Scientific communication and publishing
Course notes
Szeged, March 2012
Course teacher:
Gabor L. Lövei
Aarhus University, Flakkebjerg Res. Ctr., Slagelse, Denmark gabor.lovei@agrsci.dk
©Gabor Lövei, 2000-2011
ON COMMUNICATION
Introductory thoughts and exercise
ON LEARNING AND TOOLS TO HELP LEARNING
"Csak az olvassa versemet, ki ismer engem es szeret"
"Only reads my poem/Who knows me and who loves me"
Attila Jozsef, Hungarian poet (1905- 1937) The importance of positive attitude
Some famous experiments on learning
1. Bower & al. 1969. J. Verbal Learning & Verbal Behav. 8, 323-343.
4 cards, 28 words each
Group A – hierarchically ordered:
Instrument – strings violin
viola cello, etc.
brass instruments horn
tuba
saxophone etc.
Group B – same words, randomly
Test: recall ability. Result: Group A >> B
=> Structure aids recall
2. Anderson & Parlmutter's experiment in: Anderson, JR 1985. Cognitive psychology & its implications. Freeman & Co., San Francisco.
Central words given
Task: write as many free associations as you can, starting with a specified letter Group A: central word 1: dog – associations must start with letter c;
central word 2: bone – associations must start with m
Group B: central word 1: gambler – associations must start with letter c;
central word 2: bone – associations must start with m
Test: time for associative word 'meat' to emerge Time A << time B
(dog -> bone -> meat is on an easy associative link)
=> "Memory works by an activation process which spreads from word to associated word via these links"
3. Haber RN 1970. How we remember what we see. Scientific American 105, issue 5 Expt 1-
2560 photo slides shown, each for 10 s (takes 7 hours)
1 h after last slide 2560 photo pairs shown – 1 seen, 1 not seen Task: identify the slide seen previously
recognition precision 85 – 95%
Expt. 2 –
diff. set of 2560 slides, shown @rate 1 slide/ s
1 h after last slide 2560 photo pairs shown – 1 seen, 1 not seen Task: identify the slide seen previously
recognition precision – same 85-95%
Expt. 3 –
diff. set of 2560 slides, shown @rate 1 slide/ s
1 h after last slide 2560 photo pairs shown – 1 seen, 1 not seen, but – when presented the second time, mirror image of the original shown
Task: identify the slide seen previously recognition precision 85 – 95%
=> “Our recognition of pictures is essentially perfect"
How do we learn/acquire skills?
By doing things repeatedly & personally The importance of (early) repetition
short-term memory – long-term memory transition in relation to repetition
Howe MJA 1970. Using students notes’ to examine role of individual learner in acquiring meaningful subject matter. J. Educational Res. 64: 61.
Effectiveness of traditional notes (from worst to best):
- complete transcript given
- complete transcript personally taken - sentence summary notes given
- sentence summary notes personally taken
- key card notes given
- key card notes personally taken
Brevity, efficiency & active personal involvement are keys to learning The importance of taking notes personally
- active vs. passive listening - giving structure to information - repetition
- own effort/own expressions When taking notes:
DO:
- take personal notes (active vs. passive)
- use abbreviations (coding – mental process engaged) - use colour, hierarchy, letter size - to give structure to notes - use arrows, graphic symbols
DO NOT
- rely on ready-made notes even if they seem perfect - try to copy everything – cannot follow thoughts
- try to produce 'neat' notes, complete sentences, ordered appearance - switch off at familiar information ("nothing new, no need to focus") - engage in mental duel with the speaker – derails thinking
Some problems with standard notes - obscure key words
- difficult to remember
- waste time by - taking more unnecessary notes
− reading them
− searching for key words
− fail to stimulate creativity (written = done)
− difficult to link ideas
Structure aids recall => Give structure to information - Mind maps Some basic features ofmind maps:
- uses word, image, number, rhythm, logic, colour, spatial awareness - spatially structured information (>> linearly presented information) - free form
- personal
- aids complex information recall
- repetitive process
Advantages of mind maps Time saved by
writing only relevant words (50-95%) reading" "
reviewing mind map notes
not searching for key words among many Concentration on real issues
Key words more easily recognisable Easier to recall key words
Clear and appropriate association between key words Easier to remember (structure, colours, etc. to aid recall) Making MM - creative process, helps brain working
Buzan, Tony. 1995. The mind map book. BBC Books. ISBN 0-563-37101-3
1. THE SCIENTIFIC LITERATURE & SCIENTOMETRICS Why publish?
If a tree falls in a forest, and no one hears it - does it make a sound? - discuss
A short history - the development of modern scientific literature, from oral to regulated, written
Types of publications:
Thesis; MSc, PhD
articles: 'proper' article, = primary scientific publication short communication,
review article, invited article,
note, comment, letter,
paper for conference proceedings, book chapter,
book
report, yearbook, etc. etc.
Basic distinction: primary vs. non-primary publications Definition: the primary scientific publication is:
first disclosure of new scientific knowledge in accessible form (language, circulation, ref.
journals) that allows readers to repeat the experiments
Discussion of the definition “accessible”:
1. language - English
2. form - peer-reviewed journals vs. other forums (yearbooks, government publications, conference proceedings), circulation
3. accessibility for secondary publications (abstracting services) What is “peer-review”?
Written assessment of findings, their reliability and significance by peers Key to quality in scientific publications
Necessary to pass for publication Primary journal types:
Society journals – high level, good, accessible, widely circulated, non-profit. Peer review:
very good
Example: Journal of Animal Ecology, American Naturalist
Commercial journals – for profit, very expensive => limited circulation. Peer review: not always top
Example: Oecologia, Community Ecology
Small institute journals: high-quality, specialised, small circulation, infrequent publication.
Peer review: good – very good
Example: Proceedings of the Missouri Botanical Garden, Annales Musei Nationalis Hungariae
Recent trend of amalgamation - large publishing houses buy up journals and each other Free (electronic) journals –
BioMed Central: http://www.biomedcentral.com PloS (Public Library of Science): www.plosbiology.org Internet-only publishing – unofficial vs. official
Beware of the copyright problem!
Electronic publication: Electronic & print vs. electronic only – basic rules are same
– format similar – currently expensive – limited vs. free access
– in conflict with traditional publishing – the scene is quickly changing
Non-primary publications:
many types: reviews, reports, conference proceedings, comments, etc.
failing some of the primary publication criteria not useless!
Some major types of non-primary publications:
A.) Conference proceedings
Very common, ad hoc. Not primary because published in small no. of copies => Limited and erratic circulation. Variable scientific level.
B) Review journals/publications
Only publish reviews of already published primary information. Very useful and popular publications.
