A new paper by Cancan Wang and Kalina Staykova
Open public data, as a philosophy and a set of policies for increasing the access and use of the dataset of public bodies, has been advocated and implemented across the globe for its promise of increased public accountability among other benefits. Nonetheless, it is often neglected that public accountability is a desired, but not a guaranteed outcome.
Since the first attempt in Shanghai to broaden public data access in 2011, open public data initiatives have witnessed rapid development but also pushbacks from local municipalities and departments, among which lack of willingness in participation and low data quality are the two primary challenges to realize the benefits of local open public data initiatives. As a countermeasure, the local regulators of open public data initiatives in Shanghai have experimented with a novel approach, building on the assumption that the perceived risk of liability in disclosing data is a key barrier for the local municipalities and departments to engage actively with open public data.
In our paper “Decoupling Accountability and Liability”, published recently in Naveiñ Reet: Nordic Journal of Law and Social Research (PDF here), we explore this novel regulatory approach by looking into the recently announced Interim Measures for the Opening of Public Data in Shanghai and the context of their emergence. By unfolding the local regulators’ accounts of the development of the interim measures, we explore: how can interim regulatory measures reduce the perceived risk of liability among public bodies and contribute to accountability of open public data initiatives?
Our findings show that the adopted interim measures have managed to provide both clarity and flexibility to open public data entities, when it comes to opening their data. In particular, the measures institutionalized the roles and responsibilities of these entities by specifying the different categories in which they can be categorized and outlining clearly their specific duties and the circumstances under which they can incur liability. At the same time, due to their interim nature, the measures allowed for certain level of flexibility as they can be easily amended in case they are not optimal. This experimental approach towards regulating open data, which relies on interim, yet specific measures, reduces the legal uncertainty, which open public data encounter when opening their data sets. Thus, they potentially contribute to increased accountability.
In our paper, we also discuss the appropriate level to regulate open data initiatives, an issue which has implications for the ability of the legislators to achieve both, clarity and flexibility of the measures. While the majority of the measures on supra-national (e.g. European Union) or national level remain somehow general and lasting for the foreseeable future, we argue that they cannot substantially reduce the legal uncertainty experienced by public entities, which remain unwilling to participate fully in open data initiatives. In our research, we emphasize the importance of local legislative initiatives to achieve the necessary specificity of the measures, while also ensuring that they remain flexible enough.
The paper is available as a free PDF here.
Cancan Wang is an Assistant Professor at the Department of Business IT, IT University of Copenhagen, Denmark. She was trained in sociology, ethnology and information systems. Her current research interest lies in the sociomaterial development (e.g., governance, regulation, and organizational arrangements, etc.) of public digitalization (e.g., open data, artificial intelligence, social media, etc.). Feel free to contact her at email@example.com or over LinkedIn.
Kalina Staykova is an Assistant Professor at the Department of Digitalization, Copenhagen Business School, Denmark. She was trained in information systems, inter-national law and management. Her research investigates broad range of issues related to digital platforms (e.g., design, adoption, monetization, regulation, etc.) in various contexts (e.g., digital payments, e-commerce, open data, etc.). Contact her at firstname.lastname@example.org or find her on LinkedIn.