In this paper, we present a domain-independent ontology extension workflow supported by LLMs. Ontology Engineering (OE) is a complex field that requires combining technical skills with domain expertise across multiple disciplines. Despite numerous attempts at automation, most of the processes are still manual. Different ontology engineering methodologies coexist, but none is a standard. These challenges, together with the lack of highly skilled workers in the sector, increase the entry barriers to the field. In parallel, Large Language Models (LLMs) are becoming prominent in ontology development due to their natural language processing and coding capabilities and their reportedly emergent abilities. In this paper, we focus on human-LLM collaboration for ontology extension. Following a Design Science Research approach, we interviewed 11 experts and modeled the current process of ontology extension to disclose its main issues. We analyzed the concerns and opportunities perceived by ontology engineers for using LLMs. Based on our insights and previous work, we designed a process framework for ontology extension that combines human expertise with LLMs capabilities, providing customizable prompt templates, OE tools, and guidelines. We tested our methodology with an existing greenhouse ontology using GPT-4o. Finally, we qualitatively evaluated the results against a manually crafted extension we use as our gold standard. The results show that the proposed approach holds the potential to (1) get inspiration for adding new entities, (2) deal with complex syntax definitions and repetitive tasks, and (3) verify whether the extended ontology conforms to the requirements and competency questions.

Cross-border eCommerce flows from non-EU countries with direct product delivery to consumers in the European Union have been rapidly growing. Whereas monitoring eCommerce flows for aspects such as Value- Added Tax (VAT), and safety and security already is a high priority, the increasing volumes bring new concerns. Such concerns include how to ensure that the products are sustainably produced and how to ensure a level playing field with products that are produced in the EU or imported via other modes of transport that are subject to more thorough checks at the border. These challenges have become new priorities in EU policy documents. Currently, authorities receive limited information related to eCommerce goods (particularly the low-value consignments that are exempted from duties), which hampers their risk assessment. Recently, Digital Product Passports (DPPs) have been introduced in legislation as a tool to inform consumers, recyclers, and market surveillance authorities about the material and manufacturing aspects of products. These DPPs promise to contain rich data that can be used to enhance both the monitoring and the customs risk assessment of cross-border eCommerce flows. To assess the exact potential and added value of DPPs, we analyze international eCommerce flows in the context of the EU-funded project PARSEC. We identify potential areas where DPPs can be relevant for eCommerce monitoring and risk assessment and present follow-up research directions on this topic.

As interest in circular economy governance grows, effective policymaking requires the creation and continuous monitoring of circular policies. In response, governments worldwide are seeking data and developing indicators to monitor and report progress within their jurisdictions. In recent years, this has led to a proliferation of monitoring frameworks at national, regional, and city levels. Nevertheless, existing research has yet to sufficiently address what types of information are essential for effective CE policymaking, how policymakers and enforcement agencies can access relevant data sources, and how information systems can support policymaking processes. This participatory workshop presents ongoing research on a conceptual framework that identifies key data attributes, information types, and digital infrastructures needed for CE policymaking. It aims to bring together researchers and policymakers working in open data, sustainability, smart cities, and evidence-based governance to discuss challenges, share best practices and build capacity through dialogue with fellow researchers and policymakers.

The EU Green Deal and the ensuing policies and regulations to stimulate the transition toward a circular economy pose challenges to policymakers and authorities. Taking planetary boundaries into account is a nascent topic on all regulatory levels, and data-driven policymaking and its implementation require the collection and access to new types of data in all policy-making phases, from agenda-setting to policy formulation, implementation, and evaluation. Extant studies into data-driven policymaking have not yet addressed which information types are needed and how policymakers and enforcement agencies can gain access to data sources, whereas the urgency to prepare for this is high. We use the lens of the policy cycles to assess the required data. In three typical cases, we explore the data sources at different policy levels of monitoring to develop a conceptual framework of data attributes to inform policymakers. We position that the extant data used in the policy phases for the transition to the circular economy are different from the familiar data that public administrations use in their respective domains. Our conceptual framework provides an initial overview of new types of data and potential shared use among the policy phases to support policymakers and enforcement agencies to timely prepare for access to the relevant data and data sources. We recommend the creation of data ecosystems for public administrations, the adoption of new capabilities for CE literacy, exploring the added value of Digital Product Passports, and AI-based tools and mechanisms to handle large volumes of data to structure messy data.

