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Successful Scientific Writing
r 1 Successful scientific writing A step-by-step guide for the biological " LJ and medical sciences • < Second edition du Janice R. Matthews, 5 M John M. Bowen, and Robert W. Matthews J CAMBRIDGE UNIVERSITY PRESS =i; PUBLISHED BY THE PRESS SYNDICATE OF THE UNIVERSITY OF CAMBRIDGE The Pitt Building, Trumpington Street, Cambridge, United Kingdom CAMBRIDGE UNIVERSITY PRESS Contents The Edinburgh Building, Cambridge CB2 2RU, UK 40 West 20th Street, New York, NY 10011-4211, USA 477 Williamstown Road, Port Melbourne, VIC 3207, Australia Ruiz de Alarcon 13, 28014 Madrid, Spain Dock House, The Waterfront, Cape Town 8001, South Africa http://www.cambridge.org © Cambridge University Press 1996, 2000 Preface This book is in copyright. Subject to statutory exception xin and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. i 1 FROM START TO FINISH: THE BIG PICTURE 1-22 Scientific writing begins where research does — with a question 1 First published 1996 Second edition 2000 Keep the big picture in mind Reprinted 2001, 2003,2005 Periodically assess research progress and direction Organization is a journey, not a destination Printed in the United Kingdom at the University Press, Cambridge Use many different search strategies Make it easy to relocate relevant material Typeset in Ehrhardt 10 /12pt [v N] The message determines the medium A catalogue record for this book is available from the British Library What message do I want to convey? 3 Which format is most appropriate for my message? Library of Congress Cataloguing in Publication data 3 Who will be most interested in my message? Matthews, Janice R., 1943- Where should this paper be published? Successful scientific writing: a step-by-step guide for the biological and medical -a Evaluate journal suitability and impact sciences/Janice R. -
Essays in Personalizable Software
Gerry Stahl’s assembled texts volume #8 Essays in Personalizable Software Gerry Stahl Essays in Personalizable Software 2 Gerry Stahl's Assembled Texts 1. Marx and Heidegger 2. Tacit and Explicit Understanding in Computer Support 3. Group Cognition: Computer Support for Building Collaborative Knowledge 4. Studying Virtual Math Teams 5. Translating Euclid: Designing a Human-Centered Mathematics. 6. Constructing Dynamic Triangles Together: The Development of Mathematical Group Cognition 7. Essays in Social Philosophy 8. Essays in Personalizable Software 9. Essays in Computer-Supported Collaborative Learning 10. Essays in Group-Cognitive Science 11. Essays in PHilosopHy of Group Cognition 12. Essays in Online MatHematics Interaction 13. Essays in Collaborative Dynamic Geometry 14. Adventures in Dynamic Geometry 15. Global Introduction to CSCL 16. Editorial Introductions to ijCSCL 17. Proposals for ResearcH 18. Overview and Autobiographical Essays 19. Theoretical Investigations 20. Works of 3-D Form 21. Dynamic Geometry Game for Pods Essays in Personalizable Software 3 Gerry Stahl’s assembled texts volume #8 Essays in Personalizable Software Gerry Stahl Essays in Personalizable Software 4 Gerry Stahl [email protected] www.GerryStahl.net Copyright © 2011, 2021 by Gerry Stahl Published by Gerry Stahl at Lulu.com Printed in the USA ISBN: 978-1-329-85913-5 (ebook) ISBN 978-1-329-85917-3 (paperback) Essays in Personalizable Software 5 Introduction uch of my work in computer science at the University of Colorado in Boulder can be characterized as explorations of personalizable software. For M me, that term increasingly meant designing hypermedia systems that would allow people to explore information from different personal perspectives. -
A Hypermedia Inference Language As an Alternative to Rule-Based Expert Systems
A Hypermedia Inference Language as an Alternative to Rule-based Expert Systems Gerry Stahl Technical Report CU-CS-557-91 November 1991 revised August 1992 . An abriged version of this paper is forthcoming in: G. Stahl, R. McCall, G. Peper (1992) Extending Hypermedia with an Inference Language: An Alternative to Rule-based Expert Systems, Proceedings of the IBM Internal Technical Liaison Conference: Expert Systems (October 19-21, 1992). Department of Computer Science University of Colorado at Boulder Campus Box 430 Boulder, Colorado 80309-0430 USA phone: (303) 444-2792 e-mail: [email protected] Abstract This paper reports on the development of a hypermedia inference language designed to strengthen the ability of hypermedia systems to be used effectively in applications that might otherwise require cumbersome rule-based expert systems. The inference language grew out of a primitive query language which provided the mechanism for navigation in a hypertext system. As the language gained logical and computational capabilities it became increasingly embedded in the nodes and links. A new paradigm of intelligent hypermedia emerged, incorporating "smart" nodes and links that were dynamically computed by means of the inference language. The language itself provided an end-user programming facility that was English-like enough in appearance to be readily comprehensible to non-programmers. An application in the domain of academic advising was developed to compare the inferencing language approach to expert system alternatives. A Hypermedia Inference Language as an Alternative to Rule-based Expert Systems Overview of Report This paper reports on the development of a hypermedia inference language designed to strengthen the ability of hypermedia systems to be used effectively in applications that might otherwise require cumbersome rule-based expert systems. -
A Language for Research Information Definition Argumentation
I Riechert, M T 2017 RIDAL – A Language for Research Information Definition CODATA '$7$6&,(1&( S Argumentation. Data Science Journal, 16: 5, pp. 1–17, DOI: https://doi. U -2851$/ org/10.5334/dsj-2017-005 RESEARCH PAPER RIDAL – A Language for Research Information Definition Argumentation Mathias Thomas Riechert German Center for Higher Education Research and Science Studies, Germany [email protected] 1 Abstract Information about the research process is gaining importance for research documentation and evaluation. With the increased usage of such research information, the requirements for data quality and interpretation consistency are increasing. An agreed understanding of the concepts of research information is therefore crucial for fair science evaluation and science policy. Initiatives like euroCRIS and CASRAI address this by standardising research informa- tion definitions. In this paper, we present an approach to systematically develop and docu- ment not only definitions of research information, but also discussed alternatives and related arguments. With that we aim to support existing RI standardisation initatives with a flexible and scalable way of documenting and communicating the standardisation process in order to increase acceptance for the resulting definitions. Our contribution is threefold: Based on the widely used IBIS notation for argumentation modelling, we first introduce semantic rules for defining research information. Secondly, a transformation algorithm is provided to reduce the complexity of those argumentations – without the loss of information – and in turn improve readability of the diagrams. Thirdly, the semantic rules of the resulting less complex RIDAL notation are provided. The presented modelling notations are evaluated in the case setting of the standardisation project for research information of the German science system “Core Research Dataset”.