Our new paper, “Theorizing the evolution of public data ecosystems: An empirically grounded multi-generational model and future research agenda”, has been published in Government Information Quarterly. This publication marks the conclusion of a long-running research journey—one so rich that it produced four papers along the way—and brings together years of reflection on how public data systems emerge, evolve, and transform.
Several months ago, in my invited blogpost for Data Studies (“In Open Data We Trust? Busting the Myth, Rethinking Value in the Age of GenAI”), I reflected on the promises and limitations of open data. Despite its early optimism and democratic ideals, open data has produced uneven results in practice. This tension reinforced what I had been observing for years: open data alone is no longer sufficient. Instead, what increasingly matters is the broader, more adaptive configuration of Public Data Ecosystems (PDEs)—dynamic, evolving socio-technical systems shaped by institutions, technologies, infrastructures, actors, risks, and societal needs. That earlier blogpost unexpectedly provided the final spark of motivation to bring this paper across the finish line.
Why Public Data Ecosystems?
PDEs extend far beyond traditional open government data. They include geospatial data infrastructures, IoT-driven ecosystems, domain-specific environments, and federated data spaces with varying access models (see typology of PDEs in figure below and this piece). What binds them is not openness but their co-evolution—the way actors, data types, governance models, and technologies reshape each other over time.
This has become particularly salient with the rise of AI, generative AI, and large language models. These technologies challenge existing assumptions about data availability, quality, reuse, and governance. PDEs are no longer static infrastructures – they are living systems, with the above being now not only mere components but active actors who shape these systems.
In this study, we:
theorize PDEs as multi-generational, evolving socio-technical systems, shaped by institutional, technological, and contextual dynamics;
refine the Evolutionary Model of PDEs (EMPDE) using empirical evidence from five European countries;
introduce new attributes that capture overlooked dynamics and emerging realities;
describe the rise of a sixth, forward-looking generation propelled by emerging technologies—including AI, LLMs, and other data-driven innovations;
propose a research agenda with 17 directions to guide the development of sustainable, resilient, and intelligent PDEs.
Rather than validating the original EMPDE model that we proposed earlier (see this and this pieces), we treated it as a heuristic tool—an analytical lens—to explore how PDEs actually evolve in practice. This approach allowed us to identify theoretical gaps, generational ambiguities, and emerging patterns that refine the model’s structure. This helped us to reveal several important shifts:
PDE evolution is not strictly linear; some countries move fluidly across “generations”;
emerging technologies are reshaping governance logics faster than institutions can adapt;
new attributes—such as ecosystem intelligence, risk-mediated openness, or cross-domain interoperability—are now essential;
the sixth generation represents a paradigm shift, in which AI not only consumes data but co-determines which data becomes valuable, usable, and governable.
Understanding PDEs as evolving systems has implications for:
policy makers, who must govern increasingly complex data landscapes;
public sector organizations, whose operations increasingly depend on cross-domain data flows;
researchers, who need frameworks that capture temporal, socio-technical, and institutional dynamics;
technology developers, who must navigate the interplay between AI capabilities and data governance constraints.
The refined EMPDE model and the proposed research agenda aim to support these communities in building sustainable, resilient, and intelligent data ecosystems—ones capable of adapting to rapid technological and societal change.
This paper is the result of a our -now already long enough- collaboration with Martin Lněnička, Mariusz Luterek, Petar Milic, and Manuel Pedro Rodríguez Bolívar. Special thanks to Marijn Janssen, whose editorial guidance and sharp comments significantly improved the paper.
And sincere thanks to Aleksi Aaltonen and Marta Stelmaszak Rosa, whose invitation to write the Data Studies blogpost provided the unexpected inspiration to finalize this study.
If you’re interested in PDEs, data governance, AI, or socio-technical systems, I’d love to hear your thoughts. This area is evolving quickly—and so are the ecosystems we rely on.
And we are back with the new edition of Data for Policy 2025 Conference, preparation to which are in full swing! And as part of these preparations, we 📣 Call for Special Tracks for Data for Policy 2025 Europe Edition to be submitted by 11 December, 2024, with the conference itself to be held on 12-13 June, 2025, at Leiden University, The Hague, Netherlands!
