An ethico-legal framework for social data science
This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how to design and implement an open platform for big data social science, including, in particular, personal data. To this end, we discuss a...
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Published in | International journal of data science and analytics Vol. 11; no. 4; pp. 377 - 390 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
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Cham
Springer International Publishing
01.05.2021
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Online Access | Get full text |
ISSN | 2364-415X 2364-4168 |
DOI | 10.1007/s41060-020-00211-7 |
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Abstract | This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how to design and implement an open platform for big data social science, including, in particular, personal data. To this end, we discuss a number of infrastructural, organizational and methodological principles to be developed for a concrete implementation. These include not only systematically tools and methodologies that effectively enable both the empirical evaluation of the privacy risk and data transformations by using privacy-preserving approaches, but also the development of training materials (a massive open online course) and organizational instruments based on legal and ethical principles. This paper provides, by way of example, the implementation that was adopted within the context of the SoBigData Research Infrastructure. |
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AbstractList | This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how to design and implement an open platform for big data social science, including, in particular, personal data. To this end, we discuss a number of infrastructural, organizational and methodological principles to be developed for a concrete implementation. These include not only systematically tools and methodologies that effectively enable both the empirical evaluation of the privacy risk and data transformations by using privacy-preserving approaches, but also the development of training materials (a massive open online course) and organizational instruments based on legal and ethical principles. This paper provides, by way of example, the implementation that was adopted within the context of the SoBigData Research Infrastructure. |
Author | Pedreschi, Dino van Putten, David Forgó, Nikolaus Lishchuk, Iryna Monreale, Anna Krügel, Tina Mahieu, René van den Hoven, Jeroen Hänold, Stefanie Pratesi, Francesca |
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Führt Big Data zum Paradigmenwechsel im DatenschutzMMR2014176360364 Rodríguez-GonzálezAVakaliAMayerMAOkumuraTMenasalvas-RuizESpiliopoulouMIntroduction to the special issue on social data analytics in medicine and healthcareInt. J. Data Sci. Anal.2019832510.1007/s41060-019-00199-9 Van den Hoven, J.: ICT and value sensitive design. In: The Information Society: Innovation, Legitimacy, Ethics and Democracy in Honor of Professor Jacques Berleur SJ, pp. 67–72. Springer, Boston (2007) MarnauNAnonymisierung. Pseudonymisierung und Transparenz für Big DataDuD201640742843310.1007/s11623-016-0631-9 BretthauerSCompliance-by-design-Anforderungen bei Smart DataZD201662267274 Mayer-SchönbergerVPadovaYRegime change? Enabling big data through Europe’s new data protection regulationColum. Sci. Tech. L. Rev.201617315335 Capitani, D., di Vimercati, S., Foresti, S., Jajodia, S., Paraboschi, S., Samarati, P.: Over-encryption: management of access control evolution on outsourced data. 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References_xml | – reference: Rodríguez-GonzálezAVakaliAMayerMAOkumuraTMenasalvas-RuizESpiliopoulouMIntroduction to the special issue on social data analytics in medicine and healthcareInt. J. Data Sci. Anal.2019832510.1007/s41060-019-00199-9 – reference: Anderson, C.: The Future of High Tech: The Power of a Strong Startup Eco System. Related by Laurens van de Velde/Universiteit van Twente (2016) – reference: Goyal, V., Pandey, O., Sahai, A., Waters, B.: Attribute-based encryption for fine-grained access control of encrypted data. In: Proceedings of the 13th ACM Conference on Computer and Communications Security (CCS), Alexandria, VA, USA (2006) – reference: European Data Protection Supervisor, Opinion 7/2015. Meeting the Challenges of Big Data. https://secure.edps.europa.eu/EDPSWEB/webdav/site/mySite/shared/Documents/Consultation/Opinions/2015/15-11-19_Big_Data_EN.pdf. Accessed on 31 May 2019 – reference: CarnianiED’ArenzoDLazouskiAMartinelliFMoriPUsage control on cloud systemsFuture