View source for Evaluating Visual Table Data Understanding

== Authors ==
*[[Fekete%2C_Jean Daniel|Jean Daniel Fekete]] <br/>
*[[Henry%2C_Nathalie|Nathalie Henry]]<br/>


== Short description ==

Evaluation of how information visualization supports exploration for visual table data.
A controlled experiment designed to evaluate how the layout of table data affects the user understanding
and his exploration process. This experiment raised interesting problems from the design phase to the data
analysis. In this paper, we focus on evaluating how information
visualization supports exploration for visual table data.
We present a controlled experiment designed to evaluate how the layout of table data affects the user understanding
and his exploration process. This experiment raised interesting problems from the design phase to the data
analysis. A a task taxonomy, the experiment procedure and clues about data collection and analysis are presented. Concluding with lessons learnt from this experiment and the discussion of the format of future evaluation.

=== Controlled Experiment ===
 
In the experiment three table ordering algorithms commonly used to reorder
rows and columns of table data where used. The first order is
alphabetic (A) and considered as a control order. The two
others (C) and (T) are issued from the field of
bioinformatics. (C) is a hierarchical clustering followed
by a linearization. (T) is based on the traveling salesman problem. They
are used to reorder DNA microarrays (visual table data
presenting gene expressions).

=== Datasets ===

Two real datasets where chosen for the experiment. The datasets had to be interesting and of reasonable size to keep the experiment subjects interested. One dataset was  the university master´s grades and the second dataset was from the CIA World Factbook. This dataset consists of statistics of productivity, export, transportation for most of the countries in the world.

== Tasks ==

The experiment subjects had to complete tasks of different difficulties. The datasets where divided in three difficulties. At a high difficulty level of the dataset the experiment subjects have interpret a lot of the data, while looking at easier parts of the dataset the readability of the datasets where tested.<br/>
The experiment consisted of the following tasks: <br/><br/>
*'''Low Level: on represenation  visual coding'''
'''Readability:'''<br/>
Find a specified student or course<br/>
Give the grade for a given student and course<br/>
Find how many students followed a given course<br/><br/>
'''Interpretation:'''<br/>
Find the course where students performs better/worse<br/>
Find the student with the highest/lowest grades<br/><br/>
*'''Medium Level: on groups and outliers'''<br/>
'''Readability:'''<br/>
Circle a group<br/>
Give it a representative element of the group<br/>
Circle outliers<br/><br/>
'''Interpretation:'''<br/>
Give it a meaningful name<br/>
Give a representative element of the group<br/>
Explain why the are outliers<br/><br/><br/>
*'''High Level: on correlations and trends'''
'''Readability:'''<br/>
Give two Courses correlated/uncorrelated<br/><br/>
'''Interpretation:'''<br/>
Give two Courses correlated/uncorrelated<br/>
Give the main trends of this master (in terms of topics)<br/>
Explain how students/courses have been ordered<br/>

== Figures ==
Pictures of the data sets in different sort orders.<br/>
[[Image:VisualTables1.GIF|center|VisualTables]]
<br/><br/>
[[Image:VisualTables2.GIF|center|VisualTables]]
<br/><br/>
Task complexity<br/>
[[Image:VisualTables4.GIF|center|VisualTables]]
<br/><br/>

== Lessons Learned ==
*'''Do not use real datasets'''
*'''Do not ask too much'''
*'''Do not exclude free comments or open questions'''
*'''Do not leave too much freedom'''
*'''Do not underestimate training'''

== Important Citations ==
Main challenges of Infosky:
<br/>
{{Quotation|We chose two real datasets in order to conduct this
experiment in a realistic context. | [Fekete et Henry, 2006]}}
<br/>
{{Quotation|We encountered problems to create relevant
questionnaires for real datasets.| [Fekete et Henry, 2006]}}
<br/>
{{Quotation|Analyzing free comments, explanations or open questions
is a nightmare.| [Fekete et Henry, 2006]}}

== Reference articles ==

*[[Rao%2C_Ramana|Ramana Rao]], [[Card%2C_Stuart|Stuart Card]]. The table lens: merging graphical and symbolic representations in an interactive focus +
context visualization for tabular information in Proceedings of the SIGCHI conference on Human factors in computing systems: celebrating interdependence ACM Press, Boston, Massachusetts, United States 1994 318-322

*[[Schneiderman%2C_Ben|Ben Schneiderman]], The Eyes Have It: A Task by Data Type Taxonomy for Information Visualization. in IEEE Symposium on Visual Languages, (1996), p 336.