This time, the Data for Policy 2025 conference will run under the “Twin Transitions in Data and Policy for a Sustainable and Inclusive Future”.
Amidst global challenges, the “twin transition”—encompassing digital and green transformations—has garnered significant attention for its potential to reshape industrial ecosystems and influence social inequalities. However, in the scientific community and policy arena questions have been raised on whether green and digital transitions are mutually compatible or whether one transition can reduce or cancel out the other. Furthermore, we see sustainability as an integrative perspective that includes environmental, social, economical and institutional sustainability.
Both public and private sectors are increasingly aligning their objectives towards digital innovation and sustainable practices 🌍. Governments are developing policies to guide these transitions, ensuring that technological advancements account for sustainability. Concurrently, substantial investments are being funneled into industries poised to drive this twin transition. Data lies at the heart of this transformation, empowering policymakers to monitor progress in real-time, identify emerging trends, and design impactful and targeted strategies. From driving down carbon emissions to closing the digital divide, data-driven insights offer the actionable intelligence needed to tackle complex challenges and pave the way toward a more equitable, sustainable future.
At this nexus, the theme of the European Data for Policy Conference is “Twin transitions in data and policy for a sustainable and inclusive future”, where we will delve into the implications of these transitions for governance, data usage, and policymaking
With CFP to be launched in a month, now, we – Sarah Giest, Bram Klievnik (both local chairs), Leid Zejnilovic, Laura Zoboli, Anastasija Nikiforova – invite proposals for Special Tracks in two categories:
Research/Policy/Practitioner Tracks: These tracks should address how digital and green initiatives work together to overcome global challenges. Proposals should align with the conference theme, “Twin Transitions in Data and Policy for a Sustainable and Inclusive Future”.
Policy/Practitioner Tracks: We invite proposals from those focused on policy and real-world applications, addressing the broader Data for Policy theme.
Proposers are encouraged to consider region-specific challenges alongside the conference theme, which offers a framework but is open to all relevant Data for Policy topics.
Accepted tracks will be part of the wider call for abstracts, full papers and panels, set to be released on 20 December, 2024, with Special Track chairs having the opportunity to propose an associated Special Collection in the Data & Policy journal published by Cambridge University Press & Assessment in due course.
26th Annual International Conference on Digital Government Research (dg.o2025)is coming with continuation of the track we launched the last time – “Sustainable Public and Open Data Ecosystems for inclusive and innovative government” track (chairs: Anastasija Nikiforova (University of Tartu, Estonia), Anthony Simonofski (Université de Namur ASBL, Belgium), Anneke Zuiderwijk (Delft University of Technology, the Netherlands) & Manuel Pedro Rodríguez Bolívar (University of Granada, Spain)).
Briefly about the track… Today, the goal of an actor-centric public data ecosystem that would be sufficiently sustainable, resilient and fair, is defined as an approach capable of representing and keeping in balance the data interests of all actors[1], to bring expected value (both economic, social and environment) became central for public data ecosystems and other types of data infrastructures and data spaces[2] that are based on the concept of openness and data sharing among stakeholders. Public data and open (government) data ecosystems are seen as a political and socio-economic phenomenon that promise to benefit the economy, and increase transparency, efficiency, and quality of public services, including the transformation of government data-driven actions, stimulate public sector innovations in various areas of public life and promote civic engagement[3][4][5]. Having collaborative governance models in place is one of the prerequisites for a resilient and value-adding ecosystem, of which stakeholders are an inevitable element, making it necessary to ensure those ecosystems are stakeholder-oriented. These models are expected to support stakeholders/actors, who, however, may have different characteristics (incl. (open) data literacy and digital literacy), needs / demands and expectations (public sector, private sector, business, citizen) for public value creation and co-creation. Understanding, designing, and maintaining such an ecosystem is further complicated by the fact that both data, service and process quality must be ensured and kept maintained with a limited understanding of how the above are expected to be ensured even alone.
