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This study advances a reconceptualization of data and information which overcomes normative understandings often contained in data policies at national and international levels. This study aims to propose a conceptual framework that moves beyond subject- and collective-centric normative understandings.

To do so, this study discusses the European Union (EU) and China’s approaches to data-driven technologies highlighting their similarities and differences when it comes to the vision underpinning how tech innovation is shaped.

Regardless of the different attention to the subject (the EU) and the collective (China), the normative understandings of technology by both actors remain trapped into a positivist approach that overlooks all that is not and cannot be turned into data, thus hindering the elaboration of a more holistic ecological thinking merging humans and technologies.

Revising the philosophical and political debate on data and data-driven technologies, a third way is elaborated, i.e. federated data as commons. This third way puts the subject as part by default of a collective at the centre of discussion. This framing can serve as the basis for elaborating sociotechnical alternatives when it comes to define and regulate the mash-up of humans and technology.

This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle, lacking the luxury of centralized database administration, database schemes, shared attributes, vocabulary, structure and semantics. The existing dataset catalogs provide basic search functionality relying on keyword search in brief, incomplete or misleading textual metadata attached to the datasets. The search results are thus often insufficient. However, there exist many ways of improving the dataset discovery by employing content-based retrieval, machine learning tools, third-party (external) knowledge bases, countless feature extraction methods and description models and so forth.

In this paper, the authors propose a modular framework for rapid experimentation with methods for similarity-based dataset discovery. The framework consists of an extensible catalog of components prepared to form custom pipelines for dataset representation and discovery.

The study proposes several proof-of-concept pipelines including experimental evaluation, which showcase the usage of the framework.

To the best of authors’ knowledge, there is no similar formal framework for experimentation with various similarity methods in the context of dataset discovery. The framework has the ambition to establish a platform for reproducible and comparable research in the area of dataset discovery. The prototype implementation of the framework is available on GitHub.

The purpose of this study is to explore and theorize on balancing practices (BP) for digital ambidexterity in the public sector.

The research is designed as an interpretative case study of a large Swedish authority, involving data collection in the form of interviews and internal documents. The method of analysis involves both theorizing on the findings from a previous framework for digital innovation and deriving design implications for ambidextrous governance.

The findings show that all identified BP except one (shadow innovation) is directed toward an increased emphasis on efficiency (exploitation) rather than innovation (exploration). With the increased demand for innovation capabilities in the public sector, this is identified as a problem.

The limitations identified are related to the choice in the method of an interpretative case study, with issues of transferability and empirical generalizability as the main concerns. The implications for research are related to a need for additional studies into the enactment of digital ambidexterity, where the findings offer insight and inspiration for continued research.

The study shows that managers and executives involved in the design and imposition of governance within the public sector need to take the design recommendations for digital ambidexterity into consideration.

The study offers two main implications for practice. First, policymakers need to take the conceptual distinction of efficiency and innovation into account when designing policies for the digital government. Second, existing funding practices need to be re-designed to better facilitate innovation.

This is the first study directed toward enhancing the insight into BP for digital ambidexterity in the public sector. The study has so far resulted in both a localized shift in policy and new directions for research. With the public sector facing needs for increased innovation capabilities, the study offers a first step toward understanding how this is currently counteracted through governance design.

This article examines how responsibility and strategy can and should be connected in a business organization.

The article offers a review of the field by mapping previous studies according to their strategy and responsibility orientations and, consequently, identifies the classic perspective, as well as the major deficiencies and prevailing research gaps in the literature.

The article contributes to the field of strategic corporate responsibility by reframing the field with a contender perspective that challenges the classic view of strategy and responsibility amalgamation. Together, the classic and the contender perspectives are synthesized to form an integrative perspective that is more holistic than those currently available.

The article ends by calling for a reimagining of the relationship between corporate responsibility and strategy to find promising future research avenues and effective business practices suitable to meet the challenges of the twenty-first century.