Making Sense of Knowledge

Okwui Enwezor
"Participating and witnessing histories unfold." — Okwui Enwezor

A Collective Archive of Practice & Theory

Curatorial Statement

This exhibition represents the culmination of a semester's work in the Curating Data elective at Aarhus University. As a collective of four students, we have revisited our individual archives—datasets, reports, and visualizations—to articulate the histories that unfolded in our learning during this course, taught by Midas Nouwens and Magdalena Regina Tyzlik-Carver.

Throughout the semester, our curating data efforts have been shaped by the understanding that data are not neutral facts but constructed artefacts. Guided by Wernimont's notion of quantification as world-making and Kitchin's definition of data as capta, we have approached data practices as interpretive, political, and situated. Working with the Curating Data Model has allowed us to conceptualise our assignments, workshops, and fieldwork within a shared taxonomy of data practices, highlighting how collection, classification, cleaning, and visualisation actively shape meaning.

Our practical work has involved critically observing and performing data practices, identifying the assumptions embedded within them, and contributing to the ongoing expansion of the model. In this way, we have come to see curating data as a critical, reflective, and methodological practice that negotiates theory and technique to reveal how data come into being and how they participate in making worlds.

01

Collecting Objects and Building Dataset

How data can be shaped by choices

Lecture Notes

We started by collecting and choosing what to write down. These notes helped us see that data can be capta: captured, not simply given.

After collecting, we started to sort. Categories can make things comparable, but they can also hide context.

02

Categorization – Referencing Knowledge Resources in Linked Open Data

How classification can change what becomes visible

Group Notes

We worked together. These notes show how we talked through categories and structure.

Next, we asked what a visualization can do. It can explain patterns, but it can also try to create feeling.

03

Visualising and Visceralising

How visualization can feel personal, not only informative

PowerBI Dashboard Canva Draft

We explored in PowerBI. We designed in Canva. We tried to move from analysis to emotion.

Assignment 4

A collective exhibition by

Jakob Munch-Brandt

Mikkel Tagesen Knudsen

Sebastian Kjær

Tobias Kyhn Mikkelsen

Bibliography

Sources & Theory

Rob Kitchin

Kitchin, R. (2025). Critical data studies: An A to Z guide to concepts and methods. Polity Press.

Kitchin, R. (2022). The data revolution: Big data, open data, data infrastructures and their consequences (2nd ed.). SAGE.

Amelia Acker

Acker, A. (2021). Metadata. In N. B. Thylstrup, D. Agostinho, A. Ring, C. D'Ignazio, & K. Veel (Eds.), Uncertain archives: Critical keywords for big data (pp. 33–42). MIT Press.

Wernimont, J. (2018). Numbered lives: Life and death in quantum media. MIT Press.

Bowker, G. C., & Star, S. L. (1999). Sorting things out: Classification and its consequences. MIT Press.

Rowley, J. (2007). The wisdom hierarchy: Representations of the DIKW hierarchy. Journal of Information Science, 33(2), 163–180.

D'Ignazio, C., & Klein, L. F. (2020). Data feminism. MIT Press.

Nadim, T. (2021). The datafication of nature: Data formations and new scales in natural history. Journal of the Royal Anthropological Institute, 27(S1), 62–75.

Loukissas, Y. A. (2019). All data are local: Thinking critically in a data-driven society. MIT Press.

Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE Symposium on Visual Languages (pp. 336–343).

Tufte, E. R. (2018). The visual display of quantitative information (2nd ed.). Graphics Press.