To facilitate the transition toward a circular economy (CE), EU policymakers are drafting new policies and legislations at a high speed. This affects a wide set of sectors and leads to legislative complexity. At the same time, the legislative developments requiring Digital Product Passports (DPPs) offer opportunities for governments to tap into a rich set of business supply chain data for CE and sustainability monitoring. Nevertheless, the diversity of these legislative initiatives leads to complexity for governments on what needs to be monitored. There is a need to reduce legislative complexity, to have a more clear view on what governments need to monitor, which in turn would provide more clarity on the types of business data from the Digital Product Passports and digital infrastructures governments may need to access for CE and sustainability monitoring purposes. One approach to reduce the legislative complexity is to have a framework of high-level concepts for CE and sustainability monitoring. The question, however, is how to arrive at such a framework of high-level concepts. In this paper, we explore the potential of the concepts found in the UN Recommendation 46 (initially developed for the traceability of textiles), to serve as a basis for a generic framework of high-level concepts for CE and sustainability monitoring. We examine the suitability by applying the concepts from UN Recommendation 46 to a variety of legislations beyond textiles. Our analysis suggests that the framework has the potential to serve as a high-level framework of CE and sustainability monitoring concepts across sectors, and we identify several areas for further research.

Circular economy (CE) and sustainability are high on the political agenda of governments nationally and internationally. We see different regulatory developments where governments aim to put stricter rules and requirements towards businesses to ensure the transition toward a more circular and sustainable future. The use of digital infrastructures, including transparency systems and digital product passports is starting to play a vital role in supporting governments in their CE monitoring efforts. Yet there are challenges to be overcome. Many government procedures are set up in laying out very detailed requirements about what one government agency can do in a singular phase of the circular process (e.g., customs performing specific checks at the border) or a single Member State (e.g., organizing Extended Producer Responsibility in a specific country). While these efforts are valuable building stones towards CE monitoring, they are fragmented, and blank spots in CE monitoring occur when borders are crossed, and another country needs to take over the CE monitoring tasks. As for circularity, even if many efforts are spent by a single government agency or a single country, all these efforts may be in vain if the proper CE monitoring of the next step is not secured. While earlier research identified this problem, there is still limited understanding of the problem itself and directions to address it systematically. In this paper, following up on earlier research and with insights gained from an EU project on CE monitoring, we shed further light on the problem. More specifically we conceptualize CE monitoring by putting the CE flows at the center and exploring deficiencies for governments and businesses to safeguard the monitoring of CE flows. We examine two routes that can be followed to ensure continued CE monitoring when borders are crossed, namely the government route, as well as the business route (enabled by traceability systems and in-control mechanisms of businesses). We discuss the need for a global governance layer that can facilitate both routes and propose further directions to advance CE monitoring by taking a global perspective.

Monitoring the circular economy (CE) transition requires data sharing and collaboration between public and private actors. However, businesses are reluctant to share data with authorities for monitoring purposes due to fear of losing control over sensitive data. The emerging technology Multi-Party Computation (MPC), which enables collaborative data analysis while maintaining data control, could address barriers in business-to-government (B2G) data sharing and collaboration. This ongoing research aims to explore the potential of MPC in facilitating B2G data sharing and collaboration for CE monitoring under the conditions of inter-organizational trust and data control. Drawing on a B2G data sharing framework, our initial findings suggest that MPC can benefit authorities in accessing sensitive business data, while businesses can benefit from controlling shared data for compliance reporting. As MPC can be deployed in various architectures, the next research steps are to examine links between variants of MPC architectures and different data-sharing solutions.

The AI Act represents a significant legislative effort by the European Union to govern the use of AI systems according to different risk-related classes, linking varying degrees of compliance obligations to the system's classification. However, it is often critiqued due to the lack of general public comprehension and effectiveness regarding the classification of AI systems to the corresponding risk classes. To mitigate those shortcomings, we propose a Decision-Tree-based framework aimed at increasing robustness, legal compliance and classification clarity with the Regulation. Quantitative evaluation shows that our framework is especially useful to individuals without a legal background, allowing them to improve considerably the accuracy and significantly reduce the time of case classification.