Infrastructuring Contingency - Daten, Geister & Intelligenzen 🐁

# Infrastructuring Contingency: A Praxiography of Humanities Research Data Infrastructures > [!tip] Reference > Paper for the panel *The Interpretive Layer: Expertise as Infrastructure in Sociotechnical Systems* at DASTS, 2026-06-30. ## Intro This talk is about research data in the humanities, and it is also about the technologies and the expertise that mobilise this data. Right now, research data _infrastructures_ are gaining ground, at least in the German academic landscape. National data networks are consolidating, and universities are building permanent advisory bodies that offer research data consulting. This is not necessarily a bad thing, of course. But when infrastructures become more rigid, proposals can become standards. The research I am presenting today is not about this situation as a whole; rather, I report from a specific site close to the humanities. Let's take a look. ## Field, Method, and Ontology Let me introduce you to my field. I work in what is called a Collaborative Research Centre, one of the larger funding formats of the DFG, the German Research Foundation. The consortium consists of around 70 people, distributed across 15 sub-projects from different disciplines and on different topics. My project is an official part of this consortium, and it is tasked with studying research practices within it. This stands in the tradition of laboratory and infrastructure studies, and I pursue it by focusing on the use of infrastructure and technologies. My method is a praxiography — that is, an ethnography of practices, drawing on Annemarie Mol. In practice, this means I do participant observation, interviews, workshops, surveys, and experimental design. ![[IMG_1699_compressed.jpg]] ![[IMG_3967_compressed.jpg]] ![[IMG_8566_compressed.jpg]] ![[IMG_7532_compressed.jpg]] Let's take a look at the Research Centre itself. This is not a natural-science consortium but one for the humanities, cultural studies, and social science. Overall, the consortium has a strong (German) _media studies_ vibe. Topics include, for example, narrative strategies in eighteenth-century literature, the social life of Renaissance libraries, robots and their sensors, exhibition practices for virtual reality media, and the material conditions of data centres. There is a pronounced interest in digital technology, and the everyday ways of working are likewise digitalised — email, Microsoft Office, files in folders. The research methods, however, are not "digital" or "computational" in the sense of the Digital Humanities. This is what I call the _postdigital humanities_: digital and non-digital topics are equally relevant, and everyday work is digitalised, but without the methods themselves being computational. ```mermaid flowchart LR Programs["Programs Exploring the contingency of meaning"] Practices["Practices Materially fix traces of meaning"] Programs <--> Practices ``` We have already made it through the basics. What follows is my proposal for how to map this site. The aim is to better understand the humanities' research data and their infrastructures. To get there, I distinguish two layers. The first are the _programs_: what are the goals of the research? The second are the _practices_: what do researchers do to get there? ## Programs: Cultivating Contingency Let me start with what I call programs. These are the goals and values of humanities research in my field. What do the researchers say they want to achieve? Here are three quotes from my interlocutors. ``` I actually want to present problems. I want to make things complex, complicated. ``` ``` [It is about] foregrounding the speculative dimension, that is, what could be, not what is. ``` ``` I like to read. […] Maybe it really is just about text. […] The humanities is about conceptual work and exploring meaning. ``` This is what I hear a lot: complexity, speculation, and text. I call this program _Cultivating Contingency_. _Contingency_ refers to circumstances that are neither necessary nor impossible, and _cultivation_ means that it is a careful, long-term process. So cultivating contingency is a systematic exploration of what is possible. This happens as part of various procedures: interpretation, critique, historicisation, genealogy, and speculation. The objects of this work are mostly texts, but they can also be artefacts or technologies. All of this happens in the medium of meaning. With Niklas Luhmann, meaning can be understood as a semantic super-medium that underlies all mental and communicative processes. Whenever something makes sense, it happens in the medium of meaning, and cultivating contingency is all about exploring the basically endless possibilities of this semantic medium. There are, of course, other programs in my field too, but this one is probably the most prominent. And it is especially important when it comes to research data, as we will hear in a minute. Let me summarise this part in one sentence: humanities researchers in my field like to cultivate contingency; they