2. Styles Verbose or cryptic, flowery or plain, poetic or literal Conventions important – reduce the effort required from readers Disregarding conventions – may distract from the message ( unless that is the message)

3. Science Writing Prosaic Clear, accurate, but not dull Economy – every sentence necessary but not to the point of over condensing Ego less – you are writing for the readers not yourself

4. Scientific Tone Objective and accurate To inform not entertain Do not over qualify – modify every claim with caveats and cautions Never use idioms like “crop up”, “loose track”, “it turned out that”, etc. Use examples if they aid in clarification

5. Scientific Motivation Brief summaries at the beginning and end of each section The connection between one paragraph and the next should be obvious Make sure your reader has sufficient knowledge to understand what follows

6. Other Writing Issues The upper hand – inclusion of offhanded remarks like “ …this is a straightforward application …” Write for your dullest readers, as an equal Obfuscation – aim is to give an impression of having done something without actually claiming to have done it Analogies – only worthwhile if it significantly reduces the work of understanding, most of the time bad analogies lead the reader astray

7. Writing Issues Straw men – indefensible hypothesis posed for the sole purpose of being demolished “it can be argued that databases do not require indexes” Also use to contrast a new idea with some impossibly bad alternative, to put the new idea in a favorable light

8. Reference and Citation Carefully relate their new work to existing work, show how their work builds on previous knowledge, and how it differs from other relevant results. References – demonstrate the claims of new, knowledge of the research area, pointers to background reading

9. References Up-to-date Relevant (no padding) Original source First order: books and journal articles Second order: conference article Third order: technical report No private communications or forums ( material cannot be accessed or verified) if you must leave as a footnote not in the bibliography Do not cite support for common knowledge

10. References Careful wording is required when you restate other work. Robinson’s theory suggests that fast access is possible, but he did not perform experiments to confirm his results[22]. Much better Robinson’s theory suggest that fast access is possible [22], but as yet there is no experimental confirmation

11. Unsubstantiated Claims Most user prefer the graphical style of interface. to We believe that …. Another possibility would be a disk-based method, but this approach is unlikely to be successful. Another …, but our experience suggests that …

12. Citation Style References should not be anonymous Other work [6] -> Marsden [6] has … In self-references, readers should know that you are using yourself to support your argument not independent authorities Avoid unnecessary discussion of references, Several authors …., we cite …

13. Citation style Ordinal-number style, name-and-date style, superscripted ordinal numbers, and strings. Use anyone, but use one! Entries ordered –By appearance of citation –alphabetically

14. Quotation Text from another source If short – enclosed in double quotes If long – set aside in an indented block Long quotations, full material, algorithms, figures may require permission from the publisher and from the author of the original Use of quotes for other reasons is not recommended

15. Acknowledgements Anyone who made a contribution Advice, proofreading, technical support, funding resources Don’t list your family, unless they really contributed to the scientific contents

16. Ethics Not present opinions as fact Distort truths Plagiarize Imply that previously published results are original Papers available on the internet – authors put out an informal publication and becomes accepted as a formal. It is expected that the informal version will be removed

18. Titles Titles should be concise and informative A New Signature File Scheme based on Multiple- Block Descriptor Files for Indexing Very Large Data Bases (better) Signature File Indexes Based on Multiple- Block Descriptor Files An Investigation of the Effectiveness of Extensions to Standard Ranking Techniques for Large Text Collections (better) Extensions to Ranking Techniques for Large Text Collections

19. Opening Paragraphs Begin well Most care with the opening Bad openings –This paper concerns –In this paper Distinguish description of existing knowledge from the description of the paper’s contribution

20. Paragraphing Discussion of a single topic or issue Long paragraphs can be an indication that the author has not disentangled his thoughts Readers pay attention to the first lines and last Link paragraphs by reuse of key words or phrases

21. Lists Good, but don’t overuse, only for important information A list of trivia can be more attention grabbing than a paragraph of important information

22. Sentences Simple structure, a line or two long Avoid nested structures In the first stage, the backtracking tokenizer with a two-element retry buffer, errors, including illegal adjacencies as well as unrecognized tokens, are stored on a error stack for collation in to a complete report. (better) The first stage is the backtracking tokenizer with a two-element retry buffer. In this stage possible errors include illegal adjacencies as well as unrecognized tokens; when detected, errors are stored on a stack for collation into a complete report

23. Repetition and Parallelism Text that consists of the same form of sentence used again and again is monotonous. Careful with however, moreover, therefore, hence, thus, and, but and then Complementary (antonyms) concepts should be explained as parallels Access is fast, but at the expense of slow update (better) Access is fast but update is slow

24. Direct Statements The following theorem can now be proved (active) We can now prove the following theorem. Artificial use of verbs Tree structures can be utilized for dynamic storage of terms. Terms can be stored in dynamic tree structures (watch – perform, utilize, achieve, conducted, occurred)

25. Direct Statements “we show” In this paper it is shown that The authors show (Here we can help explain to the reader who is making the contribution) Other times we should not be used When we conducted the experiment it showed that our conjecture was correct (correct) The experiment showed that our conjecture was correct

26. Ambiguity Check carefully The compiler did not accept the program because it contained errors. (better) The program did not compile because it contained errors

27. Qualifiers One per sentence ( might, may, perhaps, possible, likely) It is perhaps possible that the algorithm might fail on unusual input. (better) The algorithm might fail on unusual input.

