User contributions
9 January 2020
Item:Q2071
wbsetlabel-add:1|fr: Etude de la configuration en Tiers-Lieu: la repolitisation par le service
+132
Item:Q2071
wbsetlabel-set:1|en: Research into tiers-lieu configuration : re-politicisation through services
+2
Item:Q2071
wbsetclaim-create:2||1: instance of (P3): PhD thesis (Q3247)
+403
Item:Q2368
wbsetclaim-create:2||1: instance of (P3): PhD thesis (Q3247)
+403
Item:Q3247
wbsetlabel-add:1|fr: thèse de doctorat
+77
Item:Q3247
wbsetclaim-create:2||1: subclass of (P4): document (Q2408)
+418
Item:Q3247
wbeditentity-create:2|fr: PhD thesis
Item:Q2415
wbsetaliases-add:1|en: Zeynep Tufekci
+83
Item:Q2415
wbsetaliases-add:1|fr: Zeynep Tufekci
+83
Item:Q2415
wbsetdescription-add:1|fr: professeure associée à l'Université de Caroline du Nord
+117
Item:Q2415
wbsetdescription-set:1|en: associate Professor at the University of North Carolina
+38
Item:Q2415
wbsetlabel-add:1|fr: Zeynep Tüfekçi
+75
Property:P259
wbsetdescription-add:1|fr: format de données pour la syndication de contenu Web.
+113
Property:P259
wbsetlabel-add:1|fr: flux web
+66
Item:Q3244
wbsetclaim-create:2||1: image (P47): Sandra Wachter at Berkman Klein Center for Internet & Society.jpg
+399
Item:Q3244
wbsetclaim-create:2||1: Wikibase registry ID (P258): Q72977797
+344
Item:Q2518
wbsetdescription-add:1|en: unambiguous specification of how to solve a class of problems
+120
Item:Q2518
wbsetdescription-add:1|fr: procédure systématique permettant de résoudre un problème
+120
Item:Q2518
wbsetlabel-add:1|fr: algorithme
+69
Item:Q3246
wbsetclaim-create:2||1: concerns (P110): algorithm (Q2518)
+405
Item:Q3246
wbsetclaim-create:2||1: concerns (P110): Sandra Wachter (Q3244)
+422
Item:Q3246
wbsetclaim-create:2||1: official website (P15): https://www.ft.com/content/bc959e8c-1b67-11ea-97df-cc63de1d73f4
+397
Item:Q3246
wbsetclaim-create:2||1: instance of (P3): news item (Q1206)
+418
Item:Q3246
wbsetdescription-add:1|en: article published in the Financial Times in Dec 2019
+111
Item:Q3246
wbsetlabel-add:1|en: Algorithms drive online discrimination, academic warns
+113
Item:Q3246
wbeditentity-create:2|fr: Algorithms drive online discrimination, academic warns, article publié dans le Financial Times en dec 2019
Item:Q3245
wbsetclaim-create:2||1: official website (P15): https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3388639
+393
Item:Q3245
wbsetclaim-create:2||1: author (P121): Sandra Wachter (Q3244)
+422
Item:Q3245
wbsetclaim-create:2||1: DOI (P62): 10.2139/ssrn.3388639
+354
Item:Q3245
wbeditentity-create:2|fr: Affinity Profiling and Discrimination by Association in Online Behavioural Advertising, scholarly article
Item:Q3244
wbsetclaim-create:2||1: instance of (P3): human (Q355)
+416
Item:Q3244
wbsetdescription-add:1|de: Associate Professor and Senior Research Fellow in Data Ethic at the University of Oxford
+147
Item:Q3244
wbsetlabel-add:1|de: Sandra Watcher
+73
Item:Q3244
wbeditentity-create:2|fr: Sandra Watcher, professeure associée et chercheuse en éthique des données à l'Université d'Oxford
7 January 2020
Item:Q3215
wbsetclaim-update:2||1: comment (P126): ≈ 25% provided sensitive information without verifying the identity of the requester. A further 15% of organizations contacted requested a form of identity that we believed could easily be stolen or forged (such as a device identifier or a signed statement swearing to be the data subject)
-2
Item:Q3215
wbsetclaim-update:2||1: comment (P126): We found that the largest organizations in our data set (e.g. Fortune 100 companies) tended to perform well and that the smallest organizations tended to simplyi gnore GDPR requests. Non-profits and mid-size orga-nizations (100 - 1,000 employees) accounted for around 70% of mishandled requests.
+1
Item:Q3215
wbsetclaim-update:2||1|1: official website (P15): https://i.blackhat.com/USA-19/Thursday/us-19-Pavur-GDPArrrrr-Using-Privacy-Laws-To-Steal-Identities-wp.pdf
+278
Item:Q3215
wbsetclaim-update:2||1: comment (P126): ≈ 25% provided sensitive information without verifying the iden-tity of the requester . A further 15% of organizations contacted requested a form of identity that we believed could easily be stolen or forged (such as a device identifier or a signed statement swearing to be the data subject)
+1
Item:Q3215
wbsetclaim-create:2||1: comment (P126): ≈ 25% provided sensitive information without verifying the iden-tity of the requester . A further 15% of organizations contacted requested a form of identity that we believed could easily be stolen or forged (such as a device identifier or a signed statement swearing to be thedata subject)
+613
Item:Q3215
wbsetclaim-update:2||1: comment (P126): We found that the largest organizations in our data set (e.g. Fortune 100 companies) tended to perform well and that the smallest organizations tended to simplyi gnore GDPR requests. Non-profits and mid-size orga-nizations (100 - 1,000 employees) accounted for around70% of mishandled requests.
+1
Item:Q3215
wbsetclaim-create:2||1: comment (P126): We found that the largest organizations in our data set (e.g. Fortune 100 companies) tended to performwell and that the smallest organizations tended to simplyi gnore GDPR requests. Non-profits and mid-size orga-nizations (100 - 1,000 employees) accounted for around70% of mishandled requests.
+614
Item:Q3215
wbsetclaim-update:2||1|1: official website (P15): https://i.blackhat.com/USA-19/Thursday/us-19-Pavur-GDPArrrrr-Using-Privacy-Laws-To-Steal-Identities.pdf
+286
Item:Q3215
wbsetclaim-create:2||1: official website (P15): https://i.blackhat.com/USA-19/Thursday/us-19-Pavur-GDPArrrrr-Using-Privacy-Laws-To-Steal-Identities.pdf
+422
Item:Q3215
wbsetclaim-create:2||1: comment (P126): In a survey of more than 150 companies, the authors demonstrate that organizations willingly provide highly sensitive information in response to GDPR right of access requests with little or no verification of the individual making the request.
+580
Item:Q3215
wbsetclaim-create:2||1: official website (P15): https://i.blackhat.com/USA-19/Thursday/us-19-Pavur-GDPArrrrr-Using-Privacy-Laws-To-Steal-Identities-wp.pdf
+441
Item:Q3215
wbsetclaim-create:2||1: instance of (P3): scholarly article (Q210)
+416
Item:Q3215
wbeditentity-create:2|fr: GDPArrrrr: Using Privacy Laws to Steal Identities, scholarly article published in 2019
Item:Q2903
wbsetclaim-update:2||1|2: official website (P15): http://outil.ge.ch/chacatfich/#/catalog/institution/214/218
+2
Item:Q2903
wbsetclaim-update:2||1|2: official website (P15): http://outil.ge.ch/chacatfich/#/catalog/institution/214/218
+1
Item:Q2903
wbsetclaim-update:2||1|2: official website (P15): http://outil.ge.ch/chacatfich/#/catalog/institution/214/218
+137