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 inInternational journal of data science and analytics Vol. 11; no. 4; pp. 377 - 390
Main Authors Forgó, Nikolaus, Hänold, Stefanie, van den Hoven, Jeroen, Krügel, Tina, Lishchuk, Iryna, Mahieu, René, Monreale, Anna, Pedreschi, Dino, Pratesi, Francesca, van Putten, David
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.05.2021
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Online AccessGet full text
ISSN2364-415X
2364-4168
DOI10.1007/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.
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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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)
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MonrealeAAndrienkoGLAndrienkoNVGiannottiFPedreschiDRinzivilloSWrobelSMovement data anonymity through generalizationTrans. Data Priv.201032911212725421
Boehme-NeslerVDas Ende der Anonymität—Wie Big Data das Datenschutzrecht verändertDuD201640741942310.1007/s11623-016-0629-3
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FurlettiBTrasartiRCintiaPGabrielliLDiscovering and understanding city events with big data: the case of RomeInf. Multidiscip. Digit. Publ. Inst.20178743
MonrealeARinzivilloSPratesiFGiannottiFPedreschiDPrivacy-by-design in big data analytics and social miningEPJ Data Sci.2014311010.1140/epjds/s13688-014-0010-4
PratesiFMonrealeATrasartiRGiannottiFPedreschiDYanagiharaTPRUDEnce: a system for assessing privacy risk vs utility in data sharing ecosystemsTrans. Data Priv.201811139167
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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. In: Proceeding of the 33rd International Conference on Very Large Data Bases (VLDB) (2007)
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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
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Snippet This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe...
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SubjectTerms A Social Mining and Big Data Ecosystem for Open
Artificial Intelligence
Business Information Systems
Computational Biology/Bioinformatics
Computer Science
Data Mining and Knowledge Discovery
Database Management
Regular Paper
Responsible Data Science
Title An ethico-legal framework for social data science
URI https://link.springer.com/article/10.1007/s41060-020-00211-7
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