CRIS2026: Papers with Abstracts

Abstract. National research information systems play an increasingly central role in supporting evidence-based research governance, yet the ways in which these systems ensure data quality, structure validation workflows, and apply research metrics vary considerably across countries. Ukraine’s URIS system and the Slovak national CRIS provide two distinct but complementary examples of how large-scale infrastructures can manage hundreds of thousands of research records while maintaining high standards of accuracy, transparency, and interoperability. In Ukraine, more than half a million submissions undergo a combined manual and automated validation process coordinated by the State Scientific and Technical Library of Ukraine, forming the backbone of national research assessment and reporting. Slovakia, meanwhile, has developed its own frameworks for quality control and verification, embedded in long-standing national evaluation practices and supported by established governance structures.
Examining these systems side by side offers an opportunity to understand not only their technical components, but also the governance models that define who is responsible for data curation, how competencies are distributed, and which mechanisms ensure accountability.
By bringing these elements together data quality practices, validation workflows, governance arrangements, and the responsible use of metrics this study aims to provide insights of practical value to the broader CRIS community. Understanding how national systems operate in different contexts can help inform the design of infrastructures that are robust, scalable, and aligned with FAIR and Open Science principles.

Abstract. This paper provides a comprehensive overview of current research information systems (CRIS) in France, examining their development, current configurations, and future prospects across research organizations, higher education institutions, and laboratories. Drawing on policy reports, institutional analyses, and recent initiatives, it highlights the fragmented and heterogeneous nature of existing systems, shaped by diverse governance models, technological choices, and organizational constraints. The paper analyses major national tools and projects - including Labintel, CapLab, CRISalid, and scanR - and situates them within broader international developments in research information management. Particular attention is paid to the growing role of persistent identifiers as a key lever for interoperability, data quality, and administrative simplification. The analysis also addresses structural challenges related to governance, sustainability, and user engagement, especially at the laboratory level. Finally, the paper identifies emerging opportunities linked to open science policies, funding mechanisms, international collaborations, and European university alliances, arguing that France’s future CRIS landscape is likely to remain decentralized but increasingly interconnected through shared standards and infrastructures.

Abstract. In 2025, the German federal state North Rhine-Westphalia (NRW) published its first State Research Report, jointly produced by the Ministry of Culture and Science and 32 higher-education institutions (14 universities, 18 universities of applied sciences). CRIS.NRW acted as data trustee. The report is aligned with the Core Data Set for Research (KDSF) standard, avoids inter-institutional rankings, and combines aggregated indicators (Part I) with institution-authored narratives in selected KDSF research fields (Part II). We processed 52 password-protected Excel files across 397 validated sheets and 734,328 rows spanning three reporting years. This extended abstract outlines governance and the trustee model (separation of duties, small-cell policies), pragmatic KDSF profiling, an auditable QA pipeline, a dual perspective on provider and trustee challenges, and an awards case vignette. We conclude with a concise blueprint for schema-based submissions, shared code lists, and an automation roadmap toward APIs and a public portal.

Abstract. The Norwegian Research Information Repository (NVA) is a national, open-source infrastructure for documenting current Norwegian research activities and results and underpins national reporting to the Norwegian Scientific Index (NVI). It is deployed as a service-oriented, serverless platform on AWS, comprising 225 microservices across 16 independent deployment groups, using a graph data model aligned with FAIR principles and persistent identifiers. Developed over seven years with more than 40 contributors and first launched in June 2020, NVA reached full national production scale in September 2025, serving 160+ research institutions, approximately 30,000 researchers — around 69% of all Norwegian academic researchers — and some 3,500 curators and administrators. The platform has enabled the Norwegian government to effectively mandate open access for publicly funded research and provides institutions with shared tools, workflows, and best practices for research documentation. The first complete national NVI reporting cycle was successfully completed in April 2026, marking the final milestone of the transition from a fragmented landscape of over 80 separate institutional repositories and a parallel CRIS system. The paper describes the historical context, development process, technical architecture, achieved results, lessons learned, and future work, offering practical guidance when developing national-scale research information infrastructures.