Annual Reviews, - Published by Annual Reviews, Inc. – California (USA)-based, non-profit company - yearly
Trends in…, - Elsevier, Netherlands - monthly
Critical Reviews…,- Informa (CRC Press, Taylor & Francis, etc.) – bimonthly Current Opinion in…- Elsevier, NL – bimonthly
C) Abstracting forums & services C1. “Abstracts” journals:
publish abstracts, slower (but cheaper) than CC, more extensive and detailed.
Biological Abstracts Zoological Records
“Cambridge” Abstracts: of Ecology, Behaviour, etc.,
CABI Abstracts – strong in applied fields (Entomology, Weed Science, Animal Science), very wide coverage
C2. Current Contents, Science Citation Index & co.
Originally: Inst Scientific Information (ISI), Philadelphia, USA.
Weekly journal, published (photographed) content pages only, Very quick (6 wk vs. 1.5 y)
Covers a limited range of journals (aims for most important ones); geographically wide coverage
Sections (Life Sciences, Agricultural & Environment, Social Sciences, etc.), Paper vs.
electronic vs. Internet versions (Web of Science)
Electronic versions: bibliographic data+ abstract+ author address + links to full text Web of Knowledge database: http://apps.isiknowledge.com
Scientometrics
The basis of scientometrics – citations
References, reference practice – what to cite and why?
Citation system: logic & abuse Conventions:
Where to look? data universe - ISI journals only, When does a citation count? - 2 y after publication, Which citations count? - only the ones in ISI journals.
Citation distribution unevenness: the Matthew Principle
The Science Citation Index (SCI) (part of Web of Knowledge) development, scientometrics, use in research
Citation indices, impact factor, immediacy index, citation half-life Journal Citation Reports (JCR)
Yearly lists of journals ranked by Impact Factor, discipline, no. of citations, Examples:
How to calculate the Impact Factor?
Moving from assessing publications to assessing individuals or groups:
How to calculate the Hirsch-index?
“Publish or Perish” software: www.publishorperish.org Use of PoP to analyse journals, scientific output, etc.
2. HOW TO WRITE SCIENTIFIC PAPERS: BEFORE YOU BEGIN Basic decision:
WHAT do you want to write? short paper, article, review, book chapter, thesis?
FOR WHOM? Readership: specialist/generalist, in-country, world-wide?
How to decide where to send a MS for publication?
Why is this important in the age of extensive literature databases?
Wrong choice results:
a) - delay - sent back as 'not suitable for our journal'
b) - unfair review - reviewers not familiar with your area & reject MS because they do not
understand it
c) - publication sinks without effect - researchers do not read the journal Consult before choosing:
- colleagues
- Web of Knowledge/ SCI / Current Contents/ PoP & Google Scholar - journal mastheads - for stated purpose
- instructions to authors on scope details
- recent issues (for actual preference, etc.) – go to journal homepage For evaluation of a given journal, check/consider:
- publication schedule - actual publication dates
- acceptance dates – handling time, printing time - publication standard/quality, general appearance - prestige factor – whom do you want to impress - circulation factor
- frequency factor
- cost /page charge, no. of free reprints
Write to editor for guidance? – not recommended Internet homepages of journals – all contain:
- editorial board members’ list
- information on purpose, instructions, addresses
- content pages (always) + abstracts (nearly always) + free access to selected (frequently)/all papers (occasionally)
- instructions to authors - correspondence addresses
- can be downloaded and printed free Examples of publishers' websites:
Blackwell Science (now Wiley Interscience): http://eu.wiley.com/WileyCDA/Section/id- 351067.html
Springer, Germany:
http://www.springerlink.com/home/main.mpx
(>1800 journals, inc. Oecologia, Behavioural Ecology & Sociobiology, Marine Ecology, etc.)
Cambridge University Press: http://journals.cambridge.org Elsevier: http://www.sciencedirect.com/
U.S.A. Entomological Society: http://www.entsoc.org/pubs/index.html/
Eur. J.Entomology: http://www.entu.cas.cz/eje/
Ecological Society of America:
http://www.esajournals.org/esaonline/?request=index-html
(Ecology, Ecological Monographs, Ecological Applications, Frontiers in Ecology&Environment)
American Naturalist: http://www.journals.uchicago.edu/AN/toc/
Ecology and Society – Ecol. Soc. Amer.-run “Web only” journal http://www.ecologyandsociety.org
3 THE STRUCTURE OF A PRIMARY SCIENTIFIC ARTICLE Parts of a manuscript of an article:
Title
Authors Addresses
Corresponding address:
Short title/ running title
---often title page Abstract/summary
Keywords
================ main body of MS starts Introduction
Material & methods Results
Discussion
=============== main body of MS ends: IMRaD Acknowledgements
References/literature cited
Tables – one/page! – complete with heading Figure legends
Figures one/page!
Appendices
Interlude: grammar & style style: clarity, clarity, clarity
reader does not read - s/he interprets. Any sentence can be interpreted in 10 diff. ways by 10 diff. readers
Grammar:
published results - present tense
your results - simple past tense
4. How to compose - THE TITLE
Important because read by largest no. of readers
“Things should be made as simple as necessary but not more so” (Einstein) - be precise, simple, short.
Good and bad titles: examples:
No series titles:
Incorrect: Studies on Encarsia formosa XXVII. The interaction between host feeding and oviposition
Correct: The interaction between host feeding and oviposition in Encarsia formosa No hanging titles:
Incorrect: Beyond Size: Matrix Projection Models for Populations Where Size Is an Incomplete Descriptor
Correct: Matrix Projection Models for Populations Where Size Is an Incomplete Descriptor No 'fun & jokes' titles - ref. to pop culture, sayings, etc.: advertising effects:
Putting a Cart before the Search: Successful Habitat Prediction for a Rare Forest Herb No questions in titles –
usually not good – readers want to know answers, not ability to ask questions
Community Impacts of a Tussock Sedge: Is Ecosystem Engineering Important in Benign Habitats?
Statements – occasionally OK:
Steroid Hormone Levels Are Related to Choice of Colony Size in Cliff Swallows Formulating a title:
sketchy title - draft title - final title
Short title/ running title - give it if required better your own than invented by others
5. The delicate art of deciding about AUTHORSHIP
A vital matter - vanity, perceptions about contribution, co-operation Trend towards increasing author no.s
Authorship on papers: contribution, prestige, pressure, flattery The importance of author sequence & how to decide
The Sheffield author scoring method Authors’ rights & responsibilities
Co-author? – universal responsibility for ALL content Read and approve ALL versions of a MS
New trend: each author’s contribution is detailed (in Acknowledgements) The corresponding author’s roles:
– co-ordinator of the writing process
– co-ordinator of the publication/review process – gatekeeper between team and outside world
6. How to write - ADDRESSES
address where work was done – to give credit
current address – where author can be found at time of publication
correspondence address – to find author – should be complete postal address e-mail address – increasingly common as means of contact
Example:
Zoltán Elek1,2*, Gábor L. Lövei1, and Márton Bátki3
1 Department of Agroecology, Aarhus University, Flakkebjerg Research Centre, DK-4200 Slagelse, Denmark; 2Animal Ecology Research Group, Hungarian Natural History Museum, Ludovika tér 2., H-1083 Budapest, Hungary, 3Department of Ecology, Eötvös Loránd
University, Pázmány P. Ave. 1/C., H-1117 Budapest, Hungary
BOX. The co-authorship scoring system used by the plant ecology group at the University of Sheffield, U.K.
