Without humans, knowledge would not exist. Every aspect of our lives and everything we know; we know because people have defined it. Knowledge and the production of it is something that humans have as far as we know, always grappled with. In 1988 Ackoff (1988) proposed the Knowledge Pyramid in which he argues that wisdom is acquired through a process starting with data from which information can be extracted though an analysis process. Then the information can become knowledge, which lastly, can become wisdom. In todays' age which is characterized by the rise of Big Data and an increasingly digitized world, the data we are dealing with is largely digital.

As we are more on digital platforms, we are also increasingly being confronted with data presented in various ways. However, there tends to be the assumption that the statistics and data presented are neutral and or objective. Dwelling into the process of curating data, it becomes evident that this process is far from neutral. Behind it all there is a process which relies on the curator and editorial choices. These curatorial elements not only shape the data production but affects the whole knowledge production. This process is hidden and usually goes unnoticed.

This web exhibition aims to show how neutrality in curating data is constructed and show the curatorial decision choices which lies behind. By going through the three assignments this course has included, the exhibition will show the work behind, graphs that was excluded, thoughts, considerations and choices which all came to shape the final product. The goal is to show the audience how much manual, human labour is behind and challenging the assumption that data is neutral.

By displaying several of the design elements which occurs as invisible labour, this exhibition also reveals something bigger. Because design choices are not merely about choosing which graph looks the prettiest or fulfill Edward Tufte’s ideas on “graphic excellence” (2007), but also shows how all these both small and big design choices from color of line on graph, to how we classify, to the start of the collecting the data. All these elements add up and they shape what comes to be knowledge. These design and curatorial elements shape what in the end becomes the knowledge we acquire, the knowledge we teach, and the knowledge and information we save and store for future generations about the world.

Curating data:

The invisible human labour behind

Curatorial statement

By Amalie Hauge

Assignment 3: Visualizing and visceralizing

The data people encounter in their everyday lives is often in forms of visualizations e.g. statistics like the 2 graphs presented above.

These might to the regular person look, nice, neat, and neutral. However, behind each visualization is a hidden or invisible process shaped by curatorial design choices.

Assignment 2: Categorizing Referencing Knowledge Resources in Linked Open Data

Assignment 1: Collecting objects and building dataset

Dataset: Book collection 2025

Ending at the beginning of the process of curating data: collecting the data.
For there to be visualizations it relied on a structured and categorized dataset, and before the data can be classified the data must first exist.



The process of collecting data is far from a neutral process according to Kitchin.
It is e.g. shaped by:
- Tools that have been used
- the context; cultural, historical, geographical
- political ideologies and world views

"Data as Capta" (Kitchin 2022)

If you are part of the people who despite what people say still uses Wikipedia, you have probably encountered one of these fact boxes.
These boxes come from WikiData, the world's largest linked open database, where thousands of volunteers contribute to add data.
While it might be hard to contest against basic facts such as when one was born, there is a process behind that relies on manual work by the curator and which can shapes the knowledge produced. This process is categorization, and is how we classify and structure data.


I have provided a guide on how to structure data and add the extracted information to WikiData, to show the process behind and shed light on the "invisible" process.