


Styling and infrastructure for this page inspired by related syllabi produced by Ben Baumer and R. Jordan Crouser.
All readings for this course will be available in our course Perusall, which is linked in Moodle. I encourage you to complete the readings there so that you can leave comments and questions as they come up.



Fill out the First Day of Class Questionnaire
Course slides are here.
Elish, M. C. and danah boyd (2018). “Situating Methods in the Magic of Big Data and AI”. In: Communication Monographs 85.1, pp. 57-80. (Visited on Sep. 01, 2023). Read in Perusall
Complete Syllabus Quiz
Fill out the First Day of Class Questionnaire
Fill out the Trigger Warnings Questionnaire in Moodle.
Sign-up to take class notes for community labor
Course slides are here
boyd, danah and Kate Crawford (2012). “Critical Questions for Big Data”. In: Information, Communication & Society 15.5, pp. 662-679. (Visited on Jan. 19, 2018).
Kitchin, Rob (2014). “Big Data, new epistemologies and paradigm shifts”. En. In: Big Data & Society 1.1, p. 2053951714528481. (Visited on Jul. 16, 2019).
Leonelli, S. (2014). “What difference does quantity make? On the epistemology of Big Data in biology:”. En. In: Big Data & Society. Publisher: SAGE PublicationsSage UK: London, England. (Visited on Mar. 28, 2020).
Onuoha, Mimi (2016). The Point of Collection. En. (Visited on Aug. 20, 2021).
Levy Karen, Tim Hwang (2015). ‘The Cloud’ and Other Dangerous Metaphors. En. Section: Technology. (Visited on Aug. 29, 2021). Read in Perusall
Puschmann, Cornelius and Jean Burgess (2014). “Metaphors of Big Data”. En. In: International Journal of Communication 8.0, p. 20. (Visited on May. 02, 2016). Read in Perusall
Course slides are here
Watson, Sarah M. (2021). Metaphors of Big Data. (Visited on Aug. 30, 2021).
Fiore-Silfvast, Brittany (2014). Hacked Ethnographic Fieldnotes. En. (Visited on Feb. 18, 2021). Read in Perusall
Burrell, Jenna (2012). The Ethnographer’s Complete Guide to Big Data: Small Data People in a Big Data World. (Visited on Aug. 20, 2021). Read in Perusall
Fill out CATME Survey (link sent to your email)
DM Professor if you’d like to lead a class discussion
Start working on Fieldnote 1
Introduction , Biruk, Cal (2018). Cooking Data: Culture and Politics in an African Research World. Illustrated edition. Durham: Duke University Press Books. ISBN: 978-0-8223-7074-1. Read in Perusall
Start working on Team Contract
Continue working on Fieldnote 1
Course slides are here
Denton, Emily, Alex Hanna, Razvan Amironesei, et al. (2021). “On the Genealogy of Machine Learning Datasets: A Critical History of ImageNet”. In: Big Data & Society 8.2, p. 20539517211035955. (Visited on Jan. 05, 2022). Read in Perusall
Continue working on Fieldnote 1
Course slides are here
Gebru, Timnit, Jamie Morgenstern, Briana Vecchione, et al. (2020). “Datasheets for Datasets”. In: arXiv:1803.09010 [cs]. arXiv: 1803.09010. (Visited on Jan. 24, 2021).
Bender, Emily M. and Batya Friedman (2018). “Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science”. In: Transactions of the Association for Computational Linguistics 6, pp. 587-604. (Visited on Aug. 20, 2021).
Star, Susan Leigh (1999). “The Ethnography of Infrastructure”. En. In: American Behavioral Scientist 43.3, pp. 377-391. (Visited on Feb. 18, 2016). Read in Perusall
Fieldnote 1 Due
Course slides are here
Lampland, Martha and Susan Leigh Star, ed. (2008). Standards and Their Stories: How Quantifying, Classifying, and Formalizing Practices Shape Everyday Life. 1 edition. Ithaca: Cornell University Press. ISBN: 978-0-8014-7461-3.
Ottinger, Gwen (2010). “Buckets of Resistance: Standards and the Effectiveness of Citizen Science”. En. In: Science, Technology, & Human Values 35.2, pp. 244-270. (Visited on Oct. 05, 2019).
Timmermans, Stefan and Steven Epstein (2010). “A World of Standards but not a Standard World: Toward a Sociology of Standards and Standardization*“. In: Annual Review of Sociology 36.1, pp. 69-89. (Visited on Oct. 16, 2014).
