@misc{10481/105918,
year = {2025},
month = {8},
url = {https://hdl.handle.net/10481/105918},
abstract = {Public Data Ecosystems (PDEs) are increasingly viewed as dynamic socio-technical systems shaped by evolving interactions among actors, infrastructures, data types, and governance mechanisms. Yet, most existing research remains static or domain-specific, offering limited insight into the temporal and co-evolutionary dynamics of PDEs. To address this gap, this study adopts a theory-building approach to examine how PDEs evolve over time and to define a forward-looking research agenda. Drawing on empirical insights from five European countries, we investigate how key meta-characteristics and attributes of PDEs manifest, shift, and co-evolve in practice. Leveraging a recent multi-generational model as an analytical lens, we assess its alignment with real-world trajectories, identify overlooked and emerging features, and revise its structure accordingly. In doing so, we theorize PDE evolution  as a multi-generational process shaped by institutional, technological, and contextual dynamics. This results in a refined model that better captures the complexity and diversity of PDE development, particularly considering emerging technologies such as artificial intelligence (AI), generative AI, and large language models (LLMs) shaping the forward-looking PDE generation. Building on these insights, we propose a future research agenda comprising 17 directions organized around revised meta-characteristics. This agenda supports the development of sustainable, resilient, and intelligent PDEs. The study contributes to the theorization of PDEs by offering an empirically grounded, temporally aware, and actionable roadmap for future research and policy design.},
organization = {The authors gratefully acknowledge the following sources of financial support. This research was funded the Excellence project run at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic. It was also supported by the research grant “Opening the black-box of algorithm-mediated public governance. Artificial intelligence implications in governments, public services, and humans” (AI_PublicGov, PID2022-136283OB-I00), funded by the National Research Agency, Spanish Ministry of Science and Innovation, and the project C-SEJ-325-GR23, funded by the Regional Government of Andalusia and the University of Granada, Spain. Additional funding was provided by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia (contract no. 451-03-18/2025-03/200155), through the Faculty of Technical Sciences in Kosovska Mitrovica, University of Pristina.},
publisher = {Elsevier},
keywords = {artificial intelligence},
keywords = {data ecosystem evolution},
keywords = {research agenda},
keywords = {socio-technical system},
keywords = {public data ecosystem},
keywords = {public sector innovation},
title = {Theorizing the Evolution of Public Data Ecosystems: An Empirically Grounded Multi-Generational Model and Future Research Agenda},
doi = {10.1016/j.giq.2025.102062},
author = {Nikiforova, Anastasija and Lnenicka, Martin and Milic, Petar and Luterek, Mariusz and Rodríguez Bolívar, Manuel Pedro},
}