The paper though concise, presents the content in a neat fashion which enables easy understanding of the material. I found that the authors have taken into consideration a lot of previous background work before breaking down the task list. It is always beneficial to know the pros and cons of the previous work, which I felt in this case that the authors did not do a fair job because they have generalized all the work into two points, one - only a few graph visualizations have been tested with real users and two - the tasks which have been used are very domain specific. There might have been cases where the graphs were only meant to serve a specific purpose.
For the beginners, the authors have explained the basic graph terminology which they refer to several times in the paper. It is interesting to note that most of the papers presented on graph analysis have been in the past decade. I am also impressed with the way how the authors have standardized the set of tasks which the users encounter. The examples which are associated with each task break down helped me understand what questions to expect which might seem obvious in the beginning. I am sure that these tasks are very helpful when constructing graphs which fit real data. The information relating to the higher level tasks - not performed by the low level ones will then be helpful when dealing with complex visualizations. The paper makes this transition by immediately mentioning about characterizing graph visualization tools in the section following the higher level tasks.
Future work is something which could have been included in the paper. I learnt the basics of creating good graphs from this paper which I look forward in implementing in my work dealing with graph visualizations.
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