1. Intellectual input (planning/designing/interpreting)
no contribution 0
one detailed discussion 5
several detailed discussions 10 correspondence or longer meetings 15
substantial 20
closest possible involvement 25
2. Practical input: data capture (setting-up, recording, observing/ abstracting)
none 0
small 5
moderate indirect 10
moderate, direct 15
major indirect 20
major direct 25
3. Practical input after data capture: data processing/ organising - but not interpreting see 1.
no 0
minor or brief assistance 5
substantial or prolonged 10
4. Specialist input from related fields
none 0
brief or routine advice 5
specially tailored assistance 10 whole basis of approach (but advice only 15
5. Literary input (contribution to first complete draft of Ms)
none 0
edited others' material 5
contributed small sections 10
contributed moderate sections 15
contributed majority 20
contributed virtually all 25
Summary. all participants are scored. Authorship condition: 25 points. Rank – by points.
If below 25 points, author carries it forward to next paper.
7. How to write - THE ABSTRACT?
Part read most
Part read first - important for editor/reviewer judgement!
(good abstract = ?good paper BUT bad abstract = bad paper) Reproduced in itself => self-explanatory
Can decide about conference acceptance/funds Always limited no. of words (200-500)
Word limit important BUT ≠ to use up the limit If can use 100 words, don't use 200.
List-type vs. informative
Structured – sometimes with headings or numbered statement Mini-review of the paper
- question/problem - P
- method used M
- brief/main results R - main conclusions C NO: - fillers
- suspense
- description what was done & no results
- abbreviations
- references (except in rare cases, give brief but full data in Abst) - reference to figures, tables
- information that is not in the text (!)
- 'consequences discussed' - everyone can guess!
WHEN to write: at the very end!
Write in past tense - your own results
Keywords:
consider carefully - they will be used by abstracting services observe where to put it.
8. How to write – THE INTRODUCTION
purpose: allow reader to understand and evaluate your results. New information only understandable if linked to known information
To introduce the problem if reader not interested in question, will s/he want to know the answer?
The problem:
Why is it important?
- state the problem, and how it emerged (in science; this is not your personal history) NOT 'as I was walking through the flooded spring meadow...'
What is known about it?
give context, review the literature - but only literature specific to the question
=> cite literature sparingly and functionally.
weave your theme into the “universal tapestry”.
"Funnel" structure: start with general, end with specific:
E.g. – global change as a phenomenon – urbanisation as an element in global change - impact on biodiveristy of urbanisation – study of invertebrate biodiversity – beetles as indicators of general biodiversity
What did you study and what did you find?
Explain the choice of methods Summarize results
NOT a detective story: "we want to know from the beginning that the butler did it"
Last par: summarise main reaults and conclusions!
Style & detail:
Consider audience as it determines detail needed,
terms to be used, terms to be explained, things to describe
Consider: what specific details are needed in a paper on Pyrenean plants, published in an Iberian journal, a global botanical journal, or a general, international ecology journal?
Beware of jargon & misunderstandings:
“NIH is an equal opportunity employer, M & F”. – US job advertisement What is M&F?
(muscular & fit? hermaphroditic? musical & flatulent? mature & in his fifties?) Tense: mostly present tense - published literature, existing knowledge.
Your own results: simple past tense WHEN to write?
While investigation in progress.
- Material, reagents, etc. in hand, collaborators available.
- Might lead the study to new lines.
- Might make you aware of a missed angle, method, etc.
9. How to write - MATERIALS AND METHODS
Section content: study site, study organism, material, methods, evaluation Aim:
- to enable readers to repeat your work for verification;
- enable the reader to judge the adequacy of method (and results reliable) ONE criterion - sufficient detail to be given
Cornerstone of scientific method: regularities found - repeatable Consider carefully your readership.
what do they know about your setting, organisms, methods, etc. - give detail accordingly Peer review: methods closely scrutinised. If reviewer in doubt that experiments repeatable, will be rejected no matter how wonderful the findings!
Study site:
consider readership, give details accordingly (geography, use of co-ordinates, maps).
Information on habitat, sampling site (not the lab) Study organism:
Name, species, strain, etc.
consider background information on life history consider tabulation for many strains, etc.
Materials
give exact names (chemicals), generic not trade names.
Give source (with location) if necessary
[current practice: manufacturer name, location given]
Sampling methods and measurements,
procedures: how? how much?
new method: all details – so that it is repeatable
if published method reference only, minimum description if method published, consider where was it published?
Units of measurement: only SI units: weight – mass
How did you deal with errors, missing data, missing traps, etc.?
Evaluation methods / Statistics:
reference sufficient; give detail only if new method.
Avoid neophyte description: what’s new for you, may not be new for readers give reason for choice of method if not standard
Be careful with details -- your reputation is on the line!
instructions to authors - often good, always check!
Watch for numbers, spelling, punctuation – many "strange" names occur
Meticulousness: if you cannot be trusted in doing simple things, can you expect trust in significant and complicated ones?
What is science? Grand ideas or precise work?
Order: chronological;
clustered Tense: past
Syntax carefully! “After standing in hot water for an hour, the flasks were examined”
style: one rule: give sufficient detail that experiment is repeatable
good check: can a colleague repeat the experiment based on the methods description given?
writer often too close to method, omits glaringly obvious detail Do NOT mix in results!
WHEN to write?
Start writing: first! while working - many details will be otherwise lost.
collaborators present
easy to complete while doing the work (familarity)
10. How to write the RESULTS
Key part of article, everything hinges on results Present:
a) the big picture, an overall description of the experiments (i.e. what did you manage to prove?)
b) your results (supporting the claim you make)
Detail significant data, not insignificant ones (if a variable ineffective, mention but no details)
Not all data need a table
‘absence of evidence is not evidence of absence’ - what did you NOT find?
DO NOT:
- start with a forgotten method
- give material (how many birds you examined) - present all your data
- repeat data in text and table/figure
- leave the reader to find the meaning and analyse on her own
‘the compulsion … not to leave anything out does not prove unlimited information; it proves lack of discrimination’ (Day, 1998)
DO:
point to significant trends & facts among the numbers direct reader’s attention
Write meaningful statistics:
“in 33.3% of mice, the treatment was effective; no change was observed in the condition of the other 33.3%; the third mouse escaped”
Presenting statistics:
Name test, give test statistic value, degrees of freedom, level of significance:
Student’s t-test, t = 5.43, d.f.= 114, p= 0.00014
Presenting numbers: beware of false exactness! 1 ≠ 1.0 ≠ 1.00 If measurement exactness = 0.1, do not give means as 0.13333 Style:
“When presenting facts, leave elegance to the tailor” (Einstein –cit.Day 1998) - No references (your own, new work)
- Simple past tense (your own results, first presented here) - Crystal clarity & simplicity
WHEN to write?
