Collaborative Practices in Computer-Aided Academic Research

Collaborative Practices in Computer-Aided Academic Research

J. Leng (University of Manchester, UK) and Wes Sharrock (University of Manchester, UK)
DOI: 10.4018/978-1-61520-975-0.ch016
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Abstract

Chapter 16 focuses on sharing information through global communication systems in the context of computer-aided academic research: more specifically, on cross-disciplinary research primarily involving collaborations between natural scientists and colleagues in computational science. The authors interest lies in the visualization and high performance computing (HPC) communities, branches of computational science providing enhanced ways of organising, analysing and presenting materials, models and results of research in other disciplines.
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Introduction

We are interested in what constitutes ‘best practice’ for sharing data and developing softwares in cross-disciplinary research involving academics from (primarily, but not exclusively) natural sciences collaborating with colleagues in computational science. Computational science has existed since computers have in what used to be termed scientific computing, but as this practice diffuses into non-scientific disciplines that name does not fit so we term it computer-aided academic research.

Many collaborations involve software development and hence software engineering. Since the 1990’s there have been several attempts to define ‘best practice’ in software engineering: the IEEE Computer Society has developed a number of software engineering standards (Moore, 2005; Pfleeger et al 2005) and the IEEE-CS/ACM has created a Software Engineering Code of Ethics and Professional Practice (ACM & IEEE, 2009; Abran et al, 2004; Thyler & Dorfman, a2006; Thyler & Dorfman, b2006; IEEE Computer Society, 2009). However within UK scientific research researchers increasingly advocate open-source practices for developing and sharing software and data. There are also growing demands from those who manage funding and assessment of the national research budget to encourage as ‘best practice’ the adoption of professional software engineering standards. There are issues as to how accreditation of software engineering will interact with open-source approaches and also how they will impact on established conventions for evaluating academic achievements. Changes in measuring success will alter how careers are shaped and will further impact the form of collaboration between disciplines featuring significantly different standards of disciplinary achievement and professional success (as with natural and computational sciences).

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