Enhancing access to and sharing of data: Striking the balance between openness and control over data

Reimsbach-Kounatze, Christian

doi:10.5771/9783748924999-25

Cited by 14 publications

(6 citation statements)

References 1 publication

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“…Yet, there are legitimate national, public, and private interests (OECD, 2019). The framework of OECD (2019) lists risks and challenges of data access and sharing and is established in research (e.g., Reimsbach-Kounatze, 2021; Yukhno, 2022; Trampusch, 2023). Moreover, the results of the OECD study are based on workshops held from October 2 to 3, 2017, in Copenhagen.…”

Section: Related Work and Backgroundmentioning

confidence: 99%

Overcoming intergovernmental data sharing challenges with federated learning

Sprenkamp,

Delgado Fernández,

Eckhardt

et al. 2024

Data & Policy

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Intergovernmental collaboration is needed to address global problems. Modern solutions to these problems often include data-driven methods like artificial intelligence (AI), which require large amounts of data to perform well. As AI emerges as a central catalyst in deriving effective solutions for global problems, the infrastructure that supports its data needs becomes crucial. However, data sharing between governments is often constrained due to socio-technical barriers such as concerns over data privacy, data sovereignty issues, and the risks of information misuse. Federated learning (FL) presents a promising solution as a decentralized AI methodology, enabling the use of data from multiple silos without necessitating central aggregation. Instead of sharing raw data, governments can build their own models and just share the model parameters with a central server aggregating all parameters, resulting in a superior overall model. By conducting a structured literature review, we show how major intergovernmental data-sharing challenges listed by the Organisation for Economic Co-operation and Development can be overcome by utilizing FL. Furthermore, we provide a tangible resource implementing FL linked to the Ukrainian refugee crisis that can be utilized by researchers and policymakers alike who want to implement FL in cases where data cannot be shared. Enhanced AI while maintaining privacy through FL thus allows governments to collaboratively address global problems, positively impacting governments and citizens.

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Section: Related Work and Backgroundmentioning

confidence: 99%

Overcoming intergovernmental data sharing challenges with federated learning

Sprenkamp,

Delgado Fernández,

Eckhardt

et al. 2024

Data & Policy

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“…However, quantifying these benefits is challenging [54]. Most recent studies [55] suggest that data access and sharing can increase the value of data for holders, create 10 to 20 times more value for users, i.e., indirect impact, and 20 to 50 times more value for the wider economy, i.e., induced impact. In some cases, data access and sharing may reduce data holders' producer surplus [56].…”

Section: Economic Social and Environmental Impact Of Our Proposalmentioning

confidence: 99%

Unlocking the Power of Digital Commons: Data Cooperatives as a Pathway for Data Sovereign, Innovative and Equitable Digital Communities

Bühler

Calzada

Cane

et al. 2023

Digital

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Network effects, economies of scale, and lock-in-effects increasingly lead to a concentration of digital resources and capabilities, hindering the free and equitable development of digital entrepreneurship, new skills, and jobs, especially in small communities and their small and medium-sized enterprises (“SMEs”). To ensure the affordability and accessibility of technologies, promote digital entrepreneurship and community well-being, and protect digital rights, we propose data cooperatives as a vehicle for secure, trusted, and sovereign data exchange. In post-pandemic times, community/SME-led cooperatives can play a vital role by ensuring that supply chains to support digital commons are uninterrupted, resilient, and decentralized. Digital commons and data sovereignty provide communities with affordable and easy access to information and the ability to collectively negotiate data-related decisions. Moreover, cooperative commons (a) provide access to the infrastructure that underpins the modern economy, (b) preserve property rights, and (c) ensure that privatization and monopolization do not further erode self-determination, especially in a world increasingly mediated by AI. Thus, governance plays a significant role in accelerating communities’/SMEs’ digital transformation and addressing their challenges. Cooperatives thrive on digital governance and standards such as open trusted application programming interfaces (“APIs”) that increase the efficiency, technological capabilities, and capacities of participants and, most importantly, integrate, enable, and accelerate the digital transformation of SMEs in the overall process. This review article analyses an array of transformative use cases that underline the potential of cooperative data governance. These case studies exemplify how data and platform cooperatives, through their innovative value creation mechanisms, can elevate digital commons and value chains to a new dimension of collaboration, thereby addressing pressing societal issues. Guided by our research aim, we propose a policy framework that supports the practical implementation of digital federation platforms and data cooperatives. This policy blueprint intends to facilitate sustainable development in both the Global South and North, fostering equitable and inclusive data governance strategies.

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“…Secondly, the larger number of users also increases the firm's revenues (e.g., a larger number of users increases the advertising revenues for social media and search engines). 119 Thirdly, data may be defined as an 'infrastructural resource': 120 data is not an end-user product as such, but is, rather, an input that produces different types of services and improves the quality of goods. A dataset is simply a compilation of different data, which does not have any economic value as such.…”

Section: 5b Market Failuresmentioning

confidence: 99%

Shall we share? The principle of FRAND in B2B data sharing

Botta

2023

SSRN Journal

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Enhancing access to and sharing of data: Striking the balance between openness and control over data

Cited by 14 publications

References 1 publication

Overcoming intergovernmental data sharing challenges with federated learning

Overcoming intergovernmental data sharing challenges with federated learning

Unlocking the Power of Digital Commons: Data Cooperatives as a Pathway for Data Sovereign, Innovative and Equitable Digital Communities

Shall we share? The principle of FRAND in B2B data sharing

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