28. Padding The fact that In general In any case Remove these

29. Misused Words Watch for Which, that, the May, might, can –may is for personal choice –can to indicate capability Less, few –less, continuous quantities (space) –Fewer, discrete quantities (errors)

30. Misused Words Affect, effect –Effect – consequence of an action –Affect – influence, as in outcomes Alternate, alternative, choice –Alternate – switch between –Alternative – something that can be chosen –Choice – more than one alternative –Note, if there is but one alternative, there is no choice More on page 50-51 in Writing for CS

31. Overuse of Words Same word in the same sentence is annoying. Redundancy Adding together -> adding After the end of -> after In the region of -> approximately See list on page 55

32. Tense Most text past or present Present used for eternal truths –The algorithm has complexity … not the algorithm had complexity In references may have to past tense as also in describing work and outcomes –… the ideas were tested ….

33. Others Abbreviations - best none Acronyms – use CPU not C.P.U –Limit – may confuse reader Sexist language – get rid of pronouns and recast the sentence

35. Purpose of the Problem Statement Your statement of the problem Represents the reason behind your proposal It specifies the condition(s) you want to change Supported by evidence Show your familiarity with prior research on the topic Even if the problem is obvious, your reviewers want to know how clearly you can state it

36. 5 Key Questions to Answer in Your Problem Statement Does your problem statement: –Demonstrate a precise understanding of the problem you are attempting to solve? –Clearly convey the focus of your project early in the narrative? –Indicate the relationship of your project to a larger set of problems and justify why your particular focus has been chosen?

37. 5 Key Questions to Answer in Your Problem Statement Does your problem statement –Demonstrate that your problem is feasible to solve? –Make others what to read it further?

38. Writing Tips for Problem Statement Do not paint the problem in general terms: –“little is known about..” – “no research has dealt with..” Usually arguing for something that isn’t make for a weak need statement Instead explain the consequences of the information void For example, if you want to buy computers for your school, talk about happy, computer-literate students who will benefit in the future.

39. Purpose of the Research Objectives Section Specify the outcome of your project, the end product(s) Keep you objectives S-I-M-P-L-E* Specific – indicate precisely what you intend to change through your project Immediate – indicate a time frame Measurable –what you accept as proof of project success A Guide to Proposal Planning and Writing, Mary Miner

40. Purpose of the Research Objectives Section Practical – indicate how each objective is a real solution to a real problem Logical – how each objective contributes to systematically to achieving your overall goal E valuable – indicate how much change has to occur for the project to be effective A Guide to Proposal Planning and Writing, Mary Miner

41. Purpose of the Research Objectives Section For example: given the goal of improving software estimations, a proposal objective might be To produce an effort estimation model [specific][practical] that produces estimates to within 20% [E valuable] of actual, 80% [logical] of the time.[Measurable]

42. 5 Key Questions to Answer Does this section –Clearly describe your project’s objective, hypotheses and/or research question? –Bury them in a morass of narrative? –Demonstrate that your objectives are important, significant and timely? –Include objectives that comprehensively describe the intended outcomes of the project? –State objectives, hypothesis or questions in a way they can be evaluated or tested later

43. Writing Tips for Objectives Section Don’t confuse your objectives (ends) with you methods (means). A good objective emphasizes what will be done, whereas a method will explain why or how it will be done. Include goals (ultimate) and objectives (immediate)

44. Purpose of the Research Design Data Analysis Section Describes your project activities in detail Indicates how your objective will be accomplished Description should include the sequence, flow, and interrelationship of activities It should discuss the risks of your method, and indicate why your success is probable Relate what is unique about your approach.

45. Data Analysis If the objectives and design of your proposal are precise, you are well on your way to completing the data analysis protocol. Data Analysis is essentially a four step process 1.Identify precisely what will be evaluated. If you wrote measurable objectives, you already know. 2.Determine the methods used to evaluate each objective. More precisely, you will need to describe the information you will need and how you propose to collect it.

46. Data Analysis 3. Specify the analyses you plan to make and the data you need to collect. Your design may be simply to observe behavior of a particular population or something more complex like a rigorous experimental and multiple control group design. 4. Summarize the resulting data analyses and indicate its use. Consider using mock data tables that show what your resulting data might look like.

47. An Entire Study Outline Look again at pages 149 and 150, notice that the outline of the study -> it is an instantiation of the generic proposal. Notice the review section, it has subheadings according to the study of cartographers. Also read carefully the Data Analysis given on pages141-149

48. Key Questions to Answer Does the research design and data analysis section Describe why analysis is needed in the project? Clearly identify the purpose of your analysis? Demonstrate that an appropriate analysis procedure is included for each project objective Provide a general organizational plan or model? Demonstrate what information will be needed to complete the analysis, the potential sources and the instruments that will be used to collect it.

49. Writing Tips Begin with your objectives Describe the precise steps you will follow to carry out each objective, including what will be done, and who will do it. Keep asking and answering the “What’s next?” question. Once you have determined the sequence of events, cast the major milestones into a time-and-task chart