Uncertain Archives: Critical Keywords for Big Data

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Standard

Uncertain Archives : Critical Keywords for Big Data. / Thylstrup, Nanna ; Agostinho, Daniela; D'Ignazio, Catherine; Ring, Annie; Veel, Kristin.

Uncertain Archives: Critical Keywords for Big Data . ed. / Nanna Bonde Thylstrup; Daniela Agostinho; Annie Ring; Catherine D'Ignazio; Kristin Veel. MIT Press, 2021. p. 1-27.

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Harvard

Thylstrup, N, Agostinho, D, D'Ignazio, C, Ring, A & Veel, K 2021, Uncertain Archives: Critical Keywords for Big Data. in NB Thylstrup, D Agostinho, A Ring, C D'Ignazio & K Veel (eds), Uncertain Archives: Critical Keywords for Big Data . MIT Press, pp. 1-27.

APA

Thylstrup, N., Agostinho, D., D'Ignazio, C., Ring, A., & Veel, K. (2021). Uncertain Archives: Critical Keywords for Big Data. In N. B. Thylstrup, D. Agostinho, A. Ring, C. D'Ignazio, & K. Veel (Eds.), Uncertain Archives: Critical Keywords for Big Data (pp. 1-27). MIT Press.

Vancouver

Thylstrup N, Agostinho D, D'Ignazio C, Ring A, Veel K. Uncertain Archives: Critical Keywords for Big Data. In Thylstrup NB, Agostinho D, Ring A, D'Ignazio C, Veel K, editors, Uncertain Archives: Critical Keywords for Big Data . MIT Press. 2021. p. 1-27

Author

Thylstrup, Nanna ; Agostinho, Daniela ; D'Ignazio, Catherine ; Ring, Annie ; Veel, Kristin. / Uncertain Archives : Critical Keywords for Big Data. Uncertain Archives: Critical Keywords for Big Data . editor / Nanna Bonde Thylstrup ; Daniela Agostinho ; Annie Ring ; Catherine D'Ignazio ; Kristin Veel. MIT Press, 2021. pp. 1-27

Bibtex

@inbook{535bebf5ee2d4e53a55353196d68d7c3,
title = "Uncertain Archives: Critical Keywords for Big Data",
abstract = "This groundbreaking work offers an interdisciplinary perspective on big data and the archives they accrue, interrogating key terms. Scholars from a range of disciplines analyze concepts relevant to critical studies of big data, arranged glossary style—from abuse and aggregate to visualization and vulnerability. They not only challenge conventional usage of such familiar terms as prediction and objectivity but also introduce such unfamiliar ones as overfitting and copynorm. The contributors include a broad range of leading and agenda-setting scholars, including as N. Katherine Hayles, Wendy Hui Kyong Chun, Johanna Drucker, Lisa Gitelman, Safiya Noble, Sarah T. Roberts and Nicole Starosielski.Uncertainty is inherent to archival practices; the archive as a site of knowledge is fraught with unknowns, errors, and vulnerabilities that are present, and perhaps even amplified, in big data regimes. Bringing lessons from the study of the archive to bear on big data, the contributors consider the broader implications of big data's large-scale determination of knowledge.",
author = "Nanna Thylstrup and Daniela Agostinho and Catherine D'Ignazio and Annie Ring and Kristin Veel",
year = "2021",
language = "English",
isbn = "9780262539883",
pages = "1--27",
editor = "Thylstrup, {Nanna Bonde} and Daniela Agostinho and Annie Ring and Catherine D'Ignazio and Kristin Veel",
booktitle = "Uncertain Archives",
publisher = "MIT Press",
address = "United States",

}

RIS

TY - CHAP

T1 - Uncertain Archives

T2 - Critical Keywords for Big Data

AU - Thylstrup, Nanna

AU - Agostinho, Daniela

AU - D'Ignazio, Catherine

AU - Ring, Annie

AU - Veel, Kristin

PY - 2021

Y1 - 2021

N2 - This groundbreaking work offers an interdisciplinary perspective on big data and the archives they accrue, interrogating key terms. Scholars from a range of disciplines analyze concepts relevant to critical studies of big data, arranged glossary style—from abuse and aggregate to visualization and vulnerability. They not only challenge conventional usage of such familiar terms as prediction and objectivity but also introduce such unfamiliar ones as overfitting and copynorm. The contributors include a broad range of leading and agenda-setting scholars, including as N. Katherine Hayles, Wendy Hui Kyong Chun, Johanna Drucker, Lisa Gitelman, Safiya Noble, Sarah T. Roberts and Nicole Starosielski.Uncertainty is inherent to archival practices; the archive as a site of knowledge is fraught with unknowns, errors, and vulnerabilities that are present, and perhaps even amplified, in big data regimes. Bringing lessons from the study of the archive to bear on big data, the contributors consider the broader implications of big data's large-scale determination of knowledge.

AB - This groundbreaking work offers an interdisciplinary perspective on big data and the archives they accrue, interrogating key terms. Scholars from a range of disciplines analyze concepts relevant to critical studies of big data, arranged glossary style—from abuse and aggregate to visualization and vulnerability. They not only challenge conventional usage of such familiar terms as prediction and objectivity but also introduce such unfamiliar ones as overfitting and copynorm. The contributors include a broad range of leading and agenda-setting scholars, including as N. Katherine Hayles, Wendy Hui Kyong Chun, Johanna Drucker, Lisa Gitelman, Safiya Noble, Sarah T. Roberts and Nicole Starosielski.Uncertainty is inherent to archival practices; the archive as a site of knowledge is fraught with unknowns, errors, and vulnerabilities that are present, and perhaps even amplified, in big data regimes. Bringing lessons from the study of the archive to bear on big data, the contributors consider the broader implications of big data's large-scale determination of knowledge.

UR - https://mitpress.mit.edu/books/uncertain-archives

M3 - Book chapter

SN - 9780262539883

SP - 1

EP - 27

BT - Uncertain Archives

A2 - Thylstrup, Nanna Bonde

A2 - Agostinho, Daniela

A2 - Ring, Annie

A2 - D'Ignazio, Catherine

A2 - Veel, Kristin

PB - MIT Press

ER -

ID: 300919623