After material & methods, introduction, before discussion Work in parallel on figures & tables
11. How to write - THE DISCUSSION
Hard to define, hard to write => most verbose & pull down paper most rejections due to faulty discussion
Common fault: “squid technique”: author unsure what her data mean & hides in a protective cloud
Purpose: explain what do the data mean?
DO NOT
- repeat results
- introduce new results
- pretend to have solved everything - finish with throwaway sentences
- try to walk around every possibility, esp. if speculative (keep proportion between results & discussion)
DO:
- present principles, relationships, generalisations - discuss, not repeat results
- refer back to problem
- say what was NOT found, corroborated, etc. point out gaps, inconsistencies - show how your results agree & differ with previous work?
- explain the significance of your results (avoid the “so what?”) - discuss the theoretical and practical implications
- present what is the new picture
- summarize evidence for each conclusion
(“never assume anything except a 4% mortgage” – Day 1998)
"a clear stream of discussion ends in a swampy delta" - end with a clear statement ( NOT 'more studies are needed’)
Style:
- Tense: switching between present (publ.d knowledge) & past (your results)
- No need for cosmic conclusions; you will be able to illuminate but one area. - Your conclusions can be buttressed by your facts in that one area - but if you extrapolate to a bigger area than your data allow, you may appear foolish to the degree that even your data will be doubted.
The simplest statements evoke the most wisdom.
Fancy language and abundant technical terms => to disguise shallow thinking.
“Display your small piece of truth - leave the whole truth to ingoramuses, who proclaim its discovery every day.” (Day 1998)
WHEN to write?
Towards the end, after results
Do not combine results & discussion – make you new contribution to stand out and separate from interpretation
12. OTHER PARTS: acknowledgements, & appendices, etc.
Acknowledgements
“Life is not so short but that there is always time enough for courtesy” - Ralph Waldo Emerson
Acknowledge - grants received
- any significant help with methods, work, reagents, methods, etc.
- permissions, approvals (ethical committee, access to area, etc.) - reviewers’ help, editorial help (?)
- Can write: paper series no. XXX
- new trend: give details of individual authors’ contribution (XX, ZZ designed the expeirment, FF, ZZ performed field work, etc.)
Basic rule: this is courtesy; not a surprise present - show wording to person Why?
- might think it too little / too effusive
- be specific - too general => responsible for paper?
- if not co-author, should not make the impression that s/he shares responsibility;
- often does not agree with your conclusion!
Style:
simple, precise
do not 'wish to thank' - simply 'thank' give reason why the name included?
Appendices & extra detail
- complicated procedures, programs, models - large bodies of data
data archive – computer-based (e.g. Ecology) Be prepared to have to defend inclusion!
13. How to cite & compile - REFERENCES - cite only significant, published references
"a MS containing innumerable references is a mark of uncertainty rather than a mark of scholarship" (Day 1998)
- when citing, use the most credible references:
Peer-reviewed paper > weakly-peer-reviewed (Thesis, conference proceedings paper) >
ephemeral, non-peer-reviwed (Internet site, popular article, opinion piece) Do NOT cite:
- reference not seen (if unavoidable, XYZ 1874, cit. BB 1999 – give bibliographic details of BB 1999)
- unpublished data - unpublished MS
- abstracts (conference or any other) Try to avoid citing:
- theses (except your own) – not readily available to readers - government reports – limited circulation, difficult to obtain - Internet sources - unreliable quality, ephemeral
- personal communication – usually considered low-quality information - if unavoidable: give full name, affiliation; have a written version of the
communication for archival purpose 'in press' ≠ 'submitted' or 'in preparation’
“in press” – citation allowed but have to document that paper is accepted Citation conventions
In text:
- name (year) or fact (name, year) -
One or 2 authors: Always write out: Smith (1980), Smith & Jones (1981), 3 authors: Smith, Jones & Little (1982) vs. Smith et al. (1982)
Multiple (3+) authors: Smith et al.
Sequence:
Chronological (Kis 1981, Abe 1998) vs. - alphabetical (Abe 1998, Kis 1981) – check journal for required format
Style when citing in text:
Avoid judgements:
“Jones' very elegant paper (1998)” - if cite, do not judge, but give reason WHY do you cite it?
References at the end of sentences - wrong!
On reference list:
Principle: give all bibliographic details to enable finding the reference Competing systems:
alphabetical - Chicago Manual of Style –– seems most general alphanumerical - Council of Biology Editors Manual -
citation order – “Vancouver system “ - 'uniform requirements for biomedical journals' Ref. list format:
Very different by journals: with/without title, first & last page, initials position, etc.
- smart: write ref. in full: all authors, full title, inclusive pages – for your database/ catalogue - easy to edit out, difficult to find again
- will probably use same ref. again in another paper Abbreviations – disappearing. Abbrev. rules – too few
one-word journal name never abbreviated (Ecology vs. J. Ecol.) J. = journal
-ology = ol. (Bacteriol., Ornithol., Physiol.) in doubt? - write it in full
Citation examples:
Paper:
Eernise DJ, Kluge AG. (1993) Taxonomic congruence versus total evidence, and amniote phylogeny inferred from fossils, molecules, and morphology. Molecular Biology and Evolution 10: 1170–1195.
J. S. Carr, A. T. Tokunaga, J. Najita, Astrophys. J. 603, 213 (2004)
Book:
Dressler RL. 1981. The orchids: natural history and classification. Cambridge, MA: Harvard University Press.
Book chapter:
Danchin, E. (2001) Public information and breeding habitat selection. Dispersal (eds J.
Clobert & J.D. Nichols), pp. 243–258. Oxford University Press, Oxford.
Website:
van Frankenhuyzen, K. and C. Nystrom 2002. The Bacillus thuringiensis toxin
specificity database. http://www.glfc.cfs.nrcan.gc.ca/bacillus (accessed 19 March 2008).
- check every part of every reference against the original.
refs. is section containing the most errors
check that all references on list are in text & vice versa!!
Very different format of citations/references? => reject MS; also: indicates carelessness
14. Constructing FIGURES: a tricky art?
"Clear graphics aid, and show, clear thinking about what data mean"
(Valiela 2001) NOTE: numbers in this section refer to the figures to be projected during the course. They
are available in the pdf files accompanying these notes.
The power of figures – examples
Example 1 - Figures can make a point quickly and forcefully.
