Data shadows refer to the information that a person leaves behind unintentionally while taking part in daily activities such as checking their e-mails, scrolling through social media or even by using their debit or credit card.[1][2][3]
The term data shadow was coined in 1972 by Kerstin Anér, a member of the Swedish legislature.[4]
The generated information has the potential to create a vastly detailed record of an individual's daily trails, which includes the individual's thoughts and interests, whom they communicate with, information about the organizations with which they work or interact with and so forth.[2] This information can be dispersed to a dozen organizations and servers depending on their use.[5] Along with Individuals, the activities of institutions and organizations are also tracked. Data Shadows are closely linked with data footprints, which are defined as the data that has been left behind by the individual themselves through various activities such as online activities, communication information, and transactions.[2] In a chapter for the book Geography and Technology, researcher Matthew Zook and his co-authors note that data shadows have come as a result of people becoming "digital individuals" and that these shadows are continually evolving and changing.[6] They are used to model and predict political opinions, and make inferences about a person's political values or susceptibility to advertising.[1]
The data or digital footprints are obtained from monitoring and tracking individuals’ digital activities. Digital footprints provide a drive for companies such as Facebook and Google to invest in obtaining data generated from these footprints, in order to be sold to marketers.[7] As illustrated by Bodle, users are willing to give up their information to companies they trust.[8] Although collecting individuals’ data raises several ethical concerns, it can be valuable for the healthcare data analytics and new health services.[9] For instance, access to such data can help healthcare services shed light on the causes of disease, the effects or side-effects the treatments might have and can facilitate a tailored analysis according to the individual's characteristics.[10]
Dataveillance gives rise to data shadows since it allows for the identification, classification and representation of individuals or organizations.[11] Dataveillance is defined as a mode of surveillance which tracks, monitors or regulates an individual using digital activity including their personal details and social media activities.[5] In 2013, Edward Snowden’s revelations on the National Security Agency's PRISM program, that the organization would “receive” emails, video clips, photos, voice and video calls, social networking details, logins and other data held by a range of US internet firms”.[12] It is also revealed that corporate social networks share their information with the intelligence agencies.[13] Platform owners such as Google and Facebook, anchor the trust of their users and reassure them that their information is protected through portrayal of corporate codes of conduct such as “Do no evil” and “Making the world transparent and connected” [13] However, as pointed out by Bodle, platform owners are themselves collecting the user's information and using it for purposes they deem to be necessary.[8]
Privacyedit
Europe has brought about a long-awaited revision to their data protection framework called the Data Protection Directive.[14] According to this, European Union countries are forced to remove personal data of individuals upon their request if the information is obsolete or irrelevant.[15]Information privacy is defined as the right that individuals have over the data about themselves when subjected to a third party,[2] and that the data should not be available to any organization or person without their approval.[2] However, this is not the case when data is collected and collated for marketers: online marketers use cookies, spyware, adware and so on to capture rich data about their customers.[16] State agencies also collect citizen data for security purposes.[2] The aftermath of the 9/11 terrorist attacks has allowed US national security agencies to increase their collation and exchange of information in order to strengthen the United States Intelligence Community (USIC) and to minimize potential threats.[17]
Referencesedit
^ abHoward, Philip N. (2005). New Media Campaigns and the Managed Citizen. New York, NY: Cambridge University Press. pp. 93, 144. ISBN9780521612272.
^ abcdefKitchin, Rob (2014). The data revolution: big data, open data, data infrastructures & their consequences. Sage Publications Ltd. pp. xvii, 222 pages.
^Koops, E.J (2011). "Forgetting footprints, shunning shadows: A critical analysis of the 'right to be forgotten' in big data practice". SCRIPTed. 8 (3): 229–256. SSRN 1986719.
^Steven Bellovin (2021-06-29). ""Where Did "Data Shadow" Come From?"". CircleID.
^ abRaley, Rita (2013). "Data and countervailence". Raw Data Is an Oxymoron. MIT Press. pp. 121–146. ISBN9780262518284.
^Zook, Matthew; Dodge, Martin; Aoyama, Yuko; Townsend, Anthony (2004-03-31). "New Digital Geographies: Information, Communication, and Place". Geography and Technology. Springer Science & Business Media. p. 169. ISBN9781402018718.
^ abGerman; Kathleen, M; Drushel, Bruce (2011). The ethics of emerging media: information, social norms, and new media technology. Continuum. p. 279.