Abstract. This paper examines how systematic user involvement helped shape the design and development of the Norwegian Research Information Repository (NVA), a national infrastructure for open access and research information, which was developed as a project using an iterative and agile approach. An expansion of the scope introduced a higher degree of complexity than anticipated. This introduced challenges related to functional diversity and institutional heterogeneity that the project underestimated. Additionally, large volumes of feedback from the user community proved difficult to handle by the people involved in the design and development process. To address this, a tighter collaboration with internal experts on CRIS was established, and different forms for user participation were introduced. This helped identify key functional requirements, improve the user interface, and align workflows with existing research administration practices. The examination of the user involvement process resulted in five distinct recommendations for similar national projects: secure early but structured user representation, anchor work at both operational and strategic levels, involve CRIS experts from the outset, phase and prioritise user involvement, and communicate clearly about development processes and how user feedback will be handled.

Abstract. The objective of this article is to justify the introduction of the data steward role in Ukrainian universities to enhance research data management in alignment with European standards. The methodology involves conceptual analysis of institutional models across Europe, with attention to policy frameworks, training approaches, and stakeholder engagement. The findings reveal that while data stewardship is a well-established function in many EU countries, Ukraine lacks both regulatory support and institutional infrastructure to operationalize this role.
Nevertheless, embedding data stewards within research institutions can significantly improve data quality, research reproducibility, and compliance with international funders’ requirements.
The article concludes that Ukraine should initiate a phased strategy involving institutional audits, pilot training programs, regulatory frameworks, and international collaboration to establish data stewardship as a core element of national research policy and to ensure its integration into the European Research Area.

Abstract. Current Research Information Systems (CRIS) have become key infrastructures in universities and research organisations, increasingly shaping research evaluation, strategic decision-making, and resource allocation. Despite their growing influence, research has largely focused on technical and organisational aspects such as interoperability and data quality, while ethical considerations remain underexplored. This paper conceptualises CRIS as value-laden socio-technical systems that embed normative assumptions through data models, metrics, and governance mechanisms. Drawing on information ethics and ethics-by-design, it introduces the eFIS (Ethical Research Information Systems) framework to integrate ethical principles into CRIS design and use. The study is based on a qualitative case study of the HISinOne-RES implementation at the FernUniversität in Hagen (FeU), combining document analysis, system analysis, and semi-structured interviews. The findings reveal key ethical challenges, including metric bias, lack of transparency, accountability gaps, and data protection issues. In response, the eFIS framework proposes five core dimensions—transparency, fairness, data protection, accountability, and participation—and operationalises them through practical tools such as checklists, templates, and impact assessments. The paper contributes by positioning CRIS as ethical infrastructures and offering actionable guidance for their responsible implementation.

Abstract. For the academic and scientific community whose institutions have Current Research Information Systems (CRIS), it is essential that the scientific output deposited in the CRIS will be described responsibly and with quality, in accordance with best practices and the principles of Open Science. In the academic context, science is not limited to the stages of research or publication, but also encompasses the way information is organized, described, assessed, made available, reused, and preserved over time, tasks in which libraries play a central role.
High-quality and responsible metadata description – ensuring the integration of scientific content into reliable, coherent, transparent, and interoperable information systems, in line with the FAIR Principles – is fundamental for the academic and scientific assessment of researchers, particularly concerning the awarding of degrees, career progression, access to funding, performance evaluation, or personal and professional recognition by peers.
At Iscte – University Institute of Lisbon, the Library plays a key role in curating the metadata of the scientific output deposited in the institution’s CRIS, Ciência_Iscte, contributing to the improvement and enrichment of metadata and, by enabling integration with the institutional repository, ensuring the accessibility and visibility of Iscte’s scientific production and promoting the dissemination of knowledge to a wider audience.
This paper aims to present the curation work conducted by the Iscte Library in Ciência_Iscte and its integration with the institutional repository, through a set of qualitative and quantitative data that demonstrate the work developed in this context, during the period 2020–2025.

