Chapter 1 Introduction PDF

Chapter 1 Introduction This writing seemeth to me … not much better than the noise or sound which musicians make while they are in tuning their instruments. Francis Bacon The Advancement of Learning No tale is so good that it can’t be spoiled in the telling. Proverb Writing plays many roles in sc...

Chapter 1 Introduction This writing seemeth to me … not much better than the noise or sound which musicians make while they are in tuning their instruments. Francis Bacon The Advancement of Learning No tale is so good that it can’t be spoiled in the telling. Proverb Writing plays many roles in science. We use it to record events and clarify our thinking. We use it to communicate to our colleagues, as we explain concepts and discuss our work. And we use it to add to scientific knowledge, by contributing to books, journals, and conference proceedings. Unfortunately, many researchers do not write well. Bacon’s quote given above was made four hundred years ago, yet applies to much science writing today. Perhaps we should not always expect researchers to communicate well; surely the skills required for science and writing are different. But are they? The best science is based on straightforward, logical thinking, and it isn’t rich, artistic sentences that we expect in a research paper—we expect readability. A scientist who can conceive of and explore interesting ideas in a rigorous way should be able to use much the same skills to solve the problem of how to explain and present those ideas to other people. However, many researchers undervalue the importance of clarity, and underestimate the effort required to produce a high-quality piece of writing. Some researchers seem content to write badly, and perhaps haven’t considered the impact of poor writing on their readers, and thus on their own careers. A research paper can remain relevant for years or even decades and, if published in a major journal or conference, may be read by thousands of students and researchers. Everyone whose work is affected by a poorly written paper will suffer: ambiguity leads to misunderstanding; omissions frustrate; complexity makes readers struggle to reconstruct the author’s intention. Effort used to understand the structure of a paper or the syntax of its sentences is effort not used to understand its content. And, as the proverb tells us, no tale is so good that it can’t be spoiled in the telling. Irrespective of the importance and validity of a paper, it cannot be convincing if it is difficult to understand. The more important © Springer-Verlag London 2014 J. Zobel, Writing for Computer Science, DOI 10.1007/978-1-4471-6639-9_1 1 2 1 Introduction the results—or the more startling or unlikely they seem—the better the supporting arguments and their presentation should be. Remember that, while you have months or years to prepare your work, reviewers and examiners often have no more than hours and may have rather less. You need to help them to spend their time well. For writing about science to be respected, a researcher must have something of value to say. A paper or thesis reports on research undertaken according to the norms of the field, to a standard that persuades a skeptical reader that the results are robust and of interest. Thus the written work rests on a program of activity that begins with interesting questions and proceeds through a sound methodology to clear results. Few researchers are instinctive writers, and few people are instinctive researchers. Yet it is not so difficult to become a good writer. Those who do write well have, largely, learnt through experience. Inexperienced researchers can produce competent papers by doing no more than follow some elementary steps: create a logical organization, use concise sentences, revise against checklists of possible problems, seek feedback. Likewise, the skills of research must be learnt, and early attempts at investigation and experimentation are often marked by mistakes, detours, and fumbling; but, as for writing, competent work can be produced by appreciating that there is a more or less standard template that can be followed, and then using the template to produce a first research outcome. Most researchers find that their work improves through practice, experience, and willingness to continue to reflect and learn. This observation certainly applies to me. I’ve continued to develop as a writer, and today produce text much more quickly— and with better results—than when I wrote the second edition a decade ago. I’m also a better scientist, and, looking back just a few years, am aware of poor research outcomes that are due to mistakes I would not make today. In my experience, most scientists develop a great deal as they proceed through their careers. Kinds of Publication Scientific results can be presented in a book, a thesis, a journal article, a paper or extended abstract in a conference or workshop proceedings, or a manuscript. Each kind of publication has its own characteristics. Books—the form of publication that undergraduates are the most familiar with—are usually texts that tend not to contain new results or provide evidence for the correctness of the information they present. The main purpose of a textbook is to collect information and present it in an accessible, readable form, and thus textbooks are generally better written than are papers. The other forms of publication are for describing the outcomes of new research. A thesis is usually a deep—or even definitive—exploration of a single problem. Journals and conference proceedings consist of contributions that range from substantial papers to extended abstracts. A journal paper is typically an end product of the research process, a careful presentation of new ideas that has been revised (sometimes over several iterations) according to referees’ and colleagues’ suggestions and criticisms. A paper or extended abstract in conference proceedings can likewise be an end-product, but conferences are also used to report work in progress. Conference Kinds of Publication 3 papers are usually refereed, but with more limited opportunities for iteration and revision, and may be constrained by strict length limits. There is no universal definition of “extended abstract”, but a common meaning is that the detail of the work is omitted. That is, an extended abstract may review the results