Like every software NodeGoat has some limitations. For simple data analysis with single edges and not a lot of nodes it works very fine. The problems come when the amount of data is increased. The first one is that as it doesn’t have provided layouts for data input, to make these it takes a lot of time and it also doesn’t support a lot of types of input. In the visualization field is has problems with too much information because it overlaps, lags, and becomes really hard to navigate. It also doesn’t have interface for accessing information that is not presented in the visual network, but is present in the input. The site is not very user friendly, but still is well made.
From all of these problems and interactions I learned a lot about how should such a software look like and what should it be able to do. Firstly, especially in our project where there were different types of people (actors, directors, etc.) I think color coordination, plus a legend, would be very useful. When a project has more than two types that are connected it becomes really hard to understand and navigate, which was pointed out by most of the authors that we had to read for the class. Not only does it complicates more but it also loses its meaning when there is no differentiation from person to person or object. The only conclusions I am able to draw from the network we created are concerned with the “volume” of each producer or film – how many others were connected to it, but not with specific patterns that emerge.
In order for one to find patterns she should keep the information included as limited as possible. As Weingart said in his writing about Networks, in order to make use of them one has to be very focused in her choice of nodes and edges, and to be very careful with symmetric and asymmetric relationships. In the case of Egyptian Movies I think we over complicated the network by adding so much information about the relationships between different people that the connections to movies literally disappeared under a web of marriages and divorces.