Recent research found that concepts affecting and shaping the ecosystem are: 1) stakeholders / actors and their roles, 2) phases of the data lifecycle, in which a stakeholder participates in the ecosystem, 3) technical and technological infrastructure, 4) generic services and platforms, 5) human capacities and skills of both providers and consumers, 6) smart city domains (thematic categories) as the targeted areas for data reuse, 7) externalities affecting goals, policy, and resources, 8) level of (de)centralization of data sources – development, restrictions, 9) perception of importance and support from public officials, and 10) user interface, user experience, and usability[6]. Moreover, these ecosystems same as its components are (co-)evolving over time[7] due to both internal and external factors. The latter – external factors – include technological developments. As such, the rapid development of emerging technologies such as big data, artificial intelligence (AI) is seen as a new trigger for public and open data development (AI for open data and open data for AI), machine learning (ML), federated learning (FL), internet of things (IoT), metaverse etc. provides new opportunities to improve these ecosystems in a disrupt way to be useful for collaborative governance models. Also, the link between Open Data Ecosystems and sustainable development goals (SDG) seems to be more relevant nowadays in their way to build more democratic cities based on government transparency, citizen participation, and citizen cooperation. Finally, higher expectations, needs and demands of businesses and citizens, derived from the implementation of B2G, C2G models, that influence and shape the design and development of these data environments, as well as expected to be affected, e.g., B2G in relation to which European Commission is taking regulatory action and is preparing the Data Act to set the rules and conditions, thereby changing the current voluntary model to a more mandatory data sharing. Current research suggests that these topics are of great importance to governments, as well as businesses and citizens, whose efforts should complement each other in order to enable effective data reuse and value co-creation
As such, as public and open data ecosystems promise the transformation of government data-driven actions, the fostering of public sector innovations and the collaborative smartification of cities, society and life, triggering value-adding sustainable development goals-compliant smart living and Society 5.0. New research is needed to help public managers and politicians for (1) implementing emerging technologies and technological innovations, (2) improving the achievement of sustainable development goals for increasing transparency, participation, and cooperation, and (3) meeting the stakeholders’ expectations, needs, regulations and demands.
As such, this track welcomes contributions covering, but not limited to:
The concepts of theoretical approaches toward Public Data ecosystems, Open Data ecosystems, Data Spaces, and Data Marketplaces;
Infrastructures supporting Public and Open Data Ecosystems;
The role of emerging technologies in Public and Open Data ecosystems (incl. but not limited to AI, Generative AI, LLM, NLP, cloud computing, green computing, Metaverse etc.);
Data architectures and data governance mechanisms;
Institutional aspects of implementing sustainable Public and Open Data Ecosystems;
Other sustainability dimensions of Public and Open Data Ecosystems;
Stakeholder-centric dimensions of Public and Open Data Ecosystems;
Human-Computer Interaction between users and systems (platforms);
Case studies of Public and Open Data Ecosystems, incl. but not limited to Local Government Level Data Ecosystems, e.g., Smart Cities Data Ecosystems;
The impact of Public and Open Data Ecosystems on Individuals, Organizations and Society.
The track welcomes both contributions covering the current state-of-the-art of public data ecosystems (what components constitute them, what are the relationships between these components, what makes an ecosystem resilient and sustainable), incl. individual case studies reflecting best or bad practices, as well as those addressing how these ecosystems can be transformed into more sustainable ecosystems that will “fuel” or “smartify” society (Information Society aka Society 4.0 to Super Smart Society aka Society 5.0 transition), cities and various areas of life.
The track is very aligned with the conference theme of DGO 2025, namely: Digital government fostering social cohesion for reducing inequalities. As mentioned in the theme description, “It focuses on strong social bonds in civic society, with responsive democracy and impartial law enforcement aiming at collaboratively addressing latent social conflicts. It involves building shared values in communities facing common challenges in an attempt to reduce disparities by increasing citizens’ feeling of belonging to a community and their engagement.” Public and open data ecosystems can be considered as environments that contribute to the above. Open data is aimed at reducing inequalities, open platforms constitute environments where data providers and data users find each other and collaborate and co-create to develop services and products useful for society, i.e., addressing their needs and tackling challenges society faces. While digital technologies enable the development of public and open data ecosystems, the adoption of such ecosystems has been fragmented. For instance, Van Loenen et al. (2021)[8] found that open data ecosystems “often do not balance open data supply and demand, exclude specific user groups and domains, are linear, and lack skill-training” (p. 2), which reduces their value-generation and sustainability.