Bowker, Geoffrey C. (1998). “The Kindness of Strangers: Kinds and Politics in Classification Systems”. En. In: Library Trends 47.2, pp. 255-292. (Visited on Oct. 14, 2019). Read in Perusall
Get approval for dataset
Team Contract Due
Work on semiotic analysis
Continue working on Fieldnote 2
Watch Video introducing Mini-Project 1 in Perusall
Start working on Mini-Project 1
Be sure to get approval for the TED Talks you plan to view for Mini-Project 1.
Course slides are here
ICD-11
Infrastructural Analysis Worksheet
Bowker, Geoffrey C. and Susan Leigh Star (1999). Sorting Things Out: Classification and Its Consequences. En. Cambridge, MA: MIT Press. ISBN: 978-0-262-52295-3.
Waterton, Claire (2002). “From Field to Fantasy: Classifying Nature, Constructing Europe”. En. In: Social Studies of Science 32.2, pp. 177-204. (Visited on May. 15, 2019).
Kirksey, Eben (2015). “Species: a praxiographic study”. Fr. In: Journal of the Royal Anthropological Institute 21.4, pp. 758-780. (Visited on Oct. 05, 2019).
Work on semiotic analysis
Continue working on Fieldnote 2
Continue working on Mini-Project 1
Chapter 1 , Gray, Mary L. and Siddharth Suri (2019). Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Illustrated edition. Boston: Mariner Books. ISBN: 978-1-328-56624-9. Read in Perusall
Work on peopling the data
Continue working on Fieldnote 2
Continue working on Mini-Project 1
Course slides are here
Irani, Lilly (2015). Justice for “Data Janitors”. En-US. (Visited on Dec. 13, 2018).
Plantin, Jean-Christophe (2019). “Data Cleaners for Pristine Datasets: Visibility and Invisibility of Data Processors in Social Science”. En. In: Science, Technology, & Human Values 44.1. Publisher: SAGE Publications Inc, pp. 52-73. (Visited on Aug. 20, 2021).
Forsythe, Diana E. (1993). “The Construction of Work in Artificial Intelligence”. En. In: Science, Technology, & Human Values 18.4. Publisher: SAGE Publications Inc, pp. 460-479. (Visited on Aug. 20, 2021).
Tanweer, Anissa and James Steinhoff (2023). “Academic Data Science: Transdisciplinary and Extradisciplinary Visions”. In: Social Studies of Science, p. 03063127231184443. (Visited on Jan. 02, 2024). Read in Perusall
Work on peopling the data
Fieldnote 2 Due
Continue working on Mini-Project 1
Course slides are here
Gieryn, Thomas F. (1999). Cultural Boundaries of Science: Credibility on the Line. En. University of Chicago Press. ISBN: 978-0-226-29261-8.
Garnett, Emma (2016). “Developing a feeling for error: Practices of monitoring and modelling air pollution data”. En. In: Big Data & Society 3.2, p. 2053951716658061. (Visited on Sep. 24, 2019). Read in Perusall
Work on ritual analysis
Group evaluations open
Watch Mini-Project 2 Help Video on Perusall
Start working on Mini-Project 2
Continue working on Fieldnote3
MP 1 Peer Review Submission open
Course slides are here
Lorimer, Jamie (2008). “Counting Corncrakes: The Affective Science of the UK Corncrake Census”. En. In: Social Studies of Science 38.3, pp. 377-405. (Visited on May. 16, 2019).
Ribes, David and Steven J Jackson (2013). “Data bite man: The work of sustaining a long-term study”. In: Raw data” is an oxymoron. Ed. by Lisa Gitelman. Cambridge, MA: MIT Press, pp. 147-166. Read in Perusall
Work on ritual analysis
Fieldnote 3 Due
MP 1 Peer Review Submission close and assessment opens
Continue working on Mini-Project 2
Course slides are here
Bowker, Geoffrey C. (2000). “Biodiversity Datadiversity”. En. In: Social Studies of Science 30.5, pp. 643-683. (Visited on May. 14, 2014).
Walford, Antonia (2017). “Raw Data: Making Relations Matter”. En_US. In: Social Analysis 61.2. Publisher: Berghahn Journals Section: Social Analysis, pp. 65-80. (Visited on Aug. 20, 2021).
Pink, Sarah, Shanti Sumartojo, Deborah Lupton, et al. (2017). “Mundane data: The routines, contingencies and accomplishments of digital living”. En. In: Big Data & Society 4.1. Publisher: SAGE Publications Ltd, p. 2053951717700924. (Visited on Aug. 30, 2021).
