2. Data commentary

3. 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.

4. 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 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.
From: Swales, J. and Feak, C. (1994). Academic Writing for Graduate Students. University of Michigan Press: Ann Arbor. p. 78.

5. Structure of Data Commentary
Three main points:
Location elements and/or summary statements
Highlighting statements
Discussions (implications, problems, exceptions)

6. Structure of Data Commentary 1
Location elements and summaries

7. Location elements and summaries
Table 5 shows the most common modes of infection for U.S. businesses. (active)
The most common modes of infection are shown in table 5. (passive)
Location element
Summary

8. Common verbs used: Show Provide Give Illustrate Display Present
Summarize
Reveal
Demonstrate
Indicate
Suggest

9. What kind of a summary statement?
Indicative or Informative?

10. 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.

11. 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)

12. The ’as –clause’ and prepositions (announcing/confirming)
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

13. Structure of Data Commentary 2
Highlighting statements

14. 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.

15. Sample again… Red text = highlight statements
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

16. Highlighting requires
The writer to be cautious and sometimes critical.
The writer to know how to express this caution.
*Hedging*

17. So how do we hedge? 1. Different levels of probablitity
It is certain that
It is almost certain that
It is very probable/highly likely that a reduced speed limit
It is probable/likely that will result in fewer
It is possible that injuries.
It is unlikely that
It is very unlikely/highly Improbably that

18. 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.

19. 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)

20. 4. Generalizations (covered in chapter 2.7)

21. The use of seat belts prevents physical
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.

22. Take ”The use of seat belts prevents physical injuries in car accidents” then…
Change: preventsreduce (weaker verb) reducesmay reduce (weaker still) Add: In some circumstances (weaken the generalization) certain types of injury (weakening the generalization) According to simulation (adding distance – softening) studies

23. = confidently uncertain 
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 

24. Exercise 1 - Highlighting

25. Structure of Data Commentary 3
Discussions (implications, problems, exceptions, etc.)

26. Discussions…
Use qualifying language, just like in highlighting phrases.
Usually follow the following structure
Explanations and/or implications usually required
Unexpected results or unsatisfactory data if necessary
Possible further research or possible predictions if appropriate

27. 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

28. Exercise 2 – the whole enchilada

29. Homework
Chapter 2.11 – Visual information