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Subjectivity in Data

by Nis Repenning

This project shows three different forms of digitization and archiving, the goal of it is to show the sheer complexity of digitization and how the way we are doing it has a large impact. As often said is data never raw (Gitelman 2013) and our decisions on how we choose to cook the data have created an impact on the latter outcome. While two of the examples show how I/We choose to digitize given things - in this case, my small rubber ducks, as well as books, papers, articles, and journals surrounding data, the third one shows how other people created data about me, in this case, Facebook.

All these examples show which subjectivity something like data has. Donna Harraway situated knowledge

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Facebook

Take my Facebook project as an example, the downloaded dataset I used had hundreds of different smaller datasets in it, but I actively choose to use three specific datasets, thereby not showing the rest of them, and creating a clear differentiation for the reader for what I found interesting and whatnot.

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Rubber ducks

The goal for the rubber ducks was to represent these physical objects in a digital format; this is what Hui also calls the objectification of data (Hui 2016, p. 50). However, shows it that even so simple objects as small rubber ducks are impossible to digitize without leaving some aspects/context out.

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Library

Thirdly we made a digital library surrounding the theme data and various subterms. Here it was up to us to categorize and tag these texts in a way that would not only make sense to us but in a best-case scenario also to others. This made the library highly subjective to our understanding of how others would interpret and use this library.

In the end, even looking at this project as a whole it has the same problem as each of its individual parts, I will never be able to account for all the different aspects of the things I worked with, at some point I will have to choose what I find most important and hoping that others will agree.