CREDAL: Close Reading of Data Models
Data models are foundational to the creation of data and any data-driven system. Every algorithm, ML model, statistical model, and database depends on a data model to function. As such, data models are rich sites for examining the material, social, and political conditions shaping technical systems. Inspired by literary criticism, we propose close readings of data models—treating them as artifacts to be analyzed like texts. This practice highlights the materiality, genealogy, techne, closure, and design of data systems.
Authors
- Julia Stoyanovich (ORCID: https://orcid.org/0000-0002-1587-0450)
- Olha Nahurna
- Matvii Prytula
Institutions
- Ukrainian Catholic University (UA)
- New York University (US)
- Eindhoven University of Technology (NL)
Publication Details
- Published
- 2025-06-22
- DOI
- https://doi.org/10.1145/3736733.3736737
- Primary Topic
- Semantic Web and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- Simons Foundation
- Simons Foundation Autism Research Initiative
- York University