Abtract
Big Data is expected to unleash data-driven innovation,which is supposed to better address and solve challengesin our society.
As a so-called non-rival good, the sharingand re-using of data by one actor does not diminish its valuefor other actors and can create significant spillover effects.
Data is still often stored in data silos. Releasing data fromsilos and sharing it may enhance social and economic welfare.
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References
See V. Mayer-Schönberger, K. Cukier: Big Data: A Revolution that Will Transform How We Live, Work, and Think, New York 2013, Houghton Mifflin Harcourt Publishing Company, p. 30.
See M. Hilbert: Big Data for Development: A Review of Promises and Challenges, in: Development Policy Review, Vol. 34, No. 1, 2016, pp. 135–174, p. 142.
OECD: Data-Driven Innovation: Big Data for Growth and Well-Being, Paris 2015, OECD Publishing, p. 179.
See M. von Grafenstein, J. Holzel, F. Irgmeier, J. Pohle: Nudging: Regulierung durch Big Data und Verhaltenswissenschaften, Berlin 2018, ABIDA (Assessing Big Data), p. 46.
See A. Habenstein, S. D'Onofrio, E. Portmann, M. Sturmer, T. Myrach: Open Smart City: Good Governance fur smarte Stadte, in: A. Meier, E. Portmann (eds.):Smart City: Strategie, Governance und Projekte, Wiesbaden 2016, Springer Vieweg, pp. 47–71, p. 48.
Regarding lock-in-effects, see E. Veronelli: Smart cities vs “locked- in” cities, CORDIS EU research results, 12 September 2016, available at https://cordis.europa.eu/news/rcn/135237/en.
Regarding smart cities and surveillance, see T. Wadhwa: Smart Cities: Toward the Surveillance Society?, in: D. Araya (ed.): Smart Cities as Democratic Ecologies, New York 2015, Palgrave Macmillan, pp. 125–141.
See W. Hoffmann-Riem, S. Fritzsche: Innovationsverantwor- tung - zur Einleitung, in: M. Eifert, W. Hoffmann-Riem (eds.): Innovation und Recht III - Innovationsverantwortung, Berlin 2009, Duncker & Humblot, p. 16.
See for example the smart city project in Toronto: J. Wakefield:The Google city that has angered Toronto, BBC News, 18 May 2019.
Regarding biomedical data, see J. L. Contreras: Leviathan in the Commons: Biomedical Data and the State, in: K.J. Strandburg, B.M. Frischmann, M.J. Madison (eds.): Governing Medical Knowledge Commons, Cambridge 2017, Cambridge University Press, pp. 19–45.
See, regarding the perspective of the legal regulator, A. Vofßkuhle: Neue Verwaltungsrechtswissenschaft, in: W. Hoffmann-Riem, E. Schmidt-Aßmann.A. Voßkuhle (eds.): Grundlagen des Verwal- tungsrechts - Band I: Methoden - Maßstäbe - Aufgaben - Organisation, 2nd edition, Munich 2012, C.H. Beck, cip. 20; and regarding the governance perspective, J. Hofmann, C. Katzenbach, K. Golatz: Between coordination and regulation: Finding the governance in Internet governance, in: New Media & Society, Vol. 19, No. 9, 2017, pp. 1406–1423.
See, regarding regulation by the state: A. VofSkuhle, op. cit.; and regarding regulation by private companies: J. Black: Decentring regulation: Understanding the role of regulation and selfregulation in a “post-regulatory” world, in: Current legal problems, Vol. 54, No. 1, 2001, pp.103–146
see the term “private ordering” at Elkin-Koren who defines the term as a situation wherein “the rule-making process regarding the use of information is privatized, and the legal power to define the boundaries of public access to information is delegated to private parties.” N. Elkin-Koren: A Public-Regarding Approach to Contracting over Copyrights, in: R. Dreyfuss, H. First, D. Zimmerman (eds): Expanding the Boundaries of Intellectual Property: hnovation Policy for the Knowledge Society, Oxford 2001, Oxford University Press, pp. 191
192 as cited by S. Dusollier: Sharing Access to Intellectual Property through Private Ordering, in: Chicago-Kent Law Review, Vol. 82, 2007, pp. 1391, 1393, fn. 8
see S. Schwarcz: Private ordering, in: Northwestern University Law Review, Vol. 97, No. 1, 2002, p. 319.
Regarding the privacy paradox, see for example G. Müller, C. Flender, M. Peters: Vertrauensinfrastruktur und Privatheit als ökonomische Fragestellung, in:J.Buchmann (ed.): Internet Privacy: Eine multidisziplinäre Bestandsaufnahme, Heidelberg 2012, Springer Vieweg, pp. 143–188, p. 175.
