Curating/Fermenting Data: Data Workflows for Semantic Web Applications

Workshop at NordiCHI 2022 pre-conference, Aarhus, Denmark: 9:15-17:00, October 8th, 2022

Organized by Magdalena Tyżlik-Carver (Aarhus University), Lozana Rossenova (Open Science Lab TIB), Lukas Fuchsgruber (TU Berlin)

We invite designers, data analysts, curators, computer scientists, archivists and others to collaboratively curate data. This workshop is organised as part of NordiCHI 2022 pre-conference in Aarhus and aims to experiment with speculative methods for curating data, while working practically with Linked Open Data tools and protocols for data modelling and annotation. During the workshop we will collaboratively create a structured dataset from ‘raw’ and unstructured data and we will document this process in order to critically reflect on decisions made during our workflows, also speculating on its possible future use and the way such dataset might be (mis)managed.

Workshop background:
In both machine learning and semantic web applications, a primary assumption about data – that data are raw and abstract and as such universal – continues to prevail. However, as a number of information studies, digital humanities and critical data studies scholars have argued, data has to be imagined in order to exist and function [1]. In effect, data models which are designed to process myriad data points and network relations obscure the fact that these data come from somewhere and that they had been collected under specific conditions that are social, historical, cultural and technological. To account for processes that facilitate data capture data should be understood as ‘capta’ [2, 3], not given but taken. This workshop invites cross-disciplinary collaborations to practically and theoretically interrogate systems of data capture and processing by engaging with materials, sources and tools.

Two main questions frame the workshop:
1. How to curate data so that the creation of a dataset delivers information about how it was created, by whom, for what reason and under what circumstances: We believe such information is important as it has the potential to “increase transparency and accountability.”[4]. Unpacking this problem requires attending to workflows more closely connected to the social processes surrounding data collection and the abstraction of data from real-world items and events into digital proxy concepts and processes. This is where the Fermenting Data project [5] will provide a rich context for workflow experimentation and reflection.
2. How to create and publish datasets that can be interpreted semantically, i.e. meaningfully, by both humans and machines: This is an HCI and more-than-human-design problem concerning the digital infrastructure that facilitates data curation workflows. We take the concrete environment of semantic web applications, more specifically – the public LOD platform Wikidata – as spaces that require design intervention and reconceptualising design patterns that befit mental models for interaction with non-hierarchical, complexly networked, yet traceable datasets.

Workshop methods:
• Fermenting data: Work with raw (physical) materials alongside their digital data proxies to create a case study dataset following the structuring principles of the semantic web.
• Prototyping: Collaboratively sketch out strategies towards making the underlying data model more visible and transparent to outside interpretation.
• Documentation: Discuss together decolonial frameworks around data publishing protocols through documenting the process of curation and annotation of the case study dataset.

Workshop benefits:
• Learn about the processes involved in curating and fermenting data.
• Learn about the organising principles of the semantic web and what roles they could play in improving data provenance and quality.
• Explore the linked open data environment of Wikidata.
• Contribute towards making data workflows more intelligible to fellow interdisciplinary researchers and end users alike.

How to apply:
In order to apply for the workshop, please send us a short letter (max. 2 pages) about your experience and/or interest regarding critical data work. Also let us know what you consider the most pressing issues related to data curation and data modelling? Finally, share with us your thoughts on fermentation as a speculative mode for working with data and more-than-human design. Please remember to include a short bio.

Please send you applications to: info [at]

Deadline for applications: (new deadline!) August 28, 2022

Workshop Organisers:
Magdalena Tyżlik-Carver is Associate Professor of Digital Communication and Culture at the Department of Digital Design and Information Studies at Aarhus University and Associate Researcher at Centre for the Study of the Networked Image at London South Bank University. She is curator of digital art and design and arts and humanities scholar of critical data studies. Her interdisciplinary research into computational cultures focuses on data as material practice where she explores how curating data can be a methodology for decolonial data practice.
Lozana Rossenova is a digital humanities researcher and designer. Her doctoral research focused on questions related to presentation and performativity in the online archive of born-digital art examined through the lens of interface design (theory and practice). Rossenova is currently based at the Open Science Lab at TIB, Hanover, working on the NFDI4Culture project towards a national research infrastructure of cultural heritage data. She is an active member of the Wikidata and Wikibase open source development communities, and a co-founder of the Wikibase Stakeholder Group.
Lukas Fuchsgruber is a post-doctoral researcher at TU Berlin in the collaborative project "Museums and Society - Mapping the Social" of TU Berlin, HU Berlin, the Institute for Museum Research of the State Museums in Berlin, and the Museum for Natural History Berlin. He studied art history and published his dissertation on the 19th century auction market in Paris (Das Spektakel der Auktion, 2021). Currently, he is investigating the digital image worlds created around museums, focusing on historical and contemporary social aspects of interfaces for digital commons.

[1] Lisa Gitelman and Virginia Jackson. 2013. “Raw Data” is an Oxymoron. MIT Press.

[2] Rob Kitchin. 2014. The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. SAGE Publications Ltd.

[3] Johanna Drucker. 2012. Humanistic Theory and Digital Scholarship. Pp. 85–95 in Debates in the Digital Humanities, edited by M. K. Gold. University of Minnesota Press.

[4] Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford. 2021. Datasheets for datasets. Commun. ACM 64, 12 (December 2021), 86–92. 10.1145/3458723

[5] Magdalena Tyżlik-Carver. 2020. Fermenting Data. Retrieved May 19, 2022 (

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