Abstract. The growing digitalization of research management has transformed the availability, quality, and interoperability of research information into a central strategic factor within contemporary science systems. Despite increasing demands, metadata workflows in many organizations remain highly manual and heterogeneous, relying heavily on individual interpretation and localized convention. Research in information science has long identified metadata quality as a persistent bottleneck in digital knowledge infrastructures. This challenge is exacerbated in the CRIS context, where metadata no longer serve merely descriptive purposes but underpin strategic decision-making, reporting to funders, international benchmarking, and institutional visibility.
Recent advances in large language models offer a new approach: the systematic use of prompt engineering to generate high-quality metadata through text-based instruction alone. Prompt engineering emerges as a scalable, transparent, and institutionally practical method for overcoming long-standing challenges in metadata workflows, improving the governance, interoperability, and strategic value of research information across the scholarly ecosystem. Building on this conceptual foundation, the paper focuses on concrete application scenarios and hands-on examples demonstrating how artificial intelligence and prompt engineering can be used to support the processing of research project metadata in CRIS environments.

Abstract. Current Research Information Systems (CRIS) have become essential tools for universities and research institutions to manage, analyze and disseminate information about research activities, outputs and collaborations. However, traditional CRIS platforms often operate retrospectively and rely on manual data retrieval, limiting their ability to provide dynamic, context-aware and predictive insights. Addressing these challenges, this study presents the development of an AI-enhanced Current Research Information System (AI-CRIS), named GCRIS AI, implemented for the İzmir Institute of Technology. The GCRIS AI module introduces a novel approach to research information management by integrating artificial intelligence capabilities directly into the CRIS environment. Its primary component is a multilingual chatbot, which serves as an intelligent assistant for researchers, administrators and institutional leadership. The chatbot leverages natural language processing (NLP) and semantic understanding to interpret user queries, retrieve relevant information from the institutional GCRIS database enriched with external sources such as ORCID and Scopus and provide precise, contextual and actionable responses. By providing multilingual, contextual and predictive access to research data, the platform enhances the efficiency, transparency and strategic value of CRIS infrastructures. The pilot demonstrates that AI-enhanced CRIS platforms can bridge the gap between complex data infrastructures and end-user needs, fostering adoption and satisfaction among diverse stakeholders.

Abstract. Current Research Information Systems (CRIS) have become indispensable infrastructures for documenting publications, projects, funding, patents, and collaborations. Yet many institutional CRIS implementations remain primarily retrospective, offering descriptive views of past activity rather than anticipatory intelligence for future-oriented decision-making. This paper conceptualizes a modular Artificial Intelligence (AI) component for HISinOne RES and positions FernUniversität in Hagen (FeU) as the pilot setting for its design and subsequent implementation. The proposed module combines semantic enrichment, predictive analytics, collaboration recommendation, and explainable decision support within the existing CRIS environment. Rather than replacing the system, the concept introduces an integrative AI layer that preserves governance, data stewardship, and established workflows. Methodologically, the paper develops a design-oriented framework that brings together natural language processing, machine learning, network analytics, explainable AI, and participatory co-design. We discuss the functional architecture, the underlying governance requirements, and a roadmap from conceptualization to pilot deployment. The paper argues that AI-enhanced CRIS can evolve from passive repositories into dynamic, intelligence-driven infrastructures for university research management, provided that transparency, privacy, and user trust are embedded from the outset.

Abstract. Current Research Information Systems (CRIS) constitute a central infrastructure for managing, analyzing, and strategically steering research activities in universities, non-university research institutions, and research policy organizations. They aggregate data on projects, publications, funding, collaborations, patents, research data, as well as legal and organizational frameworks. With the increasing importance of Open Science, Responsible Research and Innovation (RRI), diversity, and regulatory requirements, there is a growing need for tools that not only evaluate past policies retrospectively but also simulate the social, legal, and institutional impacts of research policies in a forward-looking manner.
This contribution investigates the use of predictive AI models to develop socially-aware and evidence-based research policy within CRIS systems. Predictive AI serves not only to forecast future research developments but also as a tool to simulate complex socio-technical interactions where policy decisions, scientific practices, legal frameworks, and societal expectations intersect. The aim is to enable decision-makers to compare different policy scenarios, anticipate potential impacts, and make strategic decisions based on solid evidence.