See H. Richter, P. R. Slowinski: The Data Sharing Economy: On the Emergence of New Intermediaries, in: IIC-lnternational Review of Intellectual Property and Competition Law, Vol. 50, No. 1, 2019, pp. 4–29, p. 7, fn 15, discussing the risk of liability of breaching data protection law.
Regarding coopetition, see D.R. Gnyawali, R. Madhavan, J. He, M. Bengtsson: The competitioncooperation paradox in inter-firm relationships: A conceptual framework, in: Industrial Marketing Man- agement, Vol. 53, 2016, pp. 7–18; sometimes, the data donor also overestimates the value of its data due to an endowment effect
see D. Kahneman, J. Knetsch, R. Thaler: Anomalies: The Endow- ment Effect, Loss Aversion, and Status Quo Bias, in: Journal of Eco- nomic Perspectives, Vol. 5, No. 1, 1991, pp. 193–206.
Regarding transaction costs in law in general, see R.H. Coase: The problem of social cost, in: The Journal of Law and Economics, Vol. 111, 1960, pp. 1–44.
Bounded rationality, such as unwarranted fear of failing to comply with data protection law, may also contribute to the reluctance to share data, see, for example H.A. Simon: Bounded rationality and organizational learning, in: Organization science, Vol. 2, No. 1, 1991, pp. 125–134.
Finally, excessive transaction costs may lead to a socalled tragedy of the anti-commons, see M.A. Heler: The Tragedy of the Anticommons: Property in the transition from Marx to markets, in: Harvard Law Review, Vol. 111, No. 3, 1998, pp. 621–688
and regarding patents, M.A. Heller, R.S. Eisenberg: Can patents deter innovation? The anticommons in biomedical research, in: Science, Vol. 280, No. 5364, 1998, pp. 698–701.
See similar reasons mentioned by V. Kathuria: Greed for data and exclusionary conduct in data-driven markets, in: Computer law & security review, Vol. 35, No. 1, 2019, pp. 89–102.
See M. von Grafenstein: The Principle of Purpose Limitation in Data Protection Laws, Baden-Baden 2018, Nomos, p. 77.
Regarding decision heuristics, see S. Mousavi, G. Gigerenzer: Risk, uncertainty, and heuristics, in: Journal of Business Research, Vol. 67, No. 8, 2014, pp. 1671–1678.
See M. Olson: Collective action, in: S.N. Durlauf, L.E. Blume:The New Palgrave Dictionary of Economics, 2nd edition, London 2008, Palgrave Macmillan, pp. 876–880.
Regarding the rationale of Art. 20 GDPR, see for example T. Jülicher, C. Rottgen, M. von Schönfeld: Das Recht auf Datenubertragbarkeit: Ein datenschutzrechtliches Novum, in: Zeitschrift für Dat- enschutz, Vol. 6, No. 8, 2016, pp. 358–362.
R. H. Weber: Improvement of Data Economy Through Compulsory Licences?, in:S. Lohsse, R. Schulze, D. Staudenmayer: Trading Data in the Digital Economy: Legal Concepts and Tools, Baden-Baden 2017, Nomos.p. 151.
See, for example, M. Grützmacher: Dateneigentumein Flickenteppich, in: Computer und Recht, Vol. 32, No. 8, 2016, pp. 485–495
N. Härting: “Dateneigentum” -Schutz durch Immaterialgüter- recht?, in: Computer und Recht, Vol. 32, No. 10, 2016, pp. 646–649; N. Jentzsch: Dateneigentum - Eine gute Idee für die Datenokönomie, Berlin 2018, Think Tank für die Gesellschaft in technologischen Wan- del, available at https://www.stiftung-nv.de/sites/default/files/nicola_jentzsch_dateneigentum.pdf}.
See H. Richter, R.M. Hilty: Die Hydra des Dateneigentums - eine methodische Betrachtung, Discussion Paper No. 12, Munich 2018, Max-Planck-Institut für Innovation und Wettbewerb, in: Stiftung Dat- enschutz (ed.): Dateneigentum und Datenhandel, Schriftenreihe Daten Debatten, Vol. 3, Berlin 2018, Erich Schmidt Verlag, pp. 241–259.
Regarding this last aspect, see again, ibid., p. 15.
See A. Nahles: Digitaler Fortschritt durch ein Daten-für-Alle-Gesetz, Positionspapier der Parteivorsitzenden der Sozialdemokratischen Partei Deutschlands, Berlin 2019, available at https://www.spd.de/aktuelles/daten-fuer-alle-gesetz/}
See T. Ramge, V. Mayer-Schonberger: Das Digital: Markt, Wertschöpfung und Gerechtigkeit im Datenkapitalismus, 3rd edition. Berlin 2017, Ullstein.