Rubbish in space: text vs. figures
…some 7,000 pieces of space debris – operating and dead satellites, explosion fragments from rocket engines, garbage bags and frozen sewage dumped by astronauts, shrapnel from antisatellite weapons tests, 34 nuclear reactors and their fuel cores, an escaped wrench and a toothbrush – now orbit our world. Only about 5 percent are working satellites. By means of extraordinary data recording and analysis, military computers identify and then track each of these 7,000 objects (>10 cm in diameter), in order to differentiate the debris from a missile attack, for which we may be thankful. Space is not totally self-cleaning; some of the stuff will be up there for centuries, endangering people and satellites working in space as well as inducing spurious astronomical observations. The risk of a damaging collision is perhaps 1 in 500 during several years in orbit. The volume of debris has doubled about every 5 years;
future testing of space weapons will accelerate the trashing of space.
Example 2 - Napoleon's war in Russia – complex story can be told
Example 3 - Barley data analysis, Minnesota, U.S.A. - Graphs can unearth aspects of data that otherwise remain hidden
See figs. 6.20, 1.1. & 6.21 for the different versions that indicate the anomaly in the dataset.
Example 4 - The Challenger disaster - Bad figures can kill
See the file, pages 6 & 7. The first contains the figure version used by the engineers to test the relationship between ground temperature at the time of space shuttle launch and O ring damage recorded on the booster rocket segments. The second has ALL the data on O-rings, irrespective of the amount of damage. The conclusion is clear: there has been no launch under 65o F when O rings did nto suffere damage. Plus the expected temprerature is much colder than at any previous launch.
Example 5 (pages 8 & 9)– The Anscombe quartet - Graphical presentation of data reveals aspects that statistics hide
The table (page 8) shows the x and y values of the four datasets. All descriptive statistics are
identical. The graph (page 9) indicates the their distribution is strikingly different. If the data are not graphed, such differnce would remain unnoticed.
Overall, statistical graphics can:
- show the data
- induce the viewer to think about the substance NOT methodology, design, or technology - avoid distorting what the data have to say
- present many numbers in small space - make large data sets coherent
- encourage the eye to compare diff. pieces of data - reveal data at several levels of detail
- serve a clear purpose: description, exploration, tabulation
- closely integrated with statistical and verbal description of a data set
Terminology
See figs. 2.1 & 2.2, depicting: data rectangle Axes & axis labels (in Us English “scales”) ticks & tick labels
key & data label legend / caption
Principles of designing graphs: economy, clarity, integrity Designed to present the data, in clear, uncluttered and honest way.
Principle. a figure should be understandable without reference to the text.
Double presentation - not allowed: either text, or figure, or table.
no double-coding (symbol + line) All axes should have a label:
what is displayed?
what are the measurement units?
Economy
Data rectangle should fill the scale-line rectangle 2.49 vs. 2.50 Do not insist to include zero – 2.59
Maximum no. of data, min. ink – improve the data/ink ratio (examples with bad data-ink ratio:
Unnecessary decorative elements (page 5) – do not use them Bad practice (chartjunk): pages 8 & 9
Tukey box plot – vs. Tufte plot (page 8)
Examples of 'more with less' (earasing ink & increase information):
- conventional axes vs. range-frame (page 9)
- indicating mean (or median), quartiles along axes(page 10) - ticks corresponding to data (page 11)
Clarity
allow for reduction in reproduction – the fig. on 2.30 did not no scale braeaks 2.71, 2.72
tick marks outward – they can inteerfere with data: bad 2.11, 2.12 & good 2.13 when data sit on axis, move away axis – 2.9 vs. 2.10
use visually prominent sumbols to show data - fig.2.5 (bad) & 2.6 (better) do not allow data labels clutter the graph 1.6 vs. 1.7
do not clutter the interior of data rectangle: 2.3 (bad) vs. 2.4 (good) , 2.14 (bad) vs. 2.15 (good), 2.16 (bad) vs. 2.17 (good)
tick marks & data labels should not dominate 2.19, 2.22 provide sufficient explanation: 2.34
Visual clarity:
avoid overlapping symbols. How?
a) use logarithms 3.27 vs. 3.28
b) moving 3.29 – only works if not too many overlapping points:
c) jittering 3.31 vs. 3.32
d) symbol use – empty circules are best – see 3.33 superimposition - symbol use 3.34, 3.35 3.36, 3.38
the role of reference grid 4.8, 3.41
banking to 45o – useful for trend assessment 1.1., 2.42,
Integrity
Figures are always selective presentation of data – certain aspects remain underemphasised or hidden => careful assessment of purpose needed:
Example: time series presentation methods
symbol plot 3.53 - good for time series for long-term trend connected plot 3.54
vertical line plot 3.55
=> Graph should be truthful to data
No pseudo-dimensions – data dimensions should match data dimensions (if possible) .- page 2 (bad example)
Comparison between panels: uniform or comparable scale 2.55 Provide context – pages 4-6
Do not use graphical elements to create misleading impression Page 7, fig. 9.26
Do not exaggerate (the “lie factor”: discrepancy between data difference and representation size difference) pages 8-14
Graphs to not have to be “alive” and “decorative” – page 15
Common problems with & misconceptions about graphs graphs have to be 'alive', 'communicatively dynamic' =>
overdecorated (chartjunk – word coined by Cleveland) exaggerated design, disguising shallow thinking disregarding the truth about data
arrogant Chartjunk:
- unintentional “optical art” (Moire vibration)
- the dreaded grid – when it is too strong and interferes with data - unnecessary decoration (e.g. p.14)
Graphical methods - Old designs to discard Area charts
Ease and precision of estimation: differences in line length >>> differences in area >>
differences in volume
Area charts violate the data dimensionality principle: a single measured value is represnted by a two-dimensional object (circle) – use dot plots instead (4.23 – bad vs. 4.24 –
recommended) Pie chart
Circles, divided into "slices". (4.19)
bad design overall - area occupied should be assessed only the largest differences could be identified.
figure useless – often numbers besides (unacceptable, double presentation of data)
Use dot plot instead (4.20) Bar chart
Oldest graph type –
measurement value = height of a column.
Often composite – several columns attached to each other, data "solidity": heavy shading, complicated markings
classifies horizontal axis as categorical variable – check if this assumption is correct (sometimes it is not, see 2.38)
point at the appropriate height gives the same information
Stacked bar chart (vertical or horizontal) Columns divided into different segments
Individual measurements very difficult to perceive - base & top both variable => proper perception impossible. (2.38)
IF horizontal axis is a proper variable (data are two-dimensional) – use a scatterplot, line plot (2.39), or similar (see options e.g. 3.53 -3.55 under integrity)
IF data are one-dimensional (4.21), use a multiple dot plot (4.22)
New methods of data presentation Dot plot & multiway dot plot for one-dimensional data
dot plot for labelled data, to replace: pie charts, bar charts
order on dot plot – according to value of measured variable, largest on top smallest on bottom – 4.10 vs. 4.9
Multiway dot plot – common horizontal axis (4.11) & optimisation of vertical order on panels: has to be uniform, AND approximate top-to-bottom order
Think about the order of categoricla variables on multiple dot plots: 4.11 vs. 4.18 superimposition possible on dot plots 1.1.
