In a brief summary of D’Iganzio’s perspective that “Data visualization (is) one more powerful and flawed tool of oppression”, it is necessary to understand the points that lead up to this point of view. To clarify, D’Iganzio’s article addresses the powerful amount of rhetoric that is present through data visualizations. In fact, data visualizations have become generalized to that point that much of the information that creates our perceptions has become misconstrued in one way or another. Specifically, data visualizations have been generalized in form to be appealing to certain audiences, genders, or small groups of people for one purpose: to persuade. D’Iganzio argues through the reflection of cartographers, mapmakers, and other analytics how data generalization can be avoided. In addition, D’Iganzio proposes three different solutions to the initial issue of data visualization becoming generalized: including missing information that has been lost through data generalization, making data references to become more reputable and connectable with the ‘real world’, and re-situating data to become interactive. After all things presented within D’Iganzios article, “Feminist Data Visualization”, it is apparent the need to reconsider how information is presented to different audiences, and to find a “Neutral point of view”.
{Link to particle: https://civic.mit.edu/2015/12/01/feminist-data-visualization/ }
In response to D’Iganzio’s article, I completely agree with the perspective that data visualizations are misrepresented. I have found throughout my college English class that the accessibility to information is more often than not influenced by biases and much of the data that is meant to be represented is left in the dark. Furthermore, I can agree that data visualizations are often presented to add to opinions of particular groups of individuals, but I have yet to experience data visualization to the extent of oppression. As a matter of fact, I believe it to be a societal issue to take only the information of one data visualization, rather than an issue of how information is presented. To clarify, I have found data visualization to be so readily available from the advancement of technology, especially online sources like Google that it has become an excuse for society from digging deeper into the information that they are receiving. As a result, individuals are already at a loss from retaining all aspects of a data visualization set due to the internal instinct to settle for less.
Correspondingly, within an novel discussing the world of “Big Data”, it is presented in an abstract way, the idea of a hypothesis driven approach. To understand the connection between data and data visualizations, I think it is very overwhelming the revolutionizing way data is being analyzed. Continuing, data was once looked at to be utilized for a cause and effect result, much like how data visualizations are utilized to show a trend of information or to add to a topic. Now, as technology becomes the new way of how the world operates, the overabundance amount of data does not have a direct relationship with an effect like it once did. In a produce/consumer world, it is inefficient to decipher every piece of data that presents itself, so only parts of data are actually being analyzed for the purpose of selling more product or producing more goods. On the other hand, data visualizations in their popularity must be analyzed in their entirety, each for their own biases, purposes, and missing information. All in all, it is imperative to look at different aspects of data and/ or data visualizations and depict them for their purpose and the surrounding influences that may lead them to be misconstrued.
Reference: Mayer- Schonberger, Viktor and K. Cukiek. “Big Data: A Revolution That Will Transform How We Live, Work, and Think.” (2013).
A Healthy Relationship 