Is your research related to any of the above topics? Then do not wait – submit!
🗓️🗓️🗓️Important Dates:
January 24, 2025: Papers, workshops, tutorials, and panels are due March 26, 2025: Author notifications (papers, workshops, tutorials, panels)
[1] Calzati, S., & van Loenen, B. (2023). A fourth way to the digital transformation: The data republic as a fair data ecosystem. Data & Policy, 5, e21.
[2] Lnenicka, M., Nikiforova, A., Luterek, M., Milic, P., Rudmark, D., Neumaier, S., … & Rodríguez Bolívar, M. P. (2023). Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems. Available at SSRN 4831881.
[3] Nikiforova, A., Rizun, N., Ciesielska, M., Alexopoulos, C., Miletič, A.(2023). Towards High-Value Datasets determination for data-driven development: a systematic literature review. In: Lindgren,I., Csáki, C., Kalampokis, E., Janssen, M.,, Viale Pereira,G.,Virkar, S., Tambouris, E., Zuiderwijk, A.Electronic Government. EGOV 2023. Lecture Notes in Computer Science. Springer, Cham
[4] Kassen, M. (2020). Open data and its peers: understanding promising harbingers from Nordic Europe. Aslib Journal of Information Management, 72(5), 765-785.
[5] Santos-Hermosa, G., Quarati, A., Loría-Soriano, E., & Raffaghelli, J. E. (2023). Why Does Open Data Get Underused? A Focus on the Role of (Open) Data Literacy. In Data Cultures in Higher Education: Emergent Practices and the Challenge Ahead (pp. 145-177). Cham: Springer International Publishing.
[6] Lnenicka, M., Nikiforova, A., Luterek, M., Azeroual, O., Ukpabi, D., Valtenbergs, V., & Machova, R. (2022). Transparency of open data ecosystems in smart cities: Definition and assessment of the maturity of transparency in 22 smart cities. Sustainable Cities and Society, 82, 103906.
[7] Nikiforova, A., Lnenicka, M., Milić, P., Luterek, M., & Rodríguez Bolívar, M. P. (2024, August). From the evolution of public data ecosystems to the evolving horizons of the forward-looking intelligent public data ecosystem empowered by emerging technologies. In International Conference on Electronic Government (pp. 402-418). Cham: Springer Nature Switzerland.
[8] Loenen, B. van, Zuiderwijk, A., Vancauwenberghe, G., Lopez-Pellicer, F. J., Mulder, I., Alexopoulos, C., … & Flores, C. C. (2021). Towards value-creating and sustainable open data ecosystems: A comparative case study and a research agenda. JeDEM-eJournal of eDemocracy and Open Government, 13(2), 1-27.
This October, I had an opportunity to participate in the panel on Trust in AI that took place as part of Digital Life Norway conference organized by Centre for Digital Life Norway (Norwegian University of Science and Technology (NTNU)) that took place in a very peaceful Hurdal (Norway) 🇳🇴🇳🇴🇳🇴.
As part of this panel, together with M. Nicolas Cruz B. (KIWI-biolab), Korbinian Bösl (ELIXIR, both of us being also part of EOSC Association)), and Anamika Chatterjee (Norwegian University of Science and Technology (NTNU)), who masterly chaired this discussion, we discussed trust in AI and data (as an integral part of it), emphasizing the need for transparency, reproducibility, and responsibility in managing them.