For two-dimensional data:
Loess (lowess): locally weighted regression
Example: hibernating hamsters & life span – 3.42 – 3.44 How loess wroks – 3.49
Testing the effect of window width – compare 3.44 and 3.45 Testing with loess of residuals – see 3.47 & 3.48
Multi-dimensional data Scatterplot matrix:
for data with > 3 variables, but relationships are always between two variables
picture every two variables against each other with shared scales 3.64 - redundant (every pairing is twice, changing the horizontal – vertical positions) but otherwise synthetic
comparison not possible
Conditional plot / coplot
To picture relationship of two variables under selected interval of a third variable – wear of car tyres example 3.66:
Colour
used to be rare in journals – expensive (USD1000+)
Cheap in Internet-based journals – consider carefully; sometimes b&W in print, Colour on Net – be careful, not always interchangeable
Use colour to help understanding, not for decoration Modest use of colour is very helpful
Try to use harmonic combinations
Consider colour-blindness (some combinations are indistinguishable)
Legend (caption)
An important part of the figure - should give information to help understand the figure Legend is printed underneath the figure – but
NOT in the manuscript – in MS legends are at the end of the text, grouped together.
Common error: not enough detail to understand the figure
Numbering – in the sequence of mentioning in the text, independently of tables
Proportion, scale and appearance:
graphs should tend towards horizontal: length > height
- eye is naturally practised in detecting deviations from horizon - ease of labelling
causal influence: mostly cause (independent variable) – effect (dependent variable) =>
horizontal depth – space to elaborate
ratio: golden section – a/b = b/ (a+b) – ratio 1:1.618
‘smoothly-changing curves can be taller than wide, wiggly curve needs to be wider than tall lettering: type & size - serif fonts preferred - more readable
Integrating figures & text
To have clear understanding, in the text:
- describe everything that is graphed
- draw attention to the important features of the data
- describe the conclusions drawn from the data on the graph
- interplay between graph, caption and text is delicate - no iron rules but hard thinking. self-contained figures necessary.
- error bars should be clearly explained : s.d., s.e., confidence interval?
Revising your graph Check the following:
- no pseudo-dimensions - maximise data-ink ratio
- erase non-data ink & redundant data ink, within reason
- is the legend appropriate?
Scientific illustration software – many types available.
Examples. Statistica, Axum, Origin, SAS (not user-friendly), S-Plus, R, SPSS, SigmaPlot Summary
A good graph:
- is a well-designed presentation of interesting data
-complex ideas communicated with clarity, precision, and efficiency
- gives the viewer the greatest no. of ideas in the shortest time with the least ink in the smallest space
- nearly always multivariate
- requires telling the truth ! about the data
Features of
friendly graph unfriendly graph
words spelled out, no mysterious coding Abbreviations abound, requiring ref. to text words run left to right words run vertically and/or several diff.
directions
messages help explain data graphic is cryptic, requires ref. to text elaborate shadings etc. avoided, labels on
graphic itself
obscure coding, frequent ref to legend needed graphic attracts viewer, raises curiosity chartjunk-filled
colour used with colour-blind in mind design insensitive to colour-blind (10% of popul.)
type clear, precise, modest type clotted, overbearing Type upper-lower case, with serifs all capitals, sans serif
Reviewing/evaluating figures (Exercise)
1. Is the figure necessary? Do the data justify a figure? Table? Can be written in the text?
2. Is the type of figure acceptable? Is a better type of figure necessary? (dot plot, multiple dot plots, co-plot, scatterplot vs. histogram or pie chart)
3. Data/ink ratio? Can this be improved? - can ink be eliminated and information retained?
4. Appearance: axis scale, labels (clear, not too many?), symbols (contrast, recognition). Do data fill the data rectangle?
5. Format: size, font type, ratio (vertical:horizontal, banked to 45 degree?) of figure.
Is size appropriate? Do data points stand out? Does it withstand reduction?
6. Is the legend appropriate?
Useful resources:
Tufte, Edward. R. 2003. The visual display of quantitative information. 2nd ed. Graphics Press, Cheshire, Connecticut, U.S.A.
Tufte, Edward. R. 1990. Envisioning information. Graphics Press.
Tufte, Edward. R. 1997. Visual explanations. Graphics Press.
Tufte, Edward R. 2006. Beautiful evidence. Graphics Press.
Cleveland, William S. 1993. Visualizing data. Hobart Press, U.S.A.
Cleveland, William S. 1994. The elements of graphing data. Hobart Press, U.S.A.
Edward Tufte’s website: www.edwardtufte.com Bill Cleveland’s website:
http://cm.bell-labs.com/cm/ms/departments/sia/wsc/
Photographs & drawings
Is it important? (editor will always ask)
Yes? – check journal reproduction standard – only good final quality convincing
colour – at your expense! (US$1000 & up) Colour possible? Provide slides (not prints)
Black& white photos: Supply B&W prints – colour photo reproduced in B&W – no good result (grays and fading shades result)
How to control photo quality?
best quality: no reduction/enlargement - consider journal dimensions
- reduction decreases quality – crop/frame the important part How? Experiment with cropping possibilities:
meaningful instructions – editor/copy editor happy to oblige
In-photo information:
letters or arrows superimposed if needed scale directly on photo (reduction!) mark “top” on back, in soft pencil
author, fig. no. – in pencil (photos separated form MS in production)
mark position in text – someone will have to decide where to insert – why not you?
Digital photo/illustrations:
check acceptable or preferred file format – can contact technical editor for clarification.
Will be seen as co-operation, not obstacle
.TIFF, .JPEG format better than EPS, etc. (but ask editor!)
Pen & ink illustrations: could be very useful, but only in good quality – by professional artist
15. TABLES
First question: Do you need a table?
- only if repetitive data must be presented
- not good science to publish data just because you measured them - printing a table is costly
- examples of bad (unnecessary) tables
lots of standard conditions – not variables lots of 0s, 100% or +/- s
word list table
Tables should be self-explanatory (as figures) Title: economic use of words
use footnotes (sparingly)
avoid exponents (prone to printing problems)
give details but not excessively (mention method but not recipe)
Format:
No vertical lines
Horizontal lines: column heading top (under table title),
column heading bottom
below table
Partial horizontal – sub-grouping column headings
data in either text, OR figures OR table – never repeat but:
Selected data can be singled out for discussion
significant figures and “virtual exactness”: 1 vs. 1.00 vs. 1.0000
Organisation: elements/comparisons read down, not across
Marginal indicator in Ms text (pencil) – helps to see if you mentioned all tables and if in sequence.
