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 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.

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 1Location elements and summaries

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

Common verbs used:

− 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)

− 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 2Highlighting 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

− 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

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: preventsreduce (weaker verb)

reducesmay reduce (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 3Discussions (implications, problems, exceptions, etc.)

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

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