The DATA LAB is a forum for collaborative co-creation and experimentation with diverse forms of doing and communicating academic knowledge.

 We meet across disciplinary, institutional and career-stage boundaries to inspire informal scholarly conversations, share experience, experiment, talk, learn together, and develop critical approaches to themes that concern the politics of “data” and of digital technologies in our scholarly practice.

The DATA LAB aims to facilitate new conversations and collaborations and will evolve in through ideas and suggested themes from the participants in workshops. The informal workshop format complements the existing traditional seminar groups and text focused work and allows for new ways to be creative, explorative and playful within academia. We cover a broad variety of contexts such as, but not limited to, everyday life, the production of knowledge and culture, urban governance, health, environmental and energy politics, or warfare.

We are inspired by STS, feminist technoscience, media studies, anthropology, philosophy of technology, critical data studies, visualization research, the digital humanities, digital sociology and related fields.

When?

Mondays or Wednesdays, 3-4 times per term, starting from Spring 2023

Organisers

Previous events

DataLab 6. Using generative AI for irreductionist visualization in science

Datlab poster
Time and place: 22 May 14.00-16.00, Universitetsklubben conference room.

Chaired by: Mathieu Jacomy from Aalborg University

In this seminar, we will explore using AI and algorithms in science through case studies and practical experiments. The seminar will take the form of an interactive discussion where we will draw tools at some point. Bring your laptop!
Mathieu will start by showcasing a mapping of AI and algorithms in science where an embedding model, network analysis and visualization techniques, prompt engineering and a large language model was used to produce a map of 2M articles. Generative AI has been used to summarize clusters of articles and produce about 8K annotations that make the map readable and relatable. The resulting landscape can be used as a boilerplate for the collaborative exploration of the controversiality of algorithms and AI in science. We could call this kind of visualization "irreductionist," following Latour's word, because it intentionally refrains from aggregating data beyond the point of oversimplification. Network visualization, dimensionality reduction (T-SNE, UMAP), and of course cartography, allow us to live with the trouble of empiricism: real world data is not only uncertain, but often ambiguous, equivocal, and/or polyvalent. Datascapes are often hard to understand by themselves and expensive to annotate, but generative AI is making a decisive change to that economy.

Our experiments show that generative AI can be acceptably good at summarizing large sets of documents, but at certain conditions. What does it mean to summarize documents? How to test and validate the results? How to approach iterating over the prompt design? Can we identify the factors that ensure good-enough results? Why would a LLM succeed at that task while it is bad at so many other things? What infrastructure to use for such computations? We will discuss those questions and explore the conditions necessary to make generative AI a worthy ally in building new methods, techniques and tools for the computational social science and humanities.

DataLab 6. Vocabularies for Thinking with Data

Time and place: 6 March 2024, 13:15 – 15:00, Universitetsklubben conference room.

 

Datalab poster
Chaired by: Julia Velkova and Ericka Johnson

During this DataLab session we present a book, eat semlor and talk about the vocabularies that we use, not use or need to describe issues brought by digitalisation and datafication. We ponder upon how do the vocabularies that we use matter, when and why. What new words, terms and fields do we need? Industries generate a buzz word a day – just think of "smart", "AI", "cloud", "digital twin”. Scholars are following by generating subfields and their own buzz words for studying digital matters – think of critical infrastructure/app/platform/algorithm/data/software/... studies. What are your buzz words, vocabularies and favourite terms? Why and when did we start calling software an app, a storage closet a "cloud", an algorithm “a robot”? What are the terms that you use and why?

We kick-off the conversation with the notion of the backend, and a brief presentation of the newly published book Media Backends: Digital Infrastructures and Sociotechnical Relations (Edited by Lisa Parks, Julia Velkova and Sander De Ridder). Everyone is welcome!

 

DataLab 5. Synthetic Data in Smart Cities/Digital Twins

Time and place: 29 November 2023, 9.00–12.00, TEM21.

