Curating Data: activating critical curatorial practices against data determinism

TY - ABST

T1 - Curating Data: activating critical curatorial practices against data determinism

AU - Tyżlik-Carver, Magdalena

PY - 2025/6/11

Y1 - 2025/6/11

N2 - In contemporary digital cultures, what we know and how we know it is technologically reorganised and becomes part of algorithmic and platform curation, data curation, and machine learning. Selection, categorisation, and forms of display, which have been always part of curatorial work, are automated and guided by questions such as how can we see billions of images (Manovich 2020) or how to distinguish fake content from what is real? These are practical concerns about the ways in which human and algorithmic abilities to sort, categorise, label, and retrieve information and data, texts, and images come together and to what ends? While seeing or reading is done with algorithms in, for example, “distant reading” (Moretti 2000) or different forms of algorithmic vision (Cox 2016; Paglen 2016; MacKenzie and Munster 2019) curating characterises the ability to collect and archive data and often to make them accessible publically and for future reuse. In this context, curating data proposes critical methodology that intervenes into automated forms of knowing by acknowledging posthuman agents of curating as subjects and objects of curatorial concern, and by attending to infrastructural arrangements necessary to maintain and process data. This presentation will first introduce Curating Data diagram which sketches out curatorial methodology to engage critically with data and its processing as social, cultural, creative and political practices and not only technical phenomena. The diagram serves also as a blueprint for research design and a method to record and track what takes place in the process of curating data, and how agency is distributed. I will then use Curating Data diagram to map what is part of curating data in curatorial and research project Fermenting Data, which is a speculative intervention and experiment that works against data determinism by asking: what if data could be fermented? I will answer this question by identifying practices (artistic, curatorial, participatory), infrastructures and ontologies (WikiData and Linked Open Data) that are activated through this project.

AB - In contemporary digital cultures, what we know and how we know it is technologically reorganised and becomes part of algorithmic and platform curation, data curation, and machine learning. Selection, categorisation, and forms of display, which have been always part of curatorial work, are automated and guided by questions such as how can we see billions of images (Manovich 2020) or how to distinguish fake content from what is real? These are practical concerns about the ways in which human and algorithmic abilities to sort, categorise, label, and retrieve information and data, texts, and images come together and to what ends? While seeing or reading is done with algorithms in, for example, “distant reading” (Moretti 2000) or different forms of algorithmic vision (Cox 2016; Paglen 2016; MacKenzie and Munster 2019) curating characterises the ability to collect and archive data and often to make them accessible publically and for future reuse. In this context, curating data proposes critical methodology that intervenes into automated forms of knowing by acknowledging posthuman agents of curating as subjects and objects of curatorial concern, and by attending to infrastructural arrangements necessary to maintain and process data. This presentation will first introduce Curating Data diagram which sketches out curatorial methodology to engage critically with data and its processing as social, cultural, creative and political practices and not only technical phenomena. The diagram serves also as a blueprint for research design and a method to record and track what takes place in the process of curating data, and how agency is distributed. I will then use Curating Data diagram to map what is part of curating data in curatorial and research project Fermenting Data, which is a speculative intervention and experiment that works against data determinism by asking: what if data could be fermented? I will answer this question by identifying practices (artistic, curatorial, participatory), infrastructures and ontologies (WikiData and Linked Open Data) that are activated through this project.

UR - https://stsitalia.org/conference.pdf

M3 - Conference abstract for conference

SP - 480

EP - 481

T2 - 10th STS Italia Conference. Technoscience for Good

Y2 - 11 June 2025 through 13 June 2025

ER -