The title is: DataLab 12: The ”Rawness” of the Data: a special session in collaboration with the Tenth Swedish Language Technology Conference.
About the seminar
This is a special session of the DataLab in collaboration with the Tenth Swedish Language Technology Conference (https://sltc2024.github.io/) that aims to provoke discussion and reflection around the notion of “raw” data. Bowker’s 2008 maxim that “raw data is both an oxymoron and a bad idea” has been enthusiastically taken up and discussed within Critical Data Studies and surrounding fields. However, this challenge to the “rawness” of data doesn’t always map well onto other disciplines, where “raw” data are essential to supporting claims to transparency or reproducibility.
To kick-start our discussion, participants will be provided in advance with copies of a book chapter about “The Rawness of Data” from the recently published volume Behind the Science: The invisible work of data management in Big Science (Harrison 2024) which examines how experimental data will be produced and managed at the European Spallation Source, and the now well-known article “Data Sheets for Datasets” (Gebru et al. 2018), which advocates for better and more transparent documentation about how datasets are produced.
With these resources in hand, we’ll be asking: What do you think of as your “raw” data? When is the moment of “data birth” (Leonelli & Tempini 2020) in your research and what happens after that? What disciplinary conventions are there that determine appropriate processing of your data, and when are your data considered to be “cooked”? How are concerns about raw data, transparency and reproducibility connected in your research field?
Note, we begin at 9:30 with a fika and mingle, and start the session at 10 sharp.
Registration
Registration deadline: 20 November
Register by filling out this form: https://forms.office.com/e/Mzsu04ZRJP