Abstract. Current Research Information Systems (CRIS) are increasingly called upon to represent dynamic, real-time, and embodied research processes, a challenge that conventional architectures are ill-equipped to meet. This paper proposes Cyberphysical Intelligence (CPS-I) as a novel CRIS infrastructure paradigm, grounded in the ongoing CIINEF initiative at the Institut national de psychiatrie légale Philippe-Pinel (INPLPP) in Montreal, Canada. CPS-I integrates extended reality (XR) environments, multimodal biometric sensing, AI-driven classification, and digital twin modeling into a unified system that simultaneously supports adaptive forensic psychiatric care and generates structured, research-grade metadata. We describe the CPS-I architecture, its alignment with CERIF entities, FAIR principles, and the Barcelona Declaration on Open Research Information, and demonstrate how governance mechanisms, informed by Privacy by Design, data governance frameworks, and the EU AI Act, enable selective but principled interoperability in a high-security, legally constrained clinical context. The resulting model constitutes a transferable template for sensitive CRIS implementations across healthcare and public safety domains, and positions CRIS as an active epistemic infrastructure rather than a passive registry.

Abstract. Subject classification of publications, projects and other entities is ubiquitous in CRIS systems.
This project arose from practical considerations: how could we easily use AI to facilitate the cris administrator's work? This led to an application that can be deployed in various settings: given a brief textual description (e.g., a title and/or abstract of a publication), the application can generate one or more proposals for subject cataloging.
This can be implemented directly in various settings and for different types of classifications. Given sufficient training material, the application can be used with any classification system.
The aim of this article is to demonstrate that the open-source project Highlites is a useful tool for calculating usable classification proposals using one's own limited resources, and in a sufficiently short time.

Abstract. Antarctic research relies fundamentally on the continuous accumulation, preservation, and interpretation of diverse scientific data. These datasets ranging from long-term meteorological observations and cryospheric measurements to biological monitoring, geophysical surveys, and environmental assessments form the empirical foundation upon which present understanding and future projections of Antarctic systems depend. In Ukraine, the state institution National Antarctic Scientific Center (NASC) plays a central role in ensuring that such information is systematically collected, curated, and made accessible to the research community. As the operator of Ukraine’s long-standing Antarctic programme and station, NASC is responsible not only for generating new data but also for maintaining the scientific integrity of its program over decades.
The aim of this paper is to articulate the conceptual principles and practical considerations that should guide NASC in adopting such standards, identifiers, and open-science infrastructures. By outlining a cohesive vision for data interoperability and long-term stewardship, the article seeks to contribute to establishing a sustainable, globally aligned framework that will enhance the resilience, accessibility, and scientific value of Ukraine’s Antarctic research outputs.

Abstract. This paper presents the evolution of Open Science practices at Iscte – Instituto Universitário de Lisboa, documenting the transition from an established Open Access framework to a comprehensive, institution-wide approach encompassing research data management, interoperable infrastructures, and research assessment reform. We describe the design and implementation of an integrated system landscape connecting Zenodo, the institutional Current Research Information System (CRIS), and the Institutional Repository, demonstrating how this architecture ensures FAIR compliance while maintaining interoperability with national and international infrastructures such as RCAAP and OpenAIRE. Our findings suggest that the CRIS, through the project page, serves not merely as an administrative tool but as a strategic instrument for aggregating research outputs and supporting responsible research assessment.

Abstract. The FAIR (Findability, Accessibility, Interoperability and Reusability) principles emphasise making research outputs machine-actionable and consistently maintained. This paper proposes applying Continuous Integration/Continuous Deployment (CI/CD) practices to FAIR metadata publishing by leveraging GitHub Actions (GHA) as the automation backbone. Machine-actionable Data Management Plans (maDMPs) conforming to the RDA Common Standard serve as the source of truth for dataset metadata, automatically validated against institutional quality policies and deployed to external FAIR repositories such as Zenodo and Dataverse upon each versioned release. The specific contribution is an organisational automation pattern that treats metadata publication as a software release process and positions validated GitHub repositories as a harvestable upstream layer for institutional CRIS systems. A proof-of-concept prototype shows the approach has a low technical entry barrier, provides full auditability through workflow execution logs, and enforces consistent metadata quality across all published datasets.