Group Evaluations Due
Work on user guide
Continue working on Mini-Project 2
Start working on Fieldnote 4
Continue working on Peer Review
Work on institutional analysis
Continue working on Fieldnote 4
Continue working on Mini-Project 2
MP 1 Peer Review Due
Work on institutional analysis
Continue working on Fieldnote 4
Continue working on Mini-Project 2
Chapter 3 , Biruk, Cal (2018). Cooking Data: Culture and Politics in an African Research World. Illustrated edition. Durham: Duke University Press Books. ISBN: 978-0-8223-7074-1. Read in Perusall
Work on discourse analysis
Fieldnote 4 Due
Mini-Project 2 Due
MP 2 Peer Review Submission Opens
Course slides are here
Institutions Worksheet
Gerlitz, Carolin and Anne Helmond (2013). “The like economy: Social buttons and the data-intensive web”. En. In: New Media & Society 15.8. Publisher: SAGE Publications, pp. 1348-1365. (Visited on Aug. 30, 2021).
Beer, David (2015). “Productive measures: Culture and measurement in the context of everyday neoliberalism”. En. In: Big Data & Society 2.1. Publisher: SAGE Publications Ltd, p. 2053951715578951. (Visited on Aug. 29, 2021).
Ottinger, Gwen and Rachel Zurer (2011). New Voices, New Approaches: Drowning in Data. En-US. (Visited on Dec. 13, 2018). Read in Perusall
Work on discourse analysis
MP 1 Peer Review Submission close and assessment opens
Start working on Mini-Project Revisions
Course slides are here.
Pine, Kathleen H. and Max Liboiron (2015). “The Politics of Measurement and Action”. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery, pp. 3147-3156. ISBN: 978-1-4503-3145-6. (Visited on Aug. 30, 2021).
Continue working on Peer Review
Continue working on Mini-Project Revisions
Poirier, Lindsay “Enacting Data Context: Fixing Meaning in Transparency Data Initiatives”. In: Big Data and Society. Read in Perusall
First Draft Due
Start working on Fieldnote 5
Continue working on Mini-Project Revisions
MP 2 Peer Review Submission Due
Course slides are here.
Dourish, Paul and Edgar Gómez Cruz (2018). “Datafication and data fiction: Narrating data and narrating with data”. En. In: Big Data & Society 5.2. Publisher: SAGE Publications Ltd, p. 2053951718784083. (Visited on Apr. 05, 2021).
Liboiron, Max (2015). “Disaster Data, Data Activism : Grassroots Responses to Representing Superstorm Sandy”. En. In: Extreme Weather and Global Media. Ed. by Julia Leyda and Diane Negra. Taylor & Francis Group. (Visited on Aug. 27, 2019). Read in Perusall
Kim, Youngrim, Megan Finn, Amelia Acker, et al. (2024). “Epistemologies of Missing Data: COVID Dashboard Builders and the Production and Maintenance of Marginalized COVID Data”. In: Big Data & Society 11.2, p. 20539517241259666. (Visited on Jun. 25, 2024). Read in Perusall
Work on user guide revisions
Continue working on Fieldnote 5
Continue working on Mini-Project Revisions
Course slides are here
Bruno, Isabelle, Emmanuel Didier, and Tommaso Vitale (2014). Statactivism: Forms of Action between Disclosure and Affirmation. En. SSRN Scholarly Paper ID 2466882. Rochester, NY: Social Science Research Network. (Visited on Dec. 18, 2018).
Milan, Stefania and Lonneke van der Velden (2016). “The Alternative Epistemologies of Data Activism”. In: Digital Culture & Society 2.2, pp. 57-74. (Visited on Jul. 16, 2019).
Currie, Morgan, Britt S Paris, Irene Pasquetto, et al. (2016). “The conundrum of police officer-involved homicides: Counter-data in Los Angeles County”. En. In: Big Data & Society 3.2, p. 2053951716663566. (Visited on Aug. 08, 2018).
mimimimimi (2021). On Missing Data Sets. original-date: 2016-02-03T16:30:28Z. (Visited on Aug. 20, 2021).
Milan, Stefania and Emiliano Treré (2020). “The Rise of the Data Poor: The COVID-19 Pandemic Seen From the Margins”. En. In: Social Media + Society 6.3. Publisher: SAGE Publications Ltd, p. 2056305120948233. (Visited on Aug. 31, 2021).
D’Ignazio, Catherine and Lauren F. Klein (2020). Data Feminism. Cambridge, Massachusetts: The MIT Press. ISBN: 978-0-262-04400-4.
Work on user guide revisions
Continue working on Fieldnote 5
Continue working on Mini-Project Revisions
Final Project Due
Fieldnote 5 Due
Community Labor Due
MP Revisions Due