of a research program, but may not include enough detail to make a solid argument for the claims. In contrast to books—which can reflect an author’s opinions as well as report on established scientific knowledge—the content of a paper must be defended and justified. This is the purpose of reviewing: to attempt to ensure that papers published in a reputable journal or conference are trustworthy, high-quality work. Indeed, in a common usage a published paper is distinguished from a mere paper by having been refereed. A typical research paper consists of the arguments, evidence, experiments, proofs, and background required to support and explain a central hypothesis. In contrast, the process of research that leads to a paper can include uninteresting failures, invalid hypotheses, misconceptions, and experimental mistakes. With few exceptions these do not belong in a paper. While a thesis might be more inclusive, for example if the author includes a critical reflection on how the work developed over the course of a Ph.D., such material would usually be limited to mistakes or failures that are genuinely illuminating. A paper or thesis should be an objective addition to scientific knowledge, not a description of the path that was taken to the result. Thus “style” is not just about how to write, but is also about what to say. Writing, Science, and Skepticism Science is a system for accumulating reliable knowledge. Broadly speaking, the process of science begins with speculation, observation, and a growing understanding of some idea or phenomenon. This understanding is used to shape research questions, which in turn are used to develop hypotheses that can be tested by proof or experimentation. The results are described in a paper, which is then submitted for independent review before (hopefully) being published; or the results are described in a thesis that is then submitted for examination. Writing underpins the whole of the research cycle. A key aspect of writing is that the discipline of stating ideas as logical, organized text forces you to formulate and clarify your thoughts. Concepts and ideas are made concrete; the act of writing suggests new concepts to consider; written material can be systematically discussed and debated with colleagues; and the only effective way to develop complex arguments or threads of reasoning, and evaluate whether they are robust, is to write them down. That is, writing is not the end of the research process, but instead shapes it. Only the styling of a paper, the polishing process, truly takes place after the research is complete. Thus the ability to write well is a key skill of science. Like many aspects of research, writing can only be thoroughly learnt while working with other researchers. Too often, however, the only help a novice receives is an advisor’s feedback on drafts of papers. Such interaction can be far from adequate: many researchers have little 4 1 Introduction experience of writing extended documents, and may be confronting the difficulties of writing in English when it is not their first language. It is not surprising that some researchers struggle. Many are intimidated by writing, and avoid it because describing research is less entertaining than actually doing it. For some advisors, the task of helping a student to write well is not one that comes naturally, and can be a distraction from the day-to-day academic work of research and teaching. Yet writing defines what we consider to be knowledge. Scientific results are only accepted as correct once they are refereed and published; if they aren’t published, they aren’t confirmed.1 Each new contribution builds on a foundation of existing concepts that are known and, within limits, trusted. New research may be wrong or misguided, but the process of reviewing eliminates some work of poor quality, while the scientific culture of questioning ideas and requiring convincing demonstrations of their correctness means that, over time, weak or unsupported concepts are forgotten. A unifying principle for the scientific culture that determines the value of research is that of skepticism. Within science, skepticism is an open-minded approach to knowledge: a researcher should accept claims provisionally given reasonable evidence and given agreement (or at least absence of contradiction) with other provisionally accepted claims. A skeptic seeks the most accurate description or solution that fits the known facts, without concern for issues such as the need to seek favour with authorities, while suspending judgement until decisive information is available. Effective research programs are designed to seek the evidence needed to convince a reasonable skeptic. Absolute skepticism is unsustainable, but credulity—the willingness to believe anything—is pointless, as, without some degree of questioning, it is impossible for knowledge to progress. Skepticism is key to good science. For an idea to survive, other researchers must be persuaded of its relevance and correctness—not with rhetoric, but in the established framework of a scientific publication. New ideas must be explained clearly to give them the best possible chance of being understood, believed, remembered, and used. This begins with the task of explaining our ideas to the person at the next desk, or even to ourselves. It ends with publication, that is, an explanation of results to the research community. Thus good writing is a crucial part of the process of good science. Using This Book There are many good general books on writing style and research methods, but the conventions of style vary from discipline to discipline, and broad guidance on science writing can be wrong or irrelevant for a specific area. Some topics—such as algorithms, mathematics, and research methods for computer science—are not discussed in these books at all. The role of this book is to help computer scientists with their writing and research. For novices, it introduces the elements of a scientific paper and reviews a wide range 1 Which is why codes of scientific conduct typically require that scientists not publicize their discoveries until after the work has been refereed. Using This Book 5 of issues that working researchers need to consider. For experienced researchers, it provides a reference point against which they can assess their own views and abilities, and is an exposure