Abstract. Responsible research evaluation increasingly requires transparent, interoperable data infrastructures to track funding through to outputs and be able to recognise a diversity of contributions. The Crossref Grant Linking System (GLS) addresses this gap by enabling funders to register open metadata for grants using Crossref grant DOIs. With more than 200,000 grant records from almost 50 funders, GLS integrates with Current Research Information Systems (CRIS) to reduce manual data entry, improve attribution accuracy, and support responsible assessment practices aligned with CoARA and the Barcelona Declaration. Evidence from early adopters, including FCT Portugal, demonstrates GLS's potential to strengthen national and institutional research evaluation through complete, high-quality, openly available funding metadata.

Abstract. Institutional Current Research Information Systems (CRIS) increasingly need reliable, affordable data on the scientific output of their institution and on the citations that output receives.
OpenAlex, a fully open and freely accessible scholarly index launched in 2022, is a compelling candidate to complement subscription databases such as Web of Science (WoS) and Scopus for these purposes. We report a case study at the Czech Technical University in Prague (CTU), whose in-house CRIS (V3S) is used as a curated baseline. We describe how OpenAlex was integrated with V3S through the institution's ROR identifier and a DOI-based matching procedure, and we measure publication coverage over the period 1996–2025 together with the citations recorded against the institution's outputs. We find that OpenAlex matches 93% of the CTU outputs that carry a DOI, that for recent DOI-bearing output its coverage is competitive with the subscription databases, and that it contributes a substantial number of citations not seen in WoS or Scopus (raising the count of distinct citations to CTU output by about 21%). At the same time, problems appear beneath the surface: aggregate figures that are internally inconsistent, and individual citation counts that are grossly inflated; and even among the outputs all three databases index, none holds the whole citation record. OpenAlex is a highly valuable and freely available research information infrastructure. Institutions that get their DOIs right can expect good publication coverage, which a curated CRIS can confirm against their own records. OpenAlex's citation counts, however, should be treated with caution, and a CRIS cannot validate them on its own.

Abstract. Maintaining researcher profiles across both institutional CRIS systems and national CV platforms creates redundant data entry and metadata inconsistencies. This paper presents a researcher-centric, consent-based integration between Iscte – University Institute of Lisbon's institutional CRIS, Ciência-Iscte, and Portugal's national CV platform, CIÊNCIAVITAE. Unlike automated synchronization approaches, the mechanism places the researcher in full control: synchronization occurs only through explicit researcher action, following an identifier-based matching and validation process. Building on prior work that relied on ORCID as an intermediary data hub, the current approach establishes a direct connection between the two systems, thereby extending the scope of synchronization from articles to a significantly broader set of entity types, including proceedings, books and chapters, datasets, software, preprints, supervision, teaching, peer review, outreach, affiliations, projects, and funding. The paper describes the architecture, including the onboarding, reconciliation, and validation processes, and presents a cost-benefit analysis based on the institution's 203,756 records across 4,625 researchers. The simulation estimates a time saving of approximately two hours per researcher per synchronization cycle and a benefit-cost ratio of 27:1 relative to the development investment.

Abstract. A national CRIS alone can be used for many bibliometric analyses but comes with natural limitations, especially citation-based analyses. However, a combination of a national CRIS and a bibliometric database like OpenAlex can utilize the best of both worlds; the accuracy on affiliation data in a CRIS and citation-data from a bibliometric source. This has been piloted in Norway, and an integration between the two systems show a big potential for wider application and more accurate results, all in the spirit of open science and the Barcelona-declaration.

Abstract. In January 2026 the Vietsch Foundation awarded a project to euroCRIS, 4Science and the Technical University of Hamburg to expand the DSpace-CRIS data model so that it becomes possible to add instruments and facilities to the snapshot for the institutional research activity. The project plan includes the modelling of this new CERIF research entity by euroCRIS on the basis of the work done by the RDA PIDINST WG, its implementation in the DSpace-CRIS version under development by 4Science and its real-life testing by the TUHH via their DSpace-CRIS-based institutional CRIS TORE.
This talk will summarise the project achievements and the lessons learned at the time the presentation gets delivered. The talk will raise awareness of this new DSpace-CRIS functionality and of the progress on its application at the TORE institutional CRIS so that other institutions using this software solution may become familiar with the metadata set used to describe these objects and the links that can be established to other entities already in the system. This development is particularly relevant in the light of the recently announced merger of DSpace and DSpace-CRIS, meaning that this functionality will soon be available for any institution currently operating a DSpace-based institutional repository.

