- Date of Class: 2/5
- First due: 2/12
- Comments due: 2/19
- Revisions due: 2/26
Our class started off by taking a look at Voyant, a tool for data visualization specifically for literary corpra. We discussed its very complex and overwhelming design, a few discoveries we thought were helpful and not as helpful(inaccurate) as we were trying to use the tool, as well as comparisons to Google Books Ngram tool. A few classmates pointed out that although voyant had much more to offer than google ngrams, the simplicity of Google Ngrams in speed, and design makes it the stronger tool. Here is a link portraying Voyant’s tool design when using the Dreamscape visualization. We discussed how this tool has a lot of potential for geographical mapping of data, however in this case it was very inaccurate because for a Shakespeare play with British names and places, the map was drawing parallels to US names and places rather than their British origins.
This exercise transitioned into our discussion about the tool design and affordances of Ngram interfaces. Affordances are the relationship and interaction between the technology and the user. Starting with the “Proceedings of the SIGCHI Conference on Human Factors in Computing Systems Reaching through Technology” reading, we began by discussing technologies and designs that we have interacted with that have high functionality, but low design aesthetic or high design aesthetic, but low functionality, and how interfaces that don’t meet user expectations in either case tend to be less popular. An example that appeared included the aesthetics of Apple products versus the functionality of Samsung products. We distinguished that there is an upheld value of aesthetics for designers where as engineers focus on functionality, and that depending on the user’s preference it is very important to find that balance between design and functionality. We then switched lenses and focused on user experience as a driving factor for objects designed for active exploration versus little to no exploration (when too much information or direction is given).
This lead into our thoughts about the Music Ngram Viewer. We thought that this tool allowed for a lot of exploration, and very little information or assistance in usability. This tool had more negative experiences from a design perspective for when interacting with the visual keyboard we were disappointed since we were not able to press down keys which may have been a more intuitive response to the tool. Many of us were not sure how to interact with the interface, and even as a musician I had difficulty inputting notes on the staff and more importantly obtaining data that provide any useful result. I personally had a hard time navigating the interface and had little to no success in obtaining meaningful results. In order to improve this tool, I would have a more guided approach for the user to feel less lost and frustrated. I would also allow for intuitive functionalities to be implemented, such as pressing the keys on the keyboard rather than typing in corresponding numbers. Here is a link to one example we viewed in class using this tool. One the other side of this argument in giving too much information, we mainly felt that providing more guidance is not a huge downside because it is more important that the user is able to use the tool, and then learn how to use it effectively. We also acknowledged that in this case the uses is not able to do as much self exploration which can lead to very diverse results and unexpected discoveries.
This interaction lead into our final question regarding this article about how much responsibility we should put on the user to pay attention to certain details in order to operate an object, and how much responsibility should be placed on the designer. As a group we felt that designers have a tendency to get caught up in the process of creating a working tool that sometimes they don’t consider potential issues that may go wrong when users with little to no experience using their tool get lost, frustrated, or overwhelmed if they are not given enough guidance. On the other hand, we also observed that tools that are designed to be extremely user-friendly can also come across as powerful or not a great tool for experts. We also felt that responsibility towards the user depends on many factors such as experience in using similar tools, purpose of using the tool, etc. Therefore, designers have the responsibility to consider whether a learning curve is detrimental or constructive to a product’s success.
Our discussion then moved on to discuss the next article titled “The Language of the State of the Union”. We looked at their interactive data visualization and compared it to a similar visualization in linked here, that portrayed the geographical terms and most popular topics in the history of US Presidential State of the Union speeches. While we didn’t get a chance to dive deeply into analyzing the actual data that was present, we briefly went over the effectiveness in this design as a positive visual engagement. Below however are questions to consider if more time was available.
- What are the design/user-interface implications of setting up an interactive chart like so? What works and what doesn’t, and more importantly, what type of story is being shared and what information is being ignored/omitted?
- What was the most interesting term and trend that you observed? What surprised you or didn’t surprise you?
- When looking at words such as “war”, “her”, and “currency” what does the trend say about language changing over time?
- What words do you think should have been included into this study?
The concluding part of our discussion quickly went into possible ways to improve a ngram data visualization tool that we have become quite familiar with, the Google Ngram Viewer, when compared to a newer tool, the HathiTrust bookworm tool. A few of our ideas included that the Google Ngram Viewer does not have labels on the x or y axis, thus assuming that all its users should know what the data being shown is representing which may cause confusion. In addition, Google Ngram Viewer does not allow the user to control the y axis scale which is constantly changing depending on the data being analyzed, thus making it harder to create more meaningful visualizations. We also proposed that Google Ngram Viewer does a good job by providing the opportunity to look more in depth between time periods, however the actual duration of time for the given sectioned out periods are not the same amount and could be confusing. Additionally, HathiTrust allows for a filter option that is intuitive to use and easier to navigate in comparison to Google Ngram’s language of specific syntax for various functions. In terms of higher functionality, we felt that it would have been beneficial if the Google Ngram Viewer allowed the user to click on the line and interact with the the data represented at the point.