments currently utilized by the Department of Defense. Assessed are effectiveness and efficiency of systems interactions and affected intra- and interorganizational processes. Methodology is derived from an operational experimentation analytics and management system designed to assess next-generation military e-services and infrastructure. A focus is the expansion of systems methodology beyond traditional transaction-oriented exchanges to include management layers for complex inter-organizational processes and mechanisms to accommodate sensitive company operations

Supporting collaboration within the eScience community

Collaboration is a core activity at the heart of large-scale co- operative scientific experimentation. In order to support the emergence of Grid-based scientific collaboration, new models of e-Science working methods are needed. Scientific collaboration involves production and manipulation of various artefacts. Based on work done in the software engineering field, this paper proposes models and tools which will support the representation and production of such artefacts. It is necessary to provide facilities to classify, organise, acquire, process, share, and reuse artefacts generated during collaborative working. The concept of a "design space" will be used to organise scientific design and the composition of experiments, and methods such as self-organising maps will be used to support the reuse of existing artefacts. It is proposed that this work can be carried out and evaluated in the UK e-Science community, using an "industry as laboratory" approach to the research, building on the knowledge, expertise, and experience of those directly involved in e-Science

What influences the speed of prototyping? An empirical investigation of twenty software startups

It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startups, how fast startups can learn depends on how fast they can prototype. Despite of the importance, there is a lack of research about prototyping in software startups. In this study, we aimed at understanding what are factors influencing different types of prototyping activities. We conducted a multiple case study on twenty European software startups. The results are two folds, firstly we propose a prototype-centric learning model in early stage software startups. Secondly, we identify factors occur as barriers but also facilitators for prototyping in early stage software startups. The factors are grouped into (1) artifacts, (2) team competence, (3) collaboration, (4) customer and (5) process dimensions. To speed up a startups progress at the early stage, it is important to incorporate the learning objective into a well-defined collaborative approach of prototypingComment: This is the author's version of the work. Copyright owner's version can be accessed at doi.org/10.1007/978-3-319-57633-6_2, XP2017, Cologne, German

Unpacking capabilities underlying design (thinking) process

Engineering graduates must know how to frame and solve non-routine problems. While design classes explicitly teach problem framing and solving, it is lacking throughout much of the rest of the engineering curriculum and is often relegated to capstone classes at the end of the students’ educational experience. This paper explores problem framing and solving through the lens of experiential learning theory. It captures core problem framing and solving approaches from critical, design and systems thinking and concludes with a table of learning outcomes that might be drawn upon in designing an engineering curriculum that more fully develops the problem framing and solving capabilities of its students

Performance measurement procedures that support innovativeness rather than hamper it

This paper addresses the contemporary challenges in increasing firm-level innovativeness and developing appropriate performance metrics. The authors discuss these challenges and provide a literature review on the innovation enhancing factors in service industries. They subsequently study the case of a multinational telecom company that tries to renew its innovative capabilities after a restructuring. An interpretative approach, based on employee focus group interviews and an extensive management workshop, is taken to co-develop context specific factors that enhance innovativeness. These factors include, amongst others, personal recognition and acknowledgement for an innovative achievement, available time, customer intimacy, and a clear innovation strategy. The identified factors will be used in a follow-up research aimed to develop performance measurement procedures that support the company to develop and exploit its innovative capabilities

Constructing a Virtual Training Laboratory Using Intelligent Agents

This paper reports on the results and experiences of the Trilogy project; a collaborative project concerned with the development of a virtual research laboratory using intelligence agents. This laboratory is designed to support the training of research students in telecommunications traffic engineering. Training research students involves a number of basic activities. They may seek guidance from, or exchange ideas with, more experienced colleagues. High quality academic papers, books and research reports provide a sound basis for developing and maintaining a good understanding of an area of research. Experimental tools enable new ideas to be evaluated, and hypotheses tested. These three components-collaboration, information and experimentation- are central to any research activity, and a good training environment for research should integrate them in a seamless fashion. To this end, we describe the design and implementation of an agent-based virtual laboratory

Networking Innovation in the European Car Industry : Does the Open Innovation Model Fit?

The automobile industry is has entered an innovation race. Uncertain technological trends, long development cycles, highly capital intensive product development, saturated markets, and environmental and safety regulations have subjected the sector to major transformations. The technological and organizational innovations related to these transformations necessitate research that can enhance our understanding of the characteristics of the new systems and extrapolate the implications for companies as well as for the wider economy. Is the industry ready to change and accelerate the pace of its innovation and adaptability? Have the traditional supply chains transformed into supply networks and regional automobile ecosystems? The study investigates the applicability of the Open Innovation concept to a mature capital-intensive asset-based industry, which is preparing for a radical technological discontinuity - the European automobile industry - through interviewing purposely selected knowledgeable respondents across seven European countries. The findings contribute to the understanding of the OI concept by identifying key obstacles to the wider adoption of the OI model, and signalling the importance of intermediaries and large incumbents for driving network development and OI practices as well as the need of new competencies to be developed by all players.Peer reviewe

Working at the edges

In this short article, the author explains how approaches to programme philosophy, curriculum structure and assessment design have liberated students to work creatively at the edges of their disciplines where they intersect with others. The article outlines the development of a Masters programme in Multidisciplinary Design Innovation

BIM adoption and implementation for architectural practices

Severe issues about data acquisition and management arise during the design creation and development due to complexity, uncertainty and ambiguity. BIM (Building Information Modelling) is a tool for a team based lean design approach towards improved architectural practice across the supply chain. However, moving from a CAD (Computer Aided Design) approach to BIM (Building Information Modelling) represents a fundamental change for individual disciplines and the construction industry as a whole. Although BIM has been implemented by large practices, it is not widely used by SMEs (Small and Medium Sized Enterprises). Purpose: This paper aims to present a systematic approach for BIM implementation for Architectural SMEs at the organizational level Design/Methodology/Approach: The research is undertaken through a KTP (Knowledge transfer Partnership) project between the University of Salford and John McCall Architects (JMA) a SME based in Liverpool. The overall aim of the KTP is to develop lean design practice through BIM adoption. The BIM implementation approach uses a socio-technical view which does not only consider the implementation of technology but also considers the socio-cultural environment that provides the context for its implementation. The action research oriented qualitative and quantitative research is used for discovery, comparison, and experimentation as it provides �learning by doing�. Findings: The strategic approach to BIM adoption incorporated people, process and technology equally and led to capacity building through the improvements in process, technological infrastructure and upskilling of JMA staff to attain efficiency gains and competitive advantages. Originality/Value: This paper introduces a systematic approach for BIM adoption based on the action research philosophy and demonstrates a roadmap for BIM adoption at the operational level for SME companie