Information on the project “Privacy by design in smart cities” available at https://www.hiig.de/en/project/privacy-by-design-in-smart-cities/
Alexander von Humboldt Institute for Internet and Society: Data Protection by Design in Smart Cities, HUG Discussion Paper, forthcoming, available at https://www.hiig.de
For more on “reasonable expectations”, see Article 29 Data Protection Working Party: Opinion 06/2014 on the notion of legitimate in- terests of the data controller under Article 7 of Directive 95/46/EC, 2014, p. 51; regarding risk expectations, see Art. 35 (9) GDPR: “Where appropriate, the controller shall seek the views of data subjects or their representatives on the intended processing, without prejudice to the protection of commercial or public interests or the security of processing operations.”
See N. Purtova: The law of everything. Broad concept of persona data and future of EU data protection law, in: Law, Innovation and Technology, Vol. 10, No. 1, 2018, pp. 40–81.
See also W. Kerber: Digital markets, data, and privacy: competition law, consumer law and data protection, in: Journal of Intellectual Property Law & Practice, Vol. 11, No. 11, 2016, pp. 856–866.
M.A. Heller: The Tragedy of the Anticommons: Property in the transition from Marx to markets, in: Harvard Law Review, Vol. 111, No. 3, 1998, pp. 621–688
M.A. Heller, R.S. Eisenberg: Can patents deter nnovation? The anticommons in biomedical research, in: Science, Vol. 280, No.5364, 1998, pp. 698–701
R.P. Merges: Contracting into liability rules: Intellectual property rights and collective rights organi- zations, in: California Law Review, Vol.84, No.5, 1996, pp. 1293–1393
M.J. Barnett: The anti-commons revisited, in: Harvard Journal of Law & Technology, Vol.29, No. 1, 2015, pp. 127–203.
A. Acquisti, C. Taylor, L. Wagman: The economics of privacy, in: Journal of Economic Literature, Vol. 54, No. 2, 2016, pp. 442–92.
M.E. Stucke, A.P. Grunes: Big data and competition policy, Oxford 2016, Oxford University Press; N. Srnicek: Platform Capitalism, London 2017, Polity
V. Kathuria: Greed for data and exclusionary conduct in data-driven markets, in: Computer law & security review, Vol.35, No. 1, 2019, pp. 89–102.
H.W. Chesbrough: Open innovation: The new imperative for cre- ating and profiting from technology, Boston 2006, Harvard Business School Press
E. von Hippel: Democratizing innovation: The evolv- ng phenomenon of user innovation, in: Journal für Betriebswirtschaft, Vol. 55, No. 1, 2005, pp. 63–78
E. von Hippel, G. von Krogh: Open source software and the “privatecollective” innovation model: Issues for organization science, in: Organization Science, Vol. 14, No. 2, 2003, pp. 209–223.
R.B. Bouncken, J. Gast, S. Kraus, M. Bogers: Coopetition: a systematic review, synthesis, and future research directions, in: Review of Managerial Science, Vol. 9, No. 3, 2015, pp. 577–601.
See, for example, G. van Overwalle, E. van Zimmeren, B. Verbeure, G. Matthijs: Models for facilitating access to patents on ge- netic inventions, in: Nature Reviews Genetics, Vol. 7, No. 2, 2006, pp. 143–148
M. Mattioli: The data-pooling problem, in: Berkeley Tech- nology Law Journal, Vol. 32, No. 1, 2017, pp. 179–236
B. Lundqvist: Competition and data pools, in: Journal of European Consumer and Market Law, Vol. 7, No. 4, 2018, pp. 146–154
M. Finck: Blockchains and theGDPR, in: European Data Protection Law Review, Vol. 4, 2018, pp. 17–35
H. Richter, P.R. Slowinski: The Data Sharing Economy: On the Emergence of New Intermediaries, in: HC-International Review of Intellectual Property and Competition Law, Vol. 50, No. 1, 2019, pp. 4–29.
See the proposed terminology and a first categorisation of interorganisational data governance models in Alexander von Humboldt Institute for Internet and Society: Data Governance: Towards a Conceptual Framework, HUG Discussion Paper, forthcoming, available at http://www.hiig.de/paper-Data-Governance-Towards-Conceptual-Framework/
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von Grafenstein, M., Wernick, A. & Olk, C. Data Governance: Enhancing Innovation and Protecting Against Its Risks. Intereconomics 54, 228–232 (2019). https://doi.org/10.1007/s10272-019-0829-9
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DOI: https://doi.org/10.1007/s10272-019-0829-9