000 | 03259nam a2200457 i 4500 | ||
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001 | 8709328 | ||
003 | IEEE | ||
005 | 20220712204939.0 | ||
006 | m o d | ||
007 | cr |n||||||||| | ||
008 | 190614s2019 mau ob 001 eng d | ||
020 |
_a9780262352215 _qelectronic bk. |
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020 |
_z0262352214 _qelectronic bk. |
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020 |
_z9780262039666 _qprint |
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035 | _a(CaBNVSL)mat08709328 | ||
035 | _a(IDAMS)0b000064892e0e12 | ||
040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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050 | 4 |
_aZA4065 _b.L68 2019eb |
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082 | 0 | 4 |
_a025.042 _223 |
100 | 1 |
_aLoukissas, Yanni A. _q(Yanni Alexander), _eauthor. _925673 |
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245 | 1 | 0 |
_aAll data are local : _bthinking critically in a data-driven society / _cYanni Alexander Loukissas ; foreword by Geoffrey C. Bowker. |
264 | 1 |
_aCambridge : _bThe MIT Press, _c2019. |
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264 | 2 |
_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2019] |
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300 | _a1 PDF (272 pages). | ||
336 |
_atext _2rdacontent |
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337 |
_aelectronic _2isbdmedia |
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338 |
_aonline resource _2rdacarrier |
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506 | _aRestricted to subscribers or individual electronic text purchasers. | ||
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. | ||
530 | _aAlso available in print. | ||
538 | _aMode of access: World Wide Web | ||
588 | 0 | _aPrint version record. | |
650 | 0 |
_aElectronic information resource literacy. _925674 |
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650 | 0 |
_aMedia literacy. _925675 |
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655 | 4 |
_aElectronic books. _93294 |
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710 | 2 |
_aIEEE Xplore (Online Service), _edistributor. _925676 |
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710 | 2 |
_aMIT Press, _epublisher. _925677 |
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776 | 0 | 8 |
_iPrint version: _aLoukissas, Yanni A. (Yanni Alexander), author. _tAll data are local _z9780262039666 _w(DLC) 2018030570 _w(OCoLC)1054264218 |
856 | 4 | 2 |
_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=8709328 |
942 | _cEBK | ||
999 |
_c73599 _d73599 |