What made this discussion to be rather insightful – for ourselves, and, hopefully, for the audience as well – is that each of us represented a distinct stage in the data lifecycle debated upon the aspect of trust and where concerns arise as data moves from the lab to inform AI tools [in biotechnology]. As such we: ✅highlighted the interconnectedness of human actors involved in data production, governance, and application; ✅highlighted the importance of proper documentation to make data usable and trustworthy, along with the need for transparency – not only for data but also for AI in general, incl. explainable AI; ✅discussed how responsibility becomes blurred as AI-driven methodologies become more prevalent, agreeing that responsibility for AI systems must be shared across teams. Lastly, despite being openness advocate, I used this opportunity to touch on the risks of open data, including the potential for misuse and ethical concerns, esp. when it comes to medical- and biotechnologies-related topics.
All in all, although rather short discussion with some more things we would love to cover but were forced to omit this time, but very lively and insightful. Sounds interesting? Watch the video, incl. keynote by Nico Cruz 👇.
And not of least interest was a diverse set of other events – keynotes, panels, posters etc. – takeaways from which to take back home (not really to home, as from the DNL, I went to the Estonian Open Data Forum, from which to ECAI, and then, finally back home to digest all the insights), where “Storytelling: is controversy good? How to pitch your research to a non-academic audience” by Kam Sripada and panel on supervision are probably the main things I take with me.
Many thanks go organizers for having me and the hospitality, where the later also goes to Hurdal 🇳🇴 in general, as we were lucky enough to have a very sunny weather, which made this very first trip to Norway – and, hopefully, not the last one – very pleasant!
This October, I had the distinct honor of participating in Estonia’s premier event on open data, the Open Data Forum (Avaandmete foorum), organized by the Ministry of Economic Affairs and Communications of Estonia, invited to talk about the role of academia and private sector in the open government data landscape. This annual gathering brings together industry experts, academic researchers, and government leaders to discuss key trends, achievements, and the future of open data in Estonia, along with highlighting the contributions coming from universities awarding the best dissertations developed by Estonian students. The latter made this event very special for me, as one of my students – Kevin Kliimask – was awarded for his outstanding bachelor’s thesis 🏆 🥇 🏅!
In his thesis –“Automated Tagging of Datasets to Improve Data Findability on Open Government Data Portals,” Kevin developed an LLM-powered interface to automate dataset tagging in both English and Estonian, thereby augmenting metadata preparation by data publishers and improving data findability on portals by users – as the practice shows their presence tend to be a challenge. E.g., our analysis conducted on the Estonian Open Data Portal, revealed that 11% datasets have no associated tags, while 26% had only one tag assigned to them, which underscores challenges in data findability and accessibility within the portal, which, according to the recent Open Data Maturity Report, is considered trend-setter. The developed solution was evaluated by users and their feedback was collected to define an agenda for future prototype improvements. The thesis has been already transformed into the scientific paper 👉 “TAGIFY: LLM-powered Tagging Interface for Improved Data Findability on OGD portals“ presented at the IEEE international conference (I posted on this earlier 👉 here).
As for my talk titled “Unlocking the Power of Open Data: The Role of Academia and the Private Sector in Building Inclusive and Sustainable Open Data Ecosystems,” I emphasized the need for a holistic approach to open data that transcends merely opening/publishing data, rather requiring adopting a systemic view that considers an open data initiative as an Open Data Ecosystem (also confirmed by Open Data Charter 👉here), as we deal not only with open data (availability), portal, stakeholders, actors, but also processes surrounding them, emerging technologies & different forms of intelligence, going beyond just Artificial Intelligence, whose role, however, is crucial (see our paper on the eight-fold role of AI in OGD).
As such, while discussing the main idea of the talk – the role of academia & the private sector in the ODE, which as per me is at least four-fold, namely – data consumers, data providers, contributors to ODE sustainability & myth busters on the global stage (assigning “Made in Estonia” tag to OGD in addition to the one we have for e-government), I also expanded the general mantra of “Data For AI” to “data for AI, AI for data, data not only for AI and not only AI for data”.
A big thank you to the organisers, who gathered so many speakers (Cybernetica, FinEst Centre for Smart Cities, Riigi Infosüsteemi Amet // Estonian Information System Authority (NCSC-EE), University of Tartu and many others) to discuss the highlights of today & tomorrow for Estonian Open Data and High-Value Datasets in particular as it was the main focus of the Forum – was happy to be part of these discussions!
Anastasija Nikiforova, PhD 