001385869 000__ 03131cam\a2200445Ki\4500
001385869 001__ 1385869
001385869 003__ MaCbMITP
001385869 005__ 20240325105013.0
001385869 006__ m\\\\\o\\d\\\\\\\\
001385869 007__ cr\cn\nnnunnun
001385869 008__ 190117s2019\\\\mau\\\\\o\\\\\000\0\eng\d
001385869 020__ $$a9780262352215$$q(electronic bk.)
001385869 020__ $$a0262352214$$q(electronic bk.)
001385869 020__ $$z9780262039666$$q(print)
001385869 035__ $$a(OCoLC)1082521438
001385869 035__ $$a(OCoLC-P)1082521438
001385869 040__ $$aOCoLC-P$$beng$$erda$$epn$$cOCoLC-P
001385869 050_4 $$aZA4065$$b.L68 2019eb
001385869 072_7 $$aCOM$$x079000$$2bisacsh
001385869 072_7 $$aTEC$$x052000$$2bisacsh
001385869 08204 $$a025.042$$223
001385869 1001_ $$aLoukissas, Yanni A.$$q(Yanni Alexander),$$eauthor.
001385869 24510 $$aAll data are local :$$bthinking critically in a data-driven society /$$cYanni Alexander Loukissas ; foreword by Geoffrey C. Bowker.
001385869 264_1 $$aCambridge :$$bThe MIT Press,$$c2019.
001385869 300__ $$a1 online resource (272 pages).
001385869 336__ $$atext$$btxt$$2rdacontent
001385869 337__ $$acomputer$$bc$$2rdamedia
001385869 338__ $$aonline resource$$bcr$$2rdacarrier
001385869 506__ $$aAccess limited to authorized users.
001385869 520__ $$aHow to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local , we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. All data are local. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States--Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow--Loukissas shows us how to analyze data settings rather than data sets. Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the "myth of digital universalism," Loukissas reminds us of the meaning-making power of the local.
001385869 588__ $$aOCLC-licensed vendor bibliographic record.
001385869 650_0 $$aElectronic information resource literacy.
001385869 650_0 $$aMedia literacy.
001385869 655_0 $$aElectronic books
001385869 852__ $$bebk
001385869 85640 $$3MIT Press$$uhttps://univsouthin.idm.oclc.org/login?url=https://doi.org/10.7551/mitpress/11543.001.0001?locatt=mode:legacy$$zOnline Access through The MIT Press Direct
001385869 85642 $$3OCLC metadata license agreement$$uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
001385869 909CO $$ooai:library.usi.edu:1385869$$pGLOBAL_SET
001385869 980__ $$aBIB
001385869 980__ $$aEBOOK
001385869 982__ $$aEbook
001385869 983__ $$aOnline