^Harjumaa, Marja; Saraniemi, Saila; Pekkarinen, Saara; Lappi, Minna; Similä, Heidi; Isomursu; Minna (2017-12-05). "Feasibility of digital footprint data for health analytics and services: an explorative pilot study". BMC Medical Informatics and Decision Making. 16 (1): 139. doi:10.1186/s12911-016-0378-0. PMC5112682. PMID 27829413.
^Kostkova, Patty; Brewer, Helen; de Lusignan, Simon; Fottrell, Edward; Goldacre, Ben; Hart, Graham; Koczan, Phil; Knight, Peter; Marsolier, Corinne (2016). "Who Owns the Data? Open Data for Healthcare". Frontiers in Public Health. 4: 7. doi:10.3389/fpubh.2016.00007. ISSN 2296-2565. PMC4756607. PMID 26925395.
^Selwyn, Neil (2017-12-05). "Data entry: towards the critical study of digital data and education". Learning, Media and Technology. 40 (1): 64–82. doi:10.1080/17439884.2014.921628. S2CID 143752752.
^Kelion, Leo (2013-06-25). "Q&A: Prism internet surveillance". BBC News. Retrieved 2017-11-25.
^ abvan Dijck, José (2014). "Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology". Surveillance & Society. 12 (2). ISSN 1477-7487.
^Gutwirth, Serge (2013). European data protection: coming of age (1. Aufl., 2013, 1 ed.). Springer. p. 437. Retrieved 25 November 2017.
^Walker, R. K. (2012). "The Right to be Forgotten". Hastings Law Journal. 64: 257–261.
^Ashworth, Laurence; Free, Clinton (August 26, 2006). "Marketing Dataveillance and Digital Privacy: Using Theories of Justice to Understand Consumers' Online Privacy Concerns". Journal of Business Ethics. 67 (2): 107–123. doi:10.1007/s10551-006-9007-7. ISSN 0167-4544. S2CID 143800212.
^Mace, Robyn R (2009). Intelligence, Dataveillance, and Information Privacy. Springer Berlin Heidelberg.
March 12, 2024
data, shadow, refer, information, that, person, leaves, behind, unintentionally, while, taking, part, daily, activities, such, checking, their, mails, scrolling, through, social, media, even, using, their, debit, credit, card, term, data, shadow, coined, 1972,. Data shadows refer to the information that a person leaves behind unintentionally while taking part in daily activities such as checking their e mails scrolling through social media or even by using their debit or credit card 1 2 3 The term data shadow was coined in 1972 by Kerstin Aner a member of the Swedish legislature 4 The generated information has the potential to create a vastly detailed record of an individual s daily trails which includes the individual s thoughts and interests whom they communicate with information about the organizations with which they work or interact with and so forth 2 This information can be dispersed to a dozen organizations and servers depending on their use 5 Along with Individuals the activities of institutions and organizations are also tracked Data Shadows are closely linked with data footprints which are defined as the data that has been left behind by the individual themselves through various activities such as online activities communication information and transactions 2 In a chapter for the book Geography and Technology researcher Matthew Zook and his co authors note that data shadows have come as a result of people becoming digital individuals and that these shadows are continually evolving and changing 6 They are used to model and predict political opinions and make inferences about a person s political values or susceptibility to advertising 1 Contents 1 Digital footprint 2 Dataveillance 3 Privacy 4 ReferencesDigital footprint editThe data or digital footprints are obtained from monitoring and tracking individuals digital activities Digital footprints provide a drive for companies such as Facebook and Google to invest in obtaining data generated from these footprints in order to be sold to marketers 7 As illustrated by Bodle users are willing to give up their information to companies they trust 8 Although collecting individuals data raises several ethical concerns it can be valuable for the healthcare data analytics and new health services 9 For instance access to such data can help healthcare services shed light on the causes of disease the effects or side effects the treatments might have and can facilitate a tailored analysis according to the individual s characteristics 10 Dataveillance editMain article Dataveillance Dataveillance gives rise to data shadows since it allows for the identification classification and representation of individuals or organizations 11 Dataveillance is defined as a mode of surveillance which tracks monitors or regulates an individual using digital activity including their personal details and social media activities 5 In 2013 Edward Snowden s revelations