Step
1
: Read the data set
description (from website and
dataset itself), carry out data
abstraction on the provided data
set. (10
points total)
·
in a Word document,
write down the dataset
type. (1
point)
·
Write down the
number
of
fields/attributes. (1
point)
·
Analyze each field in
terms of attribute
abstractions: write
down a concise
description in domain
–
dependent language of
the field’s meaning;
decide the attribute
type and write that
down. (8
points)
Step 2
: Analyze the cardi
nality (10
points total)
Write down
the number
of total
items (1 point), and
·
For each attribute,
indicate its cardinality.
(4 points)
·
For categorical
attributes, write down
the number of
unique
levels. (2
points)
· For quantitative attributes, specify the range from min to max and note any other characterization that seems potentially useful (cyclic? Anything else?) (2 points)
· For ordered attributes, consider whether it would be more useful to treat them categorical or quantitative, or to preserve them as ordered. (1 point)
Step 3: Write three questions you would like to answer with this data set, from the point of view of an aid worker reporting to the government of a country providing aid. (30 points total, 10 points for each question)
For each question, write the following information:
· Do you need a chart in order to answer this question? (1 point)
· If none of your questions require a chart, try to create a few new ones that might benefit from one.
· Which fields/attributes do you need to use to answer the question? (2 points)
· Do you need to transform the data in order to answer the question? If yes, what transformations are needed? (2 points)
· Do data set type and attribute type change when you need to transform the data? If yes, how do they change? (2 points)
· Do you have all the data you need to answer this question, or would you need additional data fields that are not provided here? (3 points)
Step 4: REFLECT/DISCUSS: What did you learn in this exercise? (5
points)
How might this analysis be useful in visualization design? (5 points)
Step 1
: Read the data set
description (from website and
dataset itself), carry out data
abstraction on the provided data
set. (10 points total)
·
in a Word document,
write down the dataset
type. (1 point)
·
Write down the
number of
fields/attributes. (1
point)
·
Analyze each field in
terms of attribute
abstractions: write
down a concise
description in domain
–
dependent language of
the field’s meaning;
decide the attribute
type and write that
down. (8 points)
Step 2
: Analyze the cardi
nality (10
points total)
Write down the
number of
total
items (1 point), and
·
For each attribute,
indicate its cardinality.
(4 points)
·
For categorical
attributes, write down
the number
of
unique
levels. (2
points)
Step 1: Read the data set
description (from website and
dataset itself), carry out data
abstraction on the provided data
set. (10
points total)
in a Word document,
write down the dataset
type. (1
point)
Write down the
number of
fields/attributes. (1
point)
Analyze each field in
terms of attribute
abstractions: write
down a concise
description in domain-
dependent language of
the field’s meaning;
decide the attribute
type and write that
down. (8 points)
Step 2: Analyze the cardinality (10
points total)
Write down the number of total
items (1 point), and
For each attribute,
indicate its cardinality.
(4 points)
For categorical
attributes, write down
the number
of unique levels. (2
points)
Source
data_2000-2011
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