Understanding Data
If we position data visualization in the context of digital humanities, there is a problem of definition. Literary disciplines, documents or history that receive the voice of the digital humanities remain connected to the text and ultimately inherit the methods of the humanities.
However, digital humanities also look at research related to sociology of uses, cultural studies, and media studies. In particular, methods and state data are considered native. More broadly, it is the scientifically applied practice and theory to make sense of the collection and analysis of data.
It is necessary to be familiar with and experience visualization, software tools, aesthetic codes, which are one of these applications. It also compares problems of epistemological nature, disciplines and fields of research.
On the other hand, it constantly refers to the social construction of what we know, namely our knowledge and data.
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First of all, it is difficult to generate data conforming to an aesthetic protocol that respects precise codes. It’s also a question of creating a well-structured, documented collection of data.
There is a discourse that gained momentum in the 2000s. The visualization of data is said to represent access to a sensory information. Because they are thought to be colorful, fun, related to the desire to see and curiosity.
There are so many elements that make up the core promise of visualizations. One of the reasons researchers are interested in them is that the uses are multiple, sometimes even extremely practical.
This is the case where data visualizations are used to communicate the result of the research to the general public.
Consider a digital social network map that doesn’t need to be self-explanatory, but creates a thought-provoking presence. The fact that they are accompanied enables play. It offers dialogue possibilities between the reader’s perception and the text and image.
In this case, the image tells and shows the text. Data visualization also makes it possible to re-problematize results in a way that is appropriate for the general public.
Dialogue Between Disciplines
Data visualization today offers other possibilities for initial communication during data collection, such as involving participants from the start.
The center of the visualization provides information about the links according to various criteria. He can also arrange them according to whether they are more or less close to him. He could make connections and create other groups of people.
During analysis, data visualization also serves as an intermediate communication tool to solve problems in the interdisciplinary nature of a project. Indeed, at the end of the first process, information gathering made it possible to generate even more data.
However, we have found that it is not always easy to read a regression table or an XML file, depending on the disciplinary skills involved.
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Therefore, it is necessary to find a way that will be understandable to people of all disciplines, engineers, computer scientists, anthropologists, and psychologists.
Finally, the results are organized through a specific visualization for analysis. This opens up a dialogue between different disciplines.