Abstract. Research information systems (CRIS) and scholarly knowledge graphs (SKGs) are core components of modern research infrastructures. Numerous initiatives at institutional, national, and international levels support Open Science by exposing structured scholarly metadata. It includes institutional CRIS platforms, aggregator services such as OpenAIRE Graph, and OpenCitations, etc. Although many of these systems rely on graph-based representations, practical interoperability between them remains limited. Data exchange is often based on heterogeneous APIs, proprietary schemas, or only partially aligned semantic models, which leads to fragmentation and duplicated effort.
This lack of interoperability particularly affects CRIS platforms, which are expected to exchange semantically rich and provenance-aware data with aggregators and European-level infrastructures. The Scientific Knowledge Graph Interoperability Framework (SKG-IF) addresses these challenges by defining a common conceptual model and standardized, API-based access to scholarly knowledge graph data. Its data model reuses established ontologies, notably the Semantic Publishing and Referencing (SPAR) Ontologies (Peroni & Shotton, 2018) and the Provenance Ontology PROV-O (Lebo et al., 2013). Aligning CRIS platforms with SKG-IF enables institutional systems to function as interoperable components of a distributed network of scholarly knowledge graphs, reducing duplication of effort and improving reuse across infrastructures (Aryani et al., 2020). However, production-level implementations of SKG-IF within operational CRIS platforms have so far been limited.
This paper presents the design and deployment of a full SKG-IF integration in TeslaRIS, an open-source CRIS developed and used at the University of Novi Sad, and evaluates its contribution to improving institutional interoperability.

Abstract. OSIRIS is an open-source Current Research Information System (CRIS) created to support research organisations whose activities include more than traditional publication outputs, e.g. conference posters, events or teaching. Its core mission is to offer a configurable, sustainable, and highly adaptable alternative to conventional CRIS solutions that are frequently designed around the needs of universities or institutes. Scientific consortia and distributed infrastructures often produce software releases, datasets, workflows, training events, and community-building activities that do not fit neatly into rigid, publication-centric systems. OSIRIS was developed precisely to address challenges like this and was successfully implemented at several scientific institutes in Germany. The German Network for Bioinformatics Infrastructure (de.NBI) provides an ideal example of a modern, distributed research environment where OSIRIS can unfold its full potential. As a nation-wide consortium that coordinates bioinformatics services across eight service centres including 24 institutes, de.NBI requires a CRIS that can adequately capture the diversity of its scientific, technical, and community-oriented contributions. The deployment of OSIRIS within de.NBI demonstrates how a flexible and open-source system can empower a large infrastructure to communicate its outputs effectively, reduce reporting burdens, and improve internal communication and cooperation. This contribution presents OSIRIS through its system perspective and highlights the lessons learned from its adoption in the de.NBI network.

Abstract. Croatian Research Information System (CroRIS) contains complete, comprehensive, and reliable data related to the system of science and higher education in the Republic of Croatia. It unifies standardized data on Croatian scientific activity – from institutions, projects and researchers to publications, equipment, services and patents – making them publicly available in a single system, thereby increasing the visibility and transparency of research in Croatia. One of the CroRIS modules that promotes open science is Equipment and Services. This presentation focuses on the equipment sub-unit of that module, which contains metadata on scientific equipment located at scientific, research, and higher education institutions in the Republic of Croatia. The availability of equipment information supports more efficient use of existing equipment, justifies its acquisition, and encourages cooperation among research institutions, researchers, and between science and industry. Equipment data were migrated to the CroRIS database from the former Šestar database. The presentation describes the technical characteristics of the system, the migration process, the metadata used to describe equipment, data management practices, the use of equipment data for official purposes by different types of CroRIS users and stakeholders, and interoperability possibilities.

Abstract. Prizes, awards and honours