Think hard about the vertical sequence of rows and general arrangement of tables – often neglected.
Tip: read instructions before final formatting! – requirements often specific and non- intuitive
Tabulation of data – why do we put independent variable to the left?
Table 1, version 1: The effect of heating on water temperature.
t (time)= 0', 3', 6', 9', 12', 15’, T (temperature)= 25, 27, 29, 31, 32, 32 oC;
Table 1, version 2: The effect of heating on water temperature.
Temperature (oC) Time (min)
25 0
27 3
29 6
31 9
32 12
32 15
Table 1, version 3. The effect of heating on water temperature.
Time (min) Temperature (oC)
0 25
3 27
6 29
9 31
12 32
15 32
individuals of Carabus nemoralis, C. hortensis, and C. coriaceus caught in 2004 and 2005, in Sorø West Zealand, Denmark.
Activity periods Year,
habitat
Early Main Late
Activity peak
No.
individuals/ye ar Carabus nemoralis
2005
Forest 02 May-17 May 17 May-24 Jun 24 Jun-03 Oct 27 May 46 Suburban 02 May-28 May 28 May-08 Sept 08 Sept-03 Oct 13 Aug 170
Urban 02 -15 May 15 May-17 Aug 17 Aug-03 Oct 23 Jun 85
Carabus hortensis 2004
Forest 06 May-03 Aug 03 Aug-12 Sept 12 Sept-11 Oct 16 Aug 328 Suburban 06 May-07 Aug 07 Aug-17 Sept 17 Sept-11 Oct 20 Aug 19 2005
Forest 02 May-16 Jul 16 Jul-14 Aug 14 Aug- 03 Oct 07 Aug 237 Suburban 02 May-10 Aug 10-Aug-4 Sept 04 Sept-03 Oct 29 Aug 89
Carabus coriaceus 2004
Forest 06 May-22 Aug 22 Aug-18 Sept 18 Sept-11 Oct 06 Sept 376 Suburban 06 May-23 Aug 23 Aug-15 Sept 15 Sept-11 Oct 3 Sept 444
2005
Forest 02 May-09 Aug 09 Aug-07 Sept 07 Sept-03 Oct 17 Aug 121 Suburban 02 May-07 Aug 07 Aug-03 Sept 03 Sept-03 Oct 14 Aug 86
16. THE WRITING PROCESS: how to write the first version?
What language to write in? English! Do not translate.
Start with: material & methods Finish with: title & abstract
Work in parallel on: results & figures-tables Introduction before discussion
Reference list: gradually – do NOT leave until the end!
“Loose-leaf” technique
Spend time on figures – before or parallel with results Tricks:
- start as soon as practicable
- sketchy title – draft title – final title
- can start with insignificant details (acknowledgements, key words) - if you cannot make progress, leave it, put it aside/ start somewhere else
Completed? Not finished! - the pre-submission maturation period First: read it yourself!
Pre-submission peer review: 1 friend, 1 colleague, 1 other professional - show it to as may people as you want
- send to foreign colleagues (ask first) - revise
- put it aside to mature - DO NOT RUSH
17. PREPARING THE FINAL VERSION & SUBMITTING
When you have finished the experiment and written the paper, the final typing is not important, because if your work is good, solid science, it will be accepted for publication. – WRONG!
Why? – first check is on format;
if format not as required, MS sent back without evaluation
- double spacing - wide margins - no right justification
- paginate MS with author name at right top (identification of lose pages) - observe heading structure & format – primary etc.
- tables/figures at end, not in between text - no mimicking of final format needed
- reference style - most errors here, use reference managing software - start new sections on new page - convenient
- spelling (British vs. US)
– use numbered lines in MS – easy to follow comments & revisions for editor, reviewer
& author
Before submission:
- final-final format check - use check sheet:
all parts there? word limits observed? all references checked? all ref.s mentioned?
position of tables & figures marked? format of ref.s correct?
Submission:
By corresponding author
Carefully & meticulously: speeds evaluation/publication Mostly electronic, postal submisison disappearing
Submitting author plays secretary (typing necessary info into the database) Immediate feedback & reference number
CAN contact editor if good reason exists
better to have all in one file (option is there to submit several diff. files) naming of files – should be meaningful names (include author name) Accompanying letter - never send anything without it!
- what is in the envelope – new submission, revised, final version, etc.
- include title and authors of the document
- for what journal –offices run many journals, receive hundreds of MSs - declare if any part published and how
- identify corresponding author, with corresponding address (redundancy but OK) - indicate if corresponding address expected to change over next 6-10 months - state co-authors agreement (not always taken, although mostly)
- state novelty:
“This manuscript is not under consideration elsewhere, and contains new, unpublished results” (legal reason)
- state no conflict of interest /declare interest
- give suggested reviewers (more than required and only if expressedly asked) - indicate non-desired reviewers
- have a list of enclosures at end
- Important: argue the merits of the paper Keep a copy for yourself – proof of existence
Once completed, circulate MS to author team (preferably as a pdf)
18. The manuscript handling process in the manuscript stage - SCIENTIFIC EDITING PROCESS
1. Ms submitted/arrives to office:
book-keeping: arrival date, author, corresponding address, reference number (automatically done when electronically submitted)
2. brief check: does it seem to fit the journal? – decision 1: Y/N 3. format check: does it conform? decision 2: Y/N
4. editor's reading: should I send this to reviewers? decision 3 Y/N – MS can be rejected without review (most MSs are)
5. (notify author of receipt) – unnecessary if submitted electronically 6. assign to sub-editor or find reviewers/identify reviewers
7. send Ms for review 8. receive/solicit reviews
9. evaluate reviews - decision 4: accept/reject/revise/ask for additional review?
10. draft editorial response: accept/reject/revise 11. Reject? –
ENDS HERE ====================
Revise? – Deadline given (if missed, back to start) 12. evaluate revision/s. Send out to reviewers again if necessary 13. correspond with author about further/final revision
14. receive final version, check format, disk, figures, etc.
15. send to printer
Follow-up correspondence after submission:
- acknowledgement of receipt – w/in 2-3 weeks - enquire if not rec.d after 4-5 weeks
- editorial response: within 6 weeks (only the best) – 5 months receipt letter often indicates target assessment time - enquire after 3 weeks past promised deadline
you can unearth a problem prompt editor into action - no reply for 6 weeks – call editor
- no response – withdraw manuscript On receipt of editor’s report
- Accepted? Hoorray! Celebrate.
- Revision? Sit back and think.
- Rejected? You are in ample company. Sit back and think. Look at positive aspects (reviewers’ suggestions can be worthwhile)
Be prepared to be rejected (60% of publ.d papers not in first journal) Rejection letter:
- ‘never want to see again’ – send elsewhere.
- additional experiments required, re-submit – is it worth?
- rejected on insufficient grounds? Best not to argue.
Rejection sentences/letters/ drawings
19. How to write - REVISIONS?
Is it worth revising? – not always
consider reviews – are they good & factual?
follow them if they’re good
do not make extensive re-writing – often better to send elsewhere change as little as possible (within reason)
Important: be meticulous in presenting your changes & arguments VERY detailed response to reviewers & editor’s suggestion
How to deal with the editor? How to get your paper published? Negotiating skills to ease your way to publication.
Advice 1: Remember: the peer review process is voluntary Advice 2:
Understand the editor – how does she work?
Be polite. Editor is on your side if you strive for quality and clarity.
Accept all reasonable suggestions Be factual if objecting
May hint careless reading by reviewer – NEVER editor!
Seek compromise
Be meticulous – substantiate all statements, provide all details, assist editor The editor in heaven
How to write a review of a MS?
- insist on complete copy (give complete copy)
- follow guidelines, check tick sheet
- write for both editor AND author (sometimes separately) - assess significance
- appropriateness of methods - check relevance of approach
- check numbers, calculations, consistency - figures & tables
- references
- clarity of expression - structure of paper
- language – consider expected audience (ask editor if you do not know) - give clear recommendation
- when criticising
be factual and not personal give evidence of your standpoint suggest alternative
20. What happens with the MS after acceptance? - TECHNICAL EDITING 1. Final submission:
- Copyright issues to be sorted out (usually earlier) A warning on copyright - re. web publication - be prompt (not to miss issue)
- NO changes!
- final copy of figures
- send carefully to save figure copies (hard back/ padded envelope)
- MS on floppy disk – check format, make sure it is retrievable & with software required
- do not forget accompanying letter
- option: self-typeset (e.g. Phil. Trans. Roy.Soc.) LatEX
2. MS goes to copy-editor
3. Copy editor checks spelling, punctuation, abbreviations unified, letter types added (i.e. Italics), author queries marked (for clarification)
4. Printer typesets, produces first proofs (galley proofs) 5. Proofs sent to author for proof-reading
6. Corrected proofs back to printer for corrections 7. 2nd proofs produced & checked (not by author) 8. 2nd proofs back to printer
9. Final corrections made 10. Whole issue collated 11. Issue ‘signed off’ by editor 12. Printing & binding
13. Mailing
21. PROOFREADING
perfect MS = perfect article because all is mechanical/computer driven– NO!
LAST CHANCE for quality control (not for revision!) How to do it?
not by yourself – in company – read aloud
at least twice
read through it – you are familiar with it, others are not! => mistakes occur reading misses 90% of errors but spots omissions
Special care with:
numbers, tables, and figures!
symbols, equations, unusual expressions and symbols - scientific names (keyboard operators are not scientists) -
check: table & figure placing
figure size
- can request re-placement or size change – with reason given – update if necessary/possible – details of ‘in press’ references
-
spell-checker does NOT care! =>
“Thou shalt commit adultery” –
Bible, King James' translation, England, ed. 1631.
Changes & corrections in proof:
Mark changes twice – in place & on margin use proof-reading marks - more efficient
no additions/excessive alterations (can also cost you – why?) Complains? At the proof stage
Reprint order – at proof stage – reprint production system how many to order? – price & other considerations
22. WHAT TO DO WITH A PUBLISHED PAPER?
Can send copies to:
• people/organizations who supported your research
• your institute's library/librarian
• colleagues in your department
• your superiors
• authors you cited in your paper
• other researchers or scientists who have published on the same subject or are working in that field
• junior researchers who are developing skills in the same field
• relevant special interest groups, online discussion forums, any professional bodies of which you are a member
• others who helped in the study
• use it as handout for talks, poster presentations (if it is based on the subject/project)
Reprint requests – who & why asks for reprints?
- foreign countries from small institutions
- peers
- collectors
Should YOU collect reprints? => review, etc.
What to collect?
On keeping an own literature database EndNote, Reference Manager
23. How to write a CONFERENCE PROCEEDINGS PAPER?
Real question: should you write a conference proceedings paper?
conflict: usually not a primary publication => little publication benefit - travel often on condition of presenting material
- pressure to publish in proceedings
different types of conferences – too oftan considerd as record that the conference happened; main purpose is often not to publish science, but to demonstrate to the organizers or funders, institutions that the conference was a success
contributions are generally NOT peer-reviewed or comments not very critical (not wanting to lose contributions – "the thicker the better")
often done on a shoestring – non-professional scientific and technical editing, low
printing standard
always has limits: format, page limit, no. of figures, etc.
Advice: be VERY careful & conscientious => editorial standard often low (ad hoc editor, no experience)
Do NOT publish full material there, always retain (copy)right to publish in primary publications
Can publish preliminary data, speculation, new ideas (not supported by data)
24. How to write A REVIEW ARTICLE?
DO NOT write review without pre-contact with editor Annual Reviews review commissioning system approach letter:
topic – why is it important to review now?
why you are the one to write it?
synopsis/structure - the more detailed the better Review: an evaluation of published knowledge
=> do NOT publish original results!
Not a primary publication typically long (10-50 pages)
style: general, expansive – readership wide: peers, colleagues, students (order many reprints!)
no accepted general structure
expand Introduction, delete M&M, delete Results, expand Discussion conclusions (&recommendations)
plan is important - make outline read papers, not abstracts do not cite paper not seen use citation maps
computer searches SCI search
Current Contents & literature databases do a mind map
On search words & search strategies importance of first paragraphs importance of conclusions
"state of the art" reviews – historical reviews
25. How to write a BOOK CHAPTER?
The increasing fashion of edited books – why?
- time lacking to write whole book by one person - information amount vast
- burden of writing shared
- general trend of co-authorship & teamwork - impatience & vanity
books & books - importance of publisher, editor, format, topic Review chapter; not a primary publication
Readership: even more general than for review articles – detail, context, style. Figures and illustrations are important.
Basic concepts, theories, to be explained in detail be cautious – is it worth it?
KNOW the editor, publisher, & other authors
How to write a BOOK?
DO NOT WRITE A BOOK (or not yet)
26. ORAL PRESENTATIONS 1: preparation and planning
differences in relation to other forms of scientific communication: talk is ephemeral, no permanent record
WHEN to give a talk? – when you have something to say No recirculation – possible exceptions exist
published material – consider carefully
General conference talk: 10 min + 5 min discussion not frequent: 10 times/lifetime!
at stake: years of research
time for talk = 1/time for preparation
Clues for clarity – from magicians’ practice (Tufte, E.R. 1997. Visual explanations, pp.
64 – 71)
Magician creates illusion – uses DISINFORMATION design:
- concealing important facts - obscuring issues
- never telling the audience in advance what are they going to do - never performing the same trick twice in one evening