DataLab 5 poster
What is synthetic data and how does it matter? At this workshop, we will discuss the risks, possibilities and promises of synthetic data across different application areas. Given the increasingly complicated regulatory environment around data use and AI systems, what kinds of risks are addressed, created or made possible through synthetic data? Where there is much excitement about synthetic data in the machine learning community, there is also apprehension and caution. There is a proliferation of synthetic data generation libraries and pipelines becoming available to the technical community. These promise to get beyond the triple challenges of privacy, bias, and data scarcity, but warrant a critical discussion about how and to what extent these challenges are being addressed. We will discuss what the state of the art in synthetic data currently is, and what critical, legal, and ethical issues synthetic data techniques may encounter.

DataLab 4. Data and Ethics Workshop

Time and place: 20 October, Digimaker (Studenthuset), 9:30 – 14:00 including lunch

DataLab 4 poster
We are kicking-off the fall term sessions of TEMAs DATA LAB with a workshop on Data & Ethics to take place on 20 October 9:30 – 14:00 on campus (DigiMaker at Studenthuset). During the workshop we will test, explore and discuss the Data Ethics Decision Aid framework developed by scholars at the Data School at Utrecht University. The framework is described as an aid “for reviewing government data projects that considers their social impact, the embedded values and the government’s responsibilities in times of data-driven public management”, and “a useful process for ethical evaluation of data projects for public management and an effective tool for creating awareness of ethical issues in data practices.” (read more about it here: https://link.springer.com/article/10.1007/s10676-020-09577-5)

We invite you to join the workshop either in the role of a tester, bringing a case to test the tool on; or in the role of discussant-participant. There are no strict requirements to be a tester, it is enough to have a project/case that involves handling data and ethics that you are willing to try the tool on during the workshop. Testers could also be organisations that you are working with and who have to deal with data and ethics. It is also perfectly fine to join as a participant/discussant if you are interested but do not have a specific project going on.
  

DataLab 3. Scholarly research in plaintext: using the zettlekasten method, markdown, and pandoc to organize a sustainable scholarly workflow 

Time and place: 17 May 2023, 0:30-12:00, in Forum

DataLab 3 poster
The workshop will be led by our colleague Charles Berret (post-doc at TEMA-G/Media and Information Technologies) and the topic is “Scholarly Research in Plaintext: Using the Zettelkasten Method, Markdown, and Pandoc to Organize a Sustainable Scholarly Workflow”.

Abstract: Every researcher needs a system to organize their work, but many tools and platforms end up working against us. The purpose of this workshop is to examine how the tools we use impact how we conduct scholarly research, especially when those tools are a source of friction with the mental models that best match our projects, practices, and materials. Focusing specifically on text-based research practices, we will explore the Zettelkastenmethod as a platform-independent, open-source workflow developed in the Digital Humanities to support scholars in gathering, organizing, and developing ideas from notes, to drafts, to manuscripts.

 

DataLab2. Beyond academic publics: collaborating with cultural institutions in research and communication

Time and place: 15 March 2023, 9:30 - 12:00 with coffee and lunch, DigiMaker at Studenthuset, floor 5

DataLab 2 poster
Chaired by Anne Kaun, Södertörn University, Julia Velkova and Maria Eidenskog, TEMA-T. How to engage cultural institutions in our research and our communication about it? This workshop gathers researchers who have actively engaged with cultural institutions to co-produce and /or disseminate knowledge. We share different experiences and jointly explore possibilities, challenges and future avenues ahead. Join the session if you are interested, regardless of your previous experience in collaborating with publics beyond academia. We aim to create a space for open and creative thinking that inspires ongoing and future projects and collaborations.

With contributions by Maria Arnelid, TEMA G, Amanda Lagerkvist, Uppsala University, Dominika Lisy, TEMA G, Marko Marila, TEMA T, Anna Storm, TEMA T, Jenny Sjöholm, TEMA T

DataLab 1. Engaging with apps: methods and questions with Darcy Parks & Julia Velkova

Time and place: 25 January 2023, 9:30 - 12:00 with coffee, Lethe

 

DataLab 1 poster
What do apps do? How do we analyze relations mediated by apps? What methods exist out there, and what methods can we use to approach a social practice via apps? Come to the first session of the Data Lab to explore apps through a hands-on workshop and a discussion about ways of knowing and engaging with apps. Everyone is welcome! Bring your laptop!