to wider cultures of research. This book is also intended to encourage reflection; some chapters pose questions about research that a responsible researcher should address. Nobody can learn to write or become a researcher just by reading this book, or indeed any book. To become competent it is necessary to practice, that is, to do research and write it up in collaboration with experienced researchers. However, familiarity with the elements of writing and research is essential in scientific training. Style is in some respects a matter of taste. The advice in this book is not a code of law to be rigidly obeyed; it is a collection of guidelines, not rules, and there are inevitably situations in which the “correct” style will seem wrong. But generally there are good reasons for writing in a certain way. Almost certainly you will disagree with some of the advice in this book, but exposure to another opinion should lead you to justify your own choice of style, rather than by habit continue with what may be poor writing. A good principle is: By all means break a rule, but have a good reason for doing so. Most computer scientists can benefit from reading a book about writing and research. This book can be used as the principal text for a senior research methods subject, or for a series of lectures on the practice of research. Such a subject would not necessarily follow this book chapter by chapter, but instead use it as a resource. In my own teaching of research methods, lectures on writing style seem to work best as introductions to the key topics of good writing; talking students through the detailed advice given here is less effective than getting them to read the book while they write and undertake research for themselves. That said, for a range of topics—figures, algorithms, presentations, statistics, reading and reviewing, drafting, ethics, and experimentation, for example—the relevant chapter can be used as the basis of one or two lectures. This book covers the major facets of writing and experimentation for research in computer science: • Commencing a research program, including getting started on the research and the writing (Chap. 2), reading and reviewing (Chap. 3), and principles of hypotheses, research questions, and evidence (Chap. 4). • Organization of papers and theses, and the practice of writing (Chap. 5). • Good writing, including writing style (Chaps. 6–8), mathematical style (Chap. 9), presentation of algorithms (Chap. 10), design of figures and graphs (Chap. 11), expert writing for other professional contexts (Chap. 12), and final editing (Chap. 13). • Research methodology, including experimentation (Chap. 14) and statistical principles (Chap. 15). • Presentations, including talks and posters (Chap. 16). • Ethics (Chap. 17). There are also exercises to help develop writing and research skills. 6 1 Introduction If you are new to research, Chaps. 2–5 may be the right place to begin. Note too that much of the book is relevant to writing in computer science in general, in particular Chaps. 6–13. While the examples and so on are derived from research, the lessons are broader, and apply to many of the kinds of writing that professionals have to undertake. This book has been written with the intention that it be browsed, not memorized or learnt by rote. Read through it once or twice, absorb whatever advice seems of value to you, then consult it for specific problems. There are checklists to be used as a reference for evaluating your work, at the ends of Chaps. 2, 4, 5, and 12–17, and, to some extent, all of the chapters are composed of lists of issues to check. Some readers of this book will want to pursue topics further. There are areas where the material is reasonably comprehensive, but there are others where it is only introductory, and still others where I’ve done no more than note that a topic is important. For most of these, it is easy to find good resources on the Web, which is where I recommend that readers look for further information on, for example, statistical methods, human studies and human ethics, and the challenges that are specific to authors whose first language is not English. Earlier editions of this book included bibliographies. These rapidly dated, and, with many good reading lists online—and new materials appearing all the time— I suggest that readers search for texts and papers on topics of interest, using the online review forums as guides. There are many home pages for research methods subjects, on research in general and in the specific context of computing, where up-to-date readings can be found. Spelling and Terminology British spelling is used throughout this book, with just a couple of quirks, such as use of “program” rather than “programme”. American readers: There is an “e” in “judgement” and a “u” in “rigour”—within these pages. Australian readers: There is a “z” in “customize”. These are choices, not mistakes. Choice of terminology is less straightforward. An undergraduate is an undergraduate, but the American graduate student is the British or Australian postgraduate. The generic “research student” is used throughout, and, making arbitrary choices, “thesis” rather than “dissertation” and “Ph.D.” rather than “doctorate”. The academic staff member (faculty in North America) who works with—“supervises”—a research student is, in this book, an “advisor” rather than a “supervisor”. Collectively, these people are “researchers” rather than “scientists”; while “computer scientists” are, in a broad sense, not just researchers in the discipline in computer science but people who are computational experts or practitioners. Researchers write articles, papers, reports, theses, extended abstracts, and reviews; in this book, the generic term for these forms of research writing is a “write-up”, while “paper” is used for both refereed publications and for work submitted for reviewing, and, sometimes, for theses too. Spelling and Terminology 7 Some of the examples are based on projects I’ve been involved in. Most of my research has been collaborative; rather than use circumlocutions such as “my colleagues and I”, or “together with my students”, the simple shorthand “we” is used to indicate that the work was not mine alone. Many of the examples of language use are drawn from other people’s writing; in some cases, the text has been altered to disguise its origin.