When reflecting on the visualized data and playing around with this tool, I considered the questions below.
Is the visualization able to capture the reasons behind the choices?
This visualization cannot capture the reasons behind the choices. That would require the individual to have access to the quiz and everyone’s choice for each response. Instead, this visualization is a good representation of connections between individuals and their choices. It also affords the onlooker to understand the relationships and where to focus their attention or further research. What this visualization did allow me to interpret is the number of data entry points that were made in connection to each song. However, in order to achieve this, it required me to play around with the various settings. Nonetheless, although, I was able to see the number of data entry points connected to each song choice, I was not able to understand the reasoning behind each choice.
Reflect on the political implications of such groupings considering what data is missing, assumed, or misinterpreted.
When reviewing such a visualization tool, the onlooker must view it with caution or a degree of skepticism. Such a tool, from the outside, can appear to be very easily manipulated to meet the needs of the group that presents the data. Although this Stanford group had the best intentions when creating a relationship-linking tool, this same tool can be manipulated to meet the needs of the organization requesting a visualization of their data. This tool could provide individuals with data that can be interpreted to meet their needs or opinions. Likewise, this tool could be manipulated to meet the needs of the group entering the data. As stated on their website, this graphing tool “does not offer models against which to test hypotheses. Instead, tools need to support scholars in building an understanding of the historical material through working with it (Stanford Humanities and Design, n.d.).” Therefore, when using such a tool, one must assess the validity of the raw data entered to have a fair and honest look at the connections between the data points. A person should question where they get their media, the same person should be ready to analyze the data entry points of any one of these visualization tools to make a proper assessment.
Can the reasons for these “null” choices ever be reflected/interpreted in the data?
To a certain degree, the null choices can be reflected in the data through the sizing of the circles. When referencing the circles and connection piece, this program seems similar to the program iMusic uses when setting up an account. The iMusic program can curate the music that appeals to you most.
This curation begins as the curator can choose floating circles. These floating circles begin with similar sizing. The circles change size based on your previous selection to the last question. This Palladio program appears to be similar, as each track, from the Golden Record album that peers more frequently select is reflected by a larger circle. What is appreciated in this data is that the circles will move based on the positioning of other circles. It is almost like a trance watching them move as you play around with them.
Reference
Stanford Humanities and Design. (n.d.). Palladio. Palladio. Retrieved November 3, 2021, from http://hdlab.stanford.edu/palladio/