The Data Sharing Economy: On the Emergence of New Intermediaries

Richter, Heiko; Slowinski, Peter R.

doi:10.1007/s40319-018-00777-7

Cited by 77 publications

(42 citation statements)

References 25 publications

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“…From a practical point of view, the cost to distinguish personal from nonpersonal data is high. Consequently, companies increasingly treat nonpersonal data as personal data [50], a practice that seems to be working for this current period. It is yet questionable for how long companies can sustain this practice.…”

Section: Nonpersonal Datamentioning

confidence: 99%

Toward privacy-sensitive human–robot interaction: Privacy terms and human–data interaction in the personal robot era

Chatzimichali

Harrison

Chrysostomou

2020

Paladyn, Journal of Behavioral Robotics

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Can we have personal robots without giving away personal data? Besides, what is the role of a robots Privacy Policy in that question? This work explores for the first time privacy in the context of consumer robotics through the lens of information communicated to users through Privacy Policies and Terms and Conditions. Privacy, personal and non-personal data are discussed under the light of the human–robot relationship, while we attempt to draw connections to dimensions related to personalization, trust, and transparency. We introduce a novel methodology to assess how the “Organization for Economic Cooperation and Development Guidelines Governing the Protection of Privacy and Trans-Border Flows of Personal Data” are reflected upon the publicly available Privacy Policies and Terms and Conditions in the consumer robotics field. We draw comparisons between the ways eight consumer robotic companies approach privacy principles. Current findings demonstrate significant deviations in the structure and context of privacy terms. Some practical dimensions in terms of improving the context and the format of privacy terms are discussed. The ultimate goal of this work is to raise awareness regarding the various privacy strategies used by robot companies while ultimately creating a usable way to make this information more relevant and accessible to users.

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Section: Nonpersonal Datamentioning

confidence: 99%

Toward privacy-sensitive human–robot interaction: Privacy terms and human–data interaction in the personal robot era

Chatzimichali

Harrison

Chrysostomou

2020

Paladyn, Journal of Behavioral Robotics

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“…In the digital economy, the value of information increases with the availability and quality of data; market players are thus interested in accessing data from other players. In this vein, Richter and Slowinski (2019), for example, address the regulatory approach to incentivising access to data, while Graef et al (2015) discuss potential liability for refusing to grant access to data. They note the existence of network effects that might increase the likelihood of dominance and lead to foreclosure of competitors by raising barriers to entry in the large collections of user data.…”

Section: Competition In and For Data Marketsmentioning

confidence: 99%

(Re)making data markets: an exploration of the regulatory challenges

Taylor¹,

Mukiri‐Smith²,

Petročnik³

et al. 2020

Preprint

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Regulating the data market is shaping up to be one of the major challenges of the twenty-first century. In order to think about regulating this market, however, we first need to make its dimensions and dynamics more accessible to research. In this paper we explore what the state of the sociological and legal research on markets can tell us about the market for data: what kind of market it is, the practices and configurations of actors that constitute it, and what kinds of data are traded there. We start from the subjective opacity of this market to researchers interested in regulation, using ‘dark pools’ as a point of reference for the challenges of understanding how data are traded and channelled. We explore comparisons from food and medicine regulation to understand how these markets have been shaped and the different aims that have been taken into account in doing so, and discuss the implications of these explorations for the future regulation of data markets.

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“…A data market, a platform to buy/sell data, works as a method for accelerating data exchange. There are various online markets such as Every Sense 1 [16], Japan Data Exchange Inc., 2 Azure Marketplace 3 [17], CKAN 4 [18], Qlik DataMarket 5 [19], and Dawex 6 [20]. Additionally, some research groups have surveyed the existing data markets and classified data marketplaces based on various aspects [21][22][23].…”

Section: Situations and Issues Surrounding Data Utilizationmentioning

confidence: 99%

Development and Evaluation of a New Platform for Accelerating Cross-Domain Data Exchange and Cooperation

2019

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The technologies for collecting and analyzing data are developing significantly, enabling us to gain new knowledge from various types of data. Recently, the considerably increasing expectation for cross-domain data exchange and cooperation has attracted attention from data markets. However, as we lack data-utilization knowledge, an accurate evaluation of data is difficult; a non-price indicator for deciding the exchange of data is needed. Thus, in this study, we propose a new online platform for stakeholders to communicate regarding data utilization. Our online platform, called Web Innovators Marketplace on Data Jackets (Web IMDJ), is built with reference to the process of IMDJ workshops. Web IMDJ is superior to the conventional paper-based IMDJ (hereafter, Table IMDJ) in terms of reducing the burden on conducting workshops. Notably, Table IMDJ and Web IMDJ have different communication media, and this may affect the data-utilization knowledge proposed in the workshop. Therefore, we conducted workshops on both platforms under a controlled experimental environment to compare the proposed data-utilization knowledge. Consequently, the knowledge proposed in Web IMDJ gained equal or higher ratings by third-party evaluators (those who did not join in the experimental workshop). By contrast, subjects themselves evaluated the knowledge proposed in Table IMDJ as superior to Web IMDJ. These results revealed that both workshops have advantages as data-utilization platforms. Furthermore, we derived the best practices to utilize data effectively from a detailed analysis of the data obtained from the experimental workshops.

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The Data Sharing Economy: On the Emergence of New Intermediaries

Abstract: Data-driven markets depend on access to data as a resource for products and services. Since the quality of information that can be drawn from data increases

Cited by 77 publications

References 25 publications

Toward privacy-sensitive human–robot interaction: Privacy terms and human–data interaction in the personal robot era

Toward privacy-sensitive human–robot interaction: Privacy terms and human–data interaction in the personal robot era

(Re)making data markets: an exploration of the regulatory challenges

Development and Evaluation of a New Platform for Accelerating Cross-Domain Data Exchange and Cooperation

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