Gener. Comput. Syst.201663C375510.1016/j.future.2016.04.010 – reference: PratesiFMonrealeATrasartiRGiannottiFPedreschiDYanagiharaTPRUDEnce: a system for assessing privacy risk vs utility in data sharing ecosystemsTrans. Data Priv.201811139167 – reference: SchefzigJBig Data = Personal Data? Der Personenbezug von Daten bei Big-Data-AnalysenK&R20141912772778 – reference: Park, J., Sandhu, R.: Towards usage control models: beyond traditional access control. In: Proceedings of the 7-th ACM Symposium on Access Control (2002) – reference: Buttarelli, G.: Opinion 4/2015 Towards a New Digital Ethics—Data, Dignity and Technology (2015). Retrieved from https://edps.europa.eu/sites/edp/files/publication/15-09-11_data_ethics_en.pdf. Accessed on 31 May 2019 – reference: ZuboffSBig other: surveillance capitalism and the prospects of an information civilizationJ. Inf. Technol.2015301758910.1057/jit.2015.5 – reference: Capitani, D., di Vimercati, S., Foresti, S., Jajodia, S., Paraboschi, S., Samarati, P.: Over-encryption: management of access control evolution on outsourced data. In: Proceeding of the 33rd International Conference on Very Large Data Bases (VLDB) (2007) – reference: Mayer-SchönbergerVPadovaYRegime change? Enabling big data through Europe’s new data protection regulationColum. Sci. Tech. L. Rev.201617315335 – reference: Martini, M.: In: B. Paal and D. Pauly (eds.) Datenschutz-Grundverordnung. München: C.H. Beck (2017) – reference: KatkoPBabaei-BeigiAAccountability statt Einwilligung? Führt Big Data zum Paradigmenwechsel im DatenschutzMMR2014176360364 – reference: Boehme-NeslerVDas Ende der Anonymität—Wie Big Data das Datenschutzrecht verändertDuD201640741942310.1007/s11623-016-0629-3 – reference: BretthauerSCompliance-by-design-Anforderungen bei Smart DataZD201662267274 – reference: GürsesSCan you engineer privacy?Commun. ACM2014578202310.1145/2633029 – reference: KrügelTDas personenbezogene Datum nach der DS-GVO—Mehr Klarheit und Rechtssicherheit?ZD2017710455460 – reference: Waters, B.: Ciphertext-policy attribute-based encryption: an expressive, efficient, and provably secure realization. In: PKC 2011. LNCS, vol. 6571, pp. 53–70. Springer, Heidelberg (2011) – reference: Narayanan, A., Felten, E.W.: No silver bullet: de-identification still doesn’t work. White Paper (2014). Retrieved from http://randomwalker.info/publications/no-silver-bullet-de-identification.pdf. Accessed on 31 May 2019 – reference: HustinxPPrivacy by design: delivering the promisesIdentity Inf. Soc.20103225325510.1007/s12394-010-0061-z – reference: InkpenDRocheMTeisseireMGuest editorial: Special issue on environmental and geospatial data analyticsInt. J. Data Sci. Anal.201858110.1007/s41060-018-0105-2 – reference: HasanMRundensteinerEAguEAutomatic emotion detection in text streams by analyzing Twitter dataInt. J. Data Sci. Anal.201973510.1007/s41060-018-0096-z – reference: European Research Area: The Lund Declaration (2009). Retrieved from https://era.gv.at/object/document/130. Accessed on 31 May 2019 – reference: FurlettiBTrasartiRCintiaPGabrielliLDiscovering and understanding city events with big data: the case of RomeInf. Multidiscip. Digit. Publ. Inst.20178743 – reference: Van den Hoven, J.: ICT and value sensitive design. In: The Information Society: Innovation, Legitimacy, Ethics and Democracy in Honor of Professor Jacques Berleur SJ, pp. 67–72. Springer, Boston (2007) – reference: MonrealeARinzivilloSPratesiFGiannottiFPedreschiDPrivacy-by-design in big data analytics and social miningEPJ Data Sci.2014311010.1140/epjds/s13688-014-0010-4 – reference: CapitaniDdi VimercatiSForestiSJajodiaSParaboschiSSamaratiPEncryption policies for regulating access to outsourced dataACM Trans. Database Syst.201035212 – reference: SarunskiMBig Data-Ende der Anonymität? Fragen aus Sicht der Datenschutzaufsichtsbehörde Mecklenburg-VorpommernDuD201640742442710.1007/s11623-016-0630-x – reference: President of the Council of European Union: Rome Declaration on Responsible Research and Innovation in Europe (2014). Retrieved from https://ec.europa.eu/research/swafs/pdf/rome_declaration_RRI_final_21_November.pdf. Accessed on 31 May 2019 – reference: MarnauNAnonymisierung. Pseudonymisierung und Transparenz für Big DataDuD201640742843310.1007/s11623-016-0631-9 – reference: MonrealeAAndrienkoGLAndrienkoNVGiannottiFPedreschiDRinzivilloSWrobelSMovement data anonymity through generalizationTrans. Data Priv.201032911212725421 – reference: ParkJSandhuRThe UCONABC usage control modelACM Trans. Inf. Syst. Secur.20047112817410.1145/984334.984339 – volume: 17 start-page: 315 year: 2016 ident: 211_CR20 publication-title: Colum. Sci. Tech. L. 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