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Table 1 Participant ranking on the source of complexity in their data

From: Experts’ perceptions on the use of visual analytics for complex mental healthcare planning: an exploratory study

 

Overall Rank

Number of participants assigning each source of complexity at this particular rank (1–9)

Source of complexity

 

1

2

3

4

5

6

7

8

9

Structure (complex = more nested elements)

1

4

5

4

6

4

4

3

Variety (complex = multiple data types)

2

3

4

5

7

3

6

2

Relationships (complex = more interaction between elements)

3

4

5

7

1

2

5

4

1

1

Number of variables (complex = more measures)

4

4

3

3

6

3

2

2

6

1

Uncertainty and ambiguity (complex = more uncertain)

5

6

4

2

2

3

1

3

7

2

Contributors (complex = larger number of individuals or data points)

6

3

3

4

1

6

3

4

4

2

Abstraction (complex = further away from raw measures)

7

3

3

1

3

2

2

10

2

4

Size (complex = larger number of individuals or data points)

8

2

1

2

2

4

3

1

6

9

Difficulty of prediction or forecasting (complex = more difficult)

9

1

2

2

2

3

4

3

2

11

  1. Note. The rank, ‘1’ is the most central to their personal definition of data complexity, and ‘9’ is the least central. Numeric columns indicate how many participants ranked each source of complexity at that particular rank. ‘Overall rank’ indicates overall rank across participants, and it was calculated by summing these values and ordering source of complexity from the smallest value (globally the highest rank) through the largest value (globally the lowest rank)