Data commentary
Why do data commentary?
− Highlight the results.
− Assess standard theory, common beliefs, or general practice in the light of
the given data.
− Compare and evaluate different data sets.
− Assess the reliability of the data in terms of the methodology that produced
it.
− Discuss the implications of the data.
From: Swales, J. and Feak, C. (1994). Academic Writing for Graduate Students.
University of Michigan Press: Ann Arbor. p. 78.
− Help the reader to interpret the data
Bailey, S. (2011) Academic Writing: A Handbook for International Students (3rd ed.).
Routledge: Oxon, p. 162.
Sample
Table 5 shows the most common modes of infection for U.S.
businesses. As can be seen, in the majority of cases, the source of
viral infection can be detected, with disks being brought to the
workplace from home being by far the most significant. However, it
is alarming to note that the source of nearly 30% of viral infections
cannot be determined. While it may be possible to eliminate hometo-workplace infection by requiring computer users to run antiviral
software on diskettes brought from home, business are still
vulnerable to major data loss, especially from unidentifiable sources
of infection.
− From: Swales, J. and Feak, C. (1994). Academic Writing for Graduate
Students. University of Michigan Press: Ann Arbor. p. 78.
Structure of Data Commentary
Three main points:
1.Location elements and/or summary
statements
2.Highlighting statements
3.Discussions (implications, problems,
exceptions)
Structure of Data Commentary 1
Location elements and summaries
Location elements and summaries
Table 5 shows the most common modes of
infection for U.S. businesses. (active)
Location element
Summary
The most common modes of infection are
shown in table 5. (passive)
Common verbs used:
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Show
Provide
Give
Illustrate
Display
Present
Summarize
Reveal
Demonstrate
Indicate
Suggest
What kind of a summary
statement?
Indicative or Informative?
Indicative: stating the obvious
Table 5 shows the most common modes of
infection for U.S. businesses.
Informative: a summary of the data
Table 5 shows that home discs are the major
source of computer viruses.
The ’as –clause’
A common way to introduce an informative summary is using the
’As –clause”
As shown in table 5, home disks are the most frequent source
of infection.
Note the difference in the following statements!!!
As it has been proved, the theory may have practical
importance. (cause/effect)
As has been proved, the theory may have practical importance.
(announce or confirm)
The ’as –clause’ and prepositions
(announcing/confirming)
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As shown IN table 3,
As can be seen FROM the data in table 3,
As shown BY the data in table 3,
As described ON page 4
Structure of Data Commentary 2
Highlighting statements
Highlighting statements
Purpose: to demonstrate that
• You can spot trends or regularities in the data
• You can separate more important findings from those less important
• You can make claims of appropriate strength
You do not:
• repeat the details in words
• attempt to cover ALL the information
• claim more than is reasonable or defensible
Swales, J. and Feak, C. (1994). Academic Writing for Graduate Students.
University of Michigan Press: Ann Arbor. p. 86.
Sample again…
Table 5 shows the most common modes of infection for U.S.
businesses. As can be seen, in the majority of cases, the
source of viral infection can be detected, with disks being
brought to the workplace from home being by far the most
significant. However, it is alarming to note that the source of
nearly 30% of viral infections cannot be determined. While it
may be possible to eliminate home-to-workplace infection by
requiring computer users to run antiviral software on diskettes
brought from home, business are still vulnerable to major data
loss, especially from unidentifiable sources of infection.
Red text = highlight statements
Highlighting requires
• The writer to be cautious and sometimes critical.
• The writer to know how to express this caution.
• *Hedging*
So how do we hedge?
1. Different levels of probablitity
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It is certain that
It is almost certain that
It is very probable/highly likely that
It is probable/likely that
It is possible that
It is unlikely that
It is very unlikely/highly Improbably that
a reduced speed limit
will result in fewer
injuries.
2. Distance: Compare the following
• Consumers have less cofidence in the economy today than 10 years
ago.
• Consumers seem to have less confidence in the economy.
• Consumers appear to have less confidence in the economy.
• It would seem/appear that consumers have less confidence in the
economy.
•
Another alternative is to make the data ’appear’ soft:
• On the limited data available,
a lower speed limit
• In the veiw of some experts,
may reduce highway
• According to this preliminary study,
fatalities.
3. Weaker verbs:
This does not refer to the overused verbs (be, have, get,
try) but to those weaker in strength. For example:
Deregulation caused the banking crisis. (strong)
Deregulation contributed to the banking crisis (weaker)
4. Generalizations (covered in chapter 2.7)
Cocktails anyone?
These 4 elements are usually combined to
construct something reasonable and defensible:
Start with a big claim:
The use of seat belts prevents physical
injuries in car accidents.
Take ”The use of seat belts prevents physical
injuries in car accidents” then…
Change:
preventsreduce
reducesmay reduce
(weaker verb)
(weaker still)
Add:
In some circumstances (weaken the generalization)
certain types of injury (weakening the generalization)
According to simulation (adding distance – softening)
studies
End result?
According to simulation studies, in some
circumstances the use of seat belts may
reduce certain types of physical injuries in
car accidents.
= confidently uncertain 
Exercise 1 - Highlighting
Structure of Data Commentary 3
Discussions (implications, problems,
exceptions, etc.)
Discussions…
•
•
Use qualifying language, just like in highlighting phrases.
Usually follow the following structure
• Explanations and/or implications
• Unexpected results or unsatisfactory
data
• Possible further research or possible
predictions
usually required
if necessary
if appropriate
Sample again
Table 5 shows the most common modes of infection for U.S. businesses. As
can be seen, in the majority of cases, the source of viral infection can be
detected, with disks being brought to the workplace from home being by far
the most significant. However, it is alarming to note that the source of nearly
30% of viral infections cannot be determined. While it may be possible to
eliminate home-to-workplace infection by requiring computer users to run
antiviral software on diskettes brought from home, business are still
vulnerable to major data loss, especially from unidentifiable sources of
infection.
Red text = implications
Exercise 2 – the whole enchilada
Homework
− Chapter 2.11 – Visual information