on the National Security Agency s PRISM program that the organization would receive emails video clips photos voice and video calls social networking details logins and other data held by a range of US internet firms 12 It is also revealed that corporate social networks share their information with the intelligence agencies 13 Platform owners such as Google and Facebook anchor the trust of their users and reassure them that their information is protected through portrayal of corporate codes of conduct such as Do no evil and Making the world transparent and connected 13 However as pointed out by Bodle platform owners are themselves collecting the user s information and using it for purposes they deem to be necessary 8 Privacy editEurope has brought about a long awaited revision to their data protection framework called the Data Protection Directive 14 According to this European Union countries are forced to remove personal data of individuals upon their request if the information is obsolete or irrelevant 15 Information privacy is defined as the right that individuals have over the data about themselves when subjected to a third party 2 and that the data should not be available to any organization or person without their approval 2 However this is not the case when data is collected and collated for marketers online marketers use cookies spyware adware and so on to capture rich data about their customers 16 State agencies also collect citizen data for security purposes 2 The aftermath of the 9 11 terrorist attacks has allowed US national security agencies to increase their collation and exchange of information in order to strengthen the United States Intelligence Community USIC and to minimize potential threats 17 References edit a b Howard Philip N 2005 New Media Campaigns and the Managed Citizen New York NY Cambridge University Press pp 93 144 ISBN 9780521612272 a b c d e f Kitchin Rob 2014 The data revolution big data open data data infrastructures amp their consequences Sage Publications Ltd pp xvii 222 pages Koops E J 2011 Forgetting footprints shunning shadows A critical analysis of the right to be forgotten in big data practice SCRIPTed 8 3 229 256 SSRN 1986719 Steven Bellovin 2021 06 29 Where Did Data Shadow Come From CircleID a b Raley Rita 2013 Data and countervailence Raw Data Is an Oxymoron MIT Press pp 121 146 ISBN 9780262518284 Zook Matthew Dodge Martin Aoyama Yuko Townsend Anthony 2004 03 31 New Digital Geographies Information Communication and Place Geography and Technology Springer Science amp Business Media p 169 ISBN 9781402018718 Wyner Gordon Wyner Gordon 2015 Digital footprints abound 27 1 16 a href Template Cite journal html title Template Cite journal cite journal a Cite journal requires journal help CS1 maint multiple names authors list link a b German Kathleen M Drushel Bruce 2011 The ethics of emerging media information social norms and new media technology Continuum p 279 Harjumaa Marja Saraniemi Saila Pekkarinen Saara Lappi Minna Simila Heidi Isomursu Minna 2017 12 05 Feasibility of digital footprint data for health analytics and services an explorative pilot study BMC Medical Informatics and Decision Making 16 1 139 doi 10 1186 s12911 016 0378 0 PMC 5112682 PMID 27829413 Kostkova Patty Brewer Helen de Lusignan Simon Fottrell Edward Goldacre Ben Hart Graham Koczan Phil Knight Peter Marsolier Corinne 2016 Who Owns the Data Open Data for Healthcare Frontiers in Public Health 4 7 doi 10 3389 fpubh 2016 00007 ISSN 2296 2565 PMC 4756607 PMID 26925395 Selwyn Neil 2017 12 05 Data entry towards the critical study of digital data and education Learning Media and Technology 40 1 64 82 doi 10 1080 17439884 2014 921628 S2CID 143752752 Kelion Leo 2013 06 25 Q amp A Prism internet surveillance BBC News Retrieved 2017 11 25 a b van Dijck Jose 2014 Datafication dataism and dataveillance Big Data between scientific paradigm and ideology Surveillance amp Society 12 2 ISSN 1477 7487 Gutwirth Serge 2013 European data protection coming of age 1 Aufl 2013 1 ed Springer p 437 Retrieved 25 November 2017 Walker R K 2012 The Right to be Forgotten Hastings Law Journal 64 257 261 Ashworth Laurence Free Clinton August 26 2006 Marketing Dataveillance and Digital Privacy Using Theories of Justice to Understand Consumers Online Privacy Concerns Journal of Business Ethics 67 2 107 123 doi 10 1007 s10551 006 9007 7 ISSN 0167 4544 S2CID 143800212 Mace Robyn R 2009 Intelligence Dataveillance and Information Privacy Springer Berlin Heidelberg Retrieved from https en wikipedia org w index php title Data shadow amp oldid 1188514581, wikipedia, wiki, book, books, library,