value a systematic exploration of what is possible. ## Practices: Data and other modes of materialising meaning So _cultivated contingency_ is what humanities researchers aim for. But in order to produce _high-quality meaning_, some practices have to be carried out. It is not very clear what one is supposed to do here. There are two recent German publications on practices from within the humanities: _Geistesarbeit_ by Martus and Spoerhase (2022), and a second one by Sybille Krämer, who has been researching the material and practical dimensions of humanities work for quite some time. I am showing you this to highlight that the question of practices is also a current question within the humanities. Here is a quote from Krämer's book: > "There are no humanities without […] objects such as documents, monuments, and artefacts […] being searched for, collected, dated, labelled, classified, edited, compared, commented on, and archived" (Krämer 2025: 12f). These are precisely the practices that are of interest here. My strategy for collecting and examining them empirically is a broad concept of research data. ![[spuren-00_compressed.jpeg]] ![[spuren-02_compressed.jpeg]] The concept goes like this. Data only exist in the course of _data practices_, and these practices always aim to _fix traces of phenomena_. In the natural sciences, these would be traces of natural phenomena, like a gene sequence. In the case of the humanities, these phenomena belong to the realm of meaning: taking notes during a talk, underlining a sentence in a text, or dragging a PDF into a folder. All of these are data practices insofar as they fix and materialise traces of meaning — like "this sentence is relevant", or "this PDF fits into a folder called _Definitely Read Later_". Here is an overview of the data practices I found in my observations and interviews using this heuristic. Each of the boxes is a category of data practice. The categories are sorted into three larger groups — _production_, _management_, and _logistics_ — plus a residual category for non-research activities. The open lists within the boxes are the formats and applications with the help of which these data practices can be carried out. | Data production | Data management | Data logistics | Project work | | -------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | ----------------------------------------------------------------------- | | *Recording* Etherpad, Hedgedoc, Textedit, Zoom, Audio Recorder … | *Collection* media/rep/, dblp bibliography, Gemeinsame Normdatei, Search Engines, LLM … | *Transfer* Email, Sciebo, Google Drive, WeTransfer, FTP … | *Deliberation* Email, Slack, Element, Zoom, Phone … | | *Text processing* Microsoft Word, Google Docs, Overleaf, Onlyoffice, Obsidian … | *Annotation* Apple Preview, Adobe Acrobat, Zotero, VisColl, Obsidian … | *Storage* External drive, Sciebo, ReSeed, Google Drive, iCloud Drive … | *Coordination* Calendar, Date Polls, Trello, Email, Todo Lists … | | *Analysis/Synthesis* MAXQDA, Obsidian, Cortext, Group Interpretation, Data Analysis … | *Organisation* Zotero, Bookends, Citavi, Sciebo, Google Drive … | *Publication* Publisher, Youtube, media/rep/, Obsidian Publish, Journals … | *Information* Mailing Lists, RSS, Blog, Mastodon, Bluesky … | I call all of this the _infrastructural ecology_ of my field. It is not one infrastructure but a conglomerate of tools, connected only through the humanities scholars' everyday work. This is the practical, technical, and often underestimated side of humanities work — or, as Hans-Jörg Rheinberger puts it: > "It is the area that extends between the agents of knowledge and the objects of their interest \[…]: the underworld of research technologies" (Rheinberger 2021: 17). Let me summarise this part quickly. When we apply this heuristic to research data as practices of fixing traces of meaning, the field reveals its infrastructural ecology: a loosely connected cluster of digital and non-digital tools that helps to explore the medium of meaning. ## Outro: Infrastructuring Contingency ```mermaid flowchart LR Programs["Programs Exploring the contingency of meaning"] Practices["Practices Materially fix traces of meaning"] Programs -->|Cultivating Contingency| Practices Practices -->|Infrastructuring Contingency| Programs ``` A few words to conclude. On the one hand, humanities researchers are all about exploring the contingency of meaning. On the other hand, they work with many tools, deploying data practices to temporarily fix traces of meaning. At this point, we arrive at the title of the talk: _infrastructuring contingency_. At first glance, this might seem an _oxymoron_, a contradiction. But humanities researchers do precisely this all the time, _somehow_. I chose the term to mark what I believe is a central challenge for researching, intervening in, and developing humanities research infrastructures. Solving this is an essential part of their expertise — but there is also a lot of potential for change here. I will end here, but I would love to keep discussing this with you.