Assignment 1: Digitization
For this assignment I have chosen to work with souvenirs as my objects. The souvenirs, which
I am digitizing and labeling, are objects I have been collecting for over 20 years. They are usually dis-played as decorations in my apartment, but some of them are also being stored in boxes due to lack of space. With this dataset I will be able to overview all of my souvenirs without having to physically find them. I have created a folder in the Photo app on my MacBook, which has four subfolders (see picture 1). Each subfolder has a geographic place as its name and contains pictures of my souvenirs from countries within the places. I used the photo album to categorize the objects but have also organized the objects into a dataset us-ing a table and variables (see appendix 1).

Gathering
When working with data the curating of the data is rather important. In the article “7 Artists, 25 Pages Each, 1 Half-Century Later: Revisiting the Xerox Book” the author, Tiernan Morgan, mentions an exhibition called The Xerox Book (Tiernan M. , 2015). When doing so he expresses his main concerns about the exhibition, namely the curating, which in this sense refers to the layout of the exhibition. The first concern being the lack of representation of the actual Xerox Book and the second being the, in his opinion, odd way of displaying the artwork. These concerns have also been relevant in my collecting of souvenirs.
Morgan writes that “Only a handful of the works relate to or recall the Xerox Book project…” (Tiernan M. , 2015). Every part of the Xerox Book was available for the creators of the exhibition, but they chose to not include most of it. When starting the gathering of objects for this assignment
I was similarly in possession of all of the souvenirs beforehand. Therefor I also considered how many of my souvenirs should be included and whether souvenirs I had received as gifts should be part of this collection as well. Morgan is in his article clearly pointing out that he would had preferred that there were more parts of the actual Xerox Book present in the exhibition, which is why I chose to include all the souvenirs that I could find.


Digitizing
Morgans second concerns about the displaying I also found relevant for my collection.
I had a lot of concerns about how to digitize my souvenirs. They were all analogue, but some were actual artifacts and others were more two dimensional. Morgan writes the following about the choice of display: “The effect is both museological and reverential — qualities that the proponents of Con-ceptual art actively sought to avoid.” (Tiernan M. , 2015). Morgan expresses that he believes that the creators of the exhibition failed to display the Xerox Book in a way that lives up to the original intend (Tiernan M. , 2015). This was something I wanted to consider. I chose to only take one picture of each object as my collection was not supposed to be replacement for the real objects but rather a folder for me to remember which objects I have, when they are not all displayed.
I also chose to photograph all of the objects horizontally and with a white background to make the objects stand out and create a similarity throughout the collection.

Whenever creating something an important factor to take into account is the recipient. As mentioned, I created this dataset merely for my own remembrance, therefor I consider my recipient to be myself. In “After Six Months of Work…(1984).” the author, Jean-Francois Lyotard, describes how the recipient has affected the exhibition Immatériaux and more specifically the first project plan. He expresses that at this point in the curating of the exhibition the communication between sender and recipient was ra-ther useful (Lyotard, 2015). I started digitizing my objects by using my smartphone to take several pictures of them each. After a few pictures I reevaluated my process and came to the conclusion, that if I was the only recipient, the pictures did not have to show the objects from every angle as long as I could recognize them. Thereafter I took one picture of each and uploaded the pictures to Google Pho-tos and downloaded them to my computer.

Labeling
The fact that I was my own recipient was also important in my categorizing and labeling process. I categorized the souvenirs after which part of the world they were from. Originally, I had planned to divide the objects into different folder for each country. Though while working in Apple’s Photo app I discovered that I could simply geotag the different pictures, so that they would show up on a map (see picture 2). This made sense for me to do, since every object had a place origin, that was not where the actual picture was taken. In doing this I also somewhat maintained parts of the origin of the objects; an aspect of curating I earlier mentioned Tiernan Morgan thinking was important (Tiernan M. , 2015).

The geotagging also provides further data into the dataset. Though I had to manually tag every object, the map creates a different visualization than a table (see appendix 1) is able to. As can be seen in ap-pendix 1, the table is merely stating the different variables of the dataset. “We’re recognized and eval-uated as an aggregation of different measurable types.” (Cheney-Lippold J. , Control: algorithm is gonna get you, 2017, s. 145). This John Cheney-Lippold states in his book We Are Data. The varia-bles in the table are measurable types of data and provides, according to Cheney-Lippolf, information about the creator of the data as well as about the data itself. Such as the fact that most of the souvenirs are from either North or South America, which indicates that I, as the collector, has travelled there a lot. Therefore, these measurable types are a valuable part of the object and of the dataset as a whole.

To sum up the assignment it is important to consider your intent of digitizing object, most importantly your recipients. These considerations have a great impact on the communication between the sender and the recipient. Every part of the digitizing process provides the recipient with information about the data itself, as well as about the creator. A lack of consideration can therefor result in miscommunica-tion, such as a misinterpretation of the dataset, the intent and the collector.

Assignment 2: Datafication
This assignment will be focused on datafication and in particular how Facebook transform their users into data based on the values they assign to them. In their short essay Datafication the authors, Ulises A. Mejias and Nick Couldry, states the following: “…datafication combines two processes: the trans-formation of human life into data through processes of quantification, and the generation of different kinds of value from data” (Mejias & Couldry, 2019, p. 3). In accordance to this statement datafication can be seen as a way of giving the users of a digital platform, like Facebook, certain values based on their behavior. In reference to that I found it interesting to explore how Facebook has datafied me, as a user. Therefore, I downloaded all the information I was able to from the Facebook settings. After do-ing so, I browsed through the different folders and I chose to look at a folder named your_topics. This folder contained 75 different topics, that I had not chosen, but that Facebook had chosen for me. The description in the html-file stated that these topics were used to customize recommendations. It is also mentioned that the topis were based on my activities on the platform, which confirms Mejias and Couldrys definition of datafication. In this matter Facebook has transformed my online behavior into quantified data that can be used to tailor and affect my activities on the platform; they have assigned me 75 values.

In his book, We Are Data, John Cheney-Lippold writes about datafication and algorithmic regulation. Throughout the second chapter titled Control: Algorithm Is Gonna Get You he seeks to explain how he defines the term algorithmic regulation. “It knows us. It learns from us. It becomes an author of our lives’ knowledges, and all we have to do is provide it the words.” (Cheney-Lippold J. , Control: algorithm is gonna get you, 2017, p. 110). In this sentence Cheney-Lippold emphasis how it has be-come the data that controls us rather than the other way around. This is in some way is very similar to Mejias and Couldry definition of datafication. We, as users, are datafied by our own online behavior, as well as our online behavior being affected by the datafication. Cheney-Lippold mentions through-out the chapter that algorithmic regulation is very much intertwined with datafication (Cheney-Lippold J. , Control: algorithm is gonna get you, 2017). Every move a user makes on an online platform pro-duces algorithms that can be regulated and datafied. It is this type of datafication that the 75 values in the html-file is based upon. When taking this into consideration the assigned values indicate what I have interacted with online, but also what I will most likely continue to see on Facebook, since the values are used for future recommendations.


For the dataselfie I have, as mentioned, chosen to create it based on the topics from the html-file (see appendix 2). I separated the 75 topics into seven groups based on themes that I found common: Food, Craft, Pop Culture, Movement, Animals, Body and Games. Then I used Microsoft Excel to make a diagram that visualized the division. As the last part of my data selfie I added a profile picture from Facebook, which was a part of another folder. The diagram and the picture were each a representation of me, that Facebook had allowed me to download and therefore I found it fitting to merge them into one image. They each contained certain values the difference being that the profile picture is public, and the 75 topics are private, in the sense that only Facebook and I have access to them.

The visualization and categorization gave a clearer image of the different values and how some of them were related. As a result of this process I discovered that Facebook has determined my interests as approximately 25 percent food, 25 percent crafts, 25 percent pop culture and the remaining 25 per-cent divided in four smaller categories. It was not until I started categorizing the topics that I realized that such a large amount of the values was related. Because of the process of visualizing the data I got a different perspective on my behavior on Facebook, as the values are based upon that data. I do not usually notice which posts are recommended to me and which are on my homepage because some of my friends interacted with them. But this visualization might make me do so in the future.

I recognize some of the topics in the file as being posts I would normally interact with, but there were also several that I had not noticed as being topics I would usually interact with on Facebook. I found it interesting to explore this category of my Facebook information because of the part of this assignment involving a data selfie. Facebook has clearly created a dataset by assigning me different values. The dataset is based on their datafication and is supposed to represent me. This is usually what a selfie is also supposed to do. Though the difference here is that in a regular selfie you as the photographer determines the values you want to include. It can be discussed whether or not I have done the same when creating the dataselfie for this assignment. I have chosen what dataset to base it on and thereby which values to include. According to the definition of datafication I have even created all of the data. Facebook have merely curated it into certain usable values. Though I created the data these values are based on I did not determine the values and therefor it can be argued that this makes for a significant difference between a regular selfie and a dataselfie. I did however curate the values into smaller groups to visualize the dataset, which is somewhat conflicting with this point. Ultimately, I would state that there is a difference between the selfie taken as a photograph and the selfie created based on a dataset, because even though I am the creator of both selfies, the data selfie is generally based on the values assigned by Facebook.

During this initial study of datafication I discovered that Facebook categorized me, as a user, in a very specific way. Just as I categorized their topics and values assigned to me, they categorize me as some-one who would find interest in these topics and contained these values. As a further research I would like to analyze if and/or how the user is able to manipulate the datafication and their values based on their online behavior. As both Mejias and Couldry and Cheney-Lippold states datafication does not require much interaction from the user, other than their usual use of the platform. Therefore, it might be interesting to explore if the user is in any way able to deliberately influence the datafication and how that might affect the quantification.