October 6, 2011

 Scientific Writing  Abstracts & Executive Summaries  Calculations & Equations  Tables & Figures

When writing scientific materials, word choice and structure are critical to clear communication. Seek simple language over more verbose phrasing Avoid vague language Use “transition language” Keep the subject and verb early in a sentence Supply grounding information before transitioning to new information Ensure that terms used in the development of claims are consistent with the strength of evidence Emphasize keywords and avoid ambiguity Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009.

“It is necessary that…”  “must” “It is possible that…”  “probably” “In order to…”  “to” “For the purpose of…”  “for” “So that …”  “so” Source: Gunning, R. “New Guide to More Effective Writing in Business and Industry,” Farnsworth Publishing, Boston, MA, 1962, p. 5-25, 7-15.

“The increase of heat influences settling time…” “…the effect of certain organisms on petroleum….” Watch-outs: …under some conditions… …these situations… …can influence… …will modify… …may affect… Source: Gunning, R. “New Guide to More Effective Writing in Business and Industry,” Farnsworth Publishing, Boston, MA, 1962, p. 5-33

Technical writing often involves statements of conclusion, and their significance depends on the language used. [Evidence] Claims often take the following form… that [Claim] proves demonstrates indicates appears suggests is was will be can may be Balance the strength of the claim with the strength of the evidence Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009.

 Provide clarity by thinking about the “ladder of abstraction” EXAMPLE Energy Source Fuel Liquid Fuel Gasoline Hexane How narrow or broadly applicable are your views or conclusions? Source: Gunning, R. “New Guide to More Effective Writing in Business and Industry,” Farnsworth Publishing, Boston, MA, 1962, p. 5-29

 What are “keywords” in your discipline or focus area? Discipline Methods Context Geotechnical Engineering Education Spectroscopy Monte Carlo Simulation Method of Sections Observational Research Case-based Instruction In-situ Experimental Theoretical Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009.

 Titles should be concise, employ keywords, and convey a message about the contents and value of the manuscript. Provide relevant information in a concise format Use audience-targeting keywords Consider the “form” of your title, and its implications Employ unambiguous language Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009.

“An introduction to ground penetrating radar” - Baker, G.S., Jordan, T.E., and Pardy, J., Geological Society of America Special Papers, 432, “Real-time measurement of soil attributes using on-the-go near infrared reflectance spectroscopy.” - Christy, C.D.,, Computers and Electronics in Agriculture, 61, “Noun-phrase” “Calcium addition improves salinity tolerance of tomatoes” - (Cargill & O’Connor, pg. 63) “Time-resolved Raman spectroscopy provides a cost-effective alternative to ion-selective electrodes for nitrogen analysis” “Statement” “Question” “Will SERS substrates improve spectroscopic analysis?” “Can aqueous sensor biofouling be prevented through controlled UV radiation exposure?” Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009.

 The value of abstracts: Provide a concise summary of manuscript contents to enable rapid article selection by readers May be the only aspect of your work available to readers without access to main sources of literature Often a core component of keyword search algorithms Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009.

The primary elements of an abstract : BPMRC BackgroundPurposeMethodsConclusionsResults Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009, p. 65.

form of "to be" + past participle = passive voice Passive sentences: ACTIVE  Why did the chicken cross the road? PASSIVE  Why was the road crossed by the chicken? ACTIVE  They speak English. PASSIVE  English is spoken ACTIVE  I completed the experiment. PASSIVE  The experiment was completed. Passive voice often stems from attempts to avoid using 1 st person

When planning the summary, consider the following: ◦ Subject and purpose of the project ◦ Research approach used ◦ Topics covered ◦ Essential background ◦ Results ◦ Conclusions ◦ Cost ◦ Anticipated implementation problems

The summary should  Target decision makers or readers who do not have time to read the full report  Target a non-technical audience, if necessary  Provide a more in-depth discussion of the report than the abstract

The summary should  Be longer than an abstract, usually 1- 1 ½ pages in length  Executive Summaries are Single-spaced, the report is usually double spaced  Focus on conclusions, recommendations and financial implications of the report

 Communication of equations and calculations should not be confused CALCULATIONSEQUATIONS Purpose Focus Communicate the process of utilizing equations in: - design - experimental analyses - theoretical analyses - development of arguments Convey the fundamental relationships between and/or relevance of variables in a system Highlight selection of variable values Describe rationale for design choices (e.g., values, use of equations) Illustrate manipulation of equations to achieve results Define key variables, and their units Define fundamental implications of equation form Provide insight into derivation Outcome Enable peer to assess and repeat analysis J. Sinfield CE 399, Spring 2011

Define all variables and units! ε =strain (in./in.) d =total elongation (in.) L= original length (in.) When communicating equations … Don’t assume the reader knows your field or the phenomenon you are discussing

Present calculations in the order in which they were performed Call out all specifications, design criteria, assumptions, equations, variables, values, and units Use figures as necessary to clarify design / calculation logic Thoroughly document all sources of design inputs Check your results manually or through well defined test cases Re-check units, for consistency and proper conversion Ensure that results pass a common sense check Have another qualified peer repeat your work Source: Sorby, S.A. and Bulleit, W.M. An Engineer’s Guide to Technical Communication, Pearson-Prentice Hall, 2006, 242 pp.

It can often be helpful to use datasheets or templates to ensure consistency in calculations But, make sure all assumptions related to templates remain true! Source: Sorby, S.A. and Bulleit, W.M. An Engineer’s Guide to Technical Communication, Pearson-Prentice Hall, 2006, pg. 129.

 Always annotate calculations to help a reader or reviewer understand your logic and design choices Source: Sorby, S.A. and Bulleit, W.M. An Engineer’s Guide to Technical Communication, Pearson-Prentice Hall, 2006, pg.135.

 People have challenged themselves to represent data graphically for centuries! Source: Delly, D., Jasperse, J., and Westbrooke, I. Designing science graphs for data analysisand presentation”, Department of Conservation Technical Series 32, Wellington New Zealand, 2005.

 Data may be presented in tables of figures FIGURES most useful for…TABLES most useful for… Highlighting a trend Emphasis on shape/pattern over actual numbers Enabling focused types of comparisons Documenting data Illustrating calculation components Showing actual/precise data values Allowing multiple types of comparisons (x-comp) Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009, p. 24.

Valuable to provide overview of multiple, unrelated variables Pie charts Column charts Radar charts Line charts Helpful when comparing three to four aspects of a phenomenon simultaneously Bubble chart The key question is “What story are you hoping to tell?” Effective for comparing proportions of a whole (use when “total” has significance) Helpful for sequence, trend, or time series information Useful for comparison of independent variables Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009, p. 24.; Mitra, B. K. Effective Technical Communication: A guide for Scientists and Engineers, Oxford University Press, 2006, Ch. 5.

Conveys the spread in a population of data Shows comparative fluctuation of difference between data sets/values Helps to visualize rate of change in data X-Y charts Frequency charts Net  chart Semi-log charts The key question is “What story are you hoping to tell?” Facilitate correlation analysis, typically between independent and dependent variables Source: Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009, p. 24.; Mitra, B. K. Effective Technical Communication: A guide for Scientists and Engineers, Oxford University Press, 2006, Ch. 5.

In addition, consider several design issues: On what aspect of the data would you like to place emphasis? What scale appropriately conveys your data? What intervals on the scale are important? How many data sets are you planning to present? How important is it to differentiate data sets? What overall range is pertinent to your data? What statistics are most meaningful? Source: Adapted from Cargill, M. and O’Connor, P. Writing Scientific Research Articles: Strategy and Steps, Wiley-Blackwell, West Sussex, UK, 2009, p. 24.

Source:

Manage scales to retain relevance and illuminate trends, rather than cloud them Remember several best practices when working with data:

Appropriately scale symbols for the graph Remember several best practices when working with data:

Don’t “connect” data that shouldn’t be “connected ” Remember several best practices when working with data :

Worse yet, don’t curve fit data that shouldn’t be curve fit

Avoid unnecessary grid lines, borders, and ink!

Use appropriate scales

Ensure scales are “equivalent” when discussing comparisons

Keep in mind that figures will likely be reduced for production Source: Paradis, J.G., and Zimmerman, M.L. “The MIT Guide to Science and Engineering Communication”, The MIT Press, 1997, p. 84.

Avoid the “lie” factor - Incongruent comparisons Source:

In tables… Avoid unnecessary lines and borders Align decimal points Use legible fonts Clearly identify headings Remember to annotate units and provide notes if needed Sort data if helpful to make an argument Include references Help the reader of related text navigate the table (e.g., with column headings)

 Makes good impression  Can be read selectively  Rational plan  Reads coherently and cumulatively  Anticipates readers questions  Discloses purpose & scope early  Written clearly without jargon

 Makes positive statement about writer & organization  Free of typographical and grammatical errors and misspelled words  Uses table & graphs appropriately  Has summary or conclusions when needed  Conveys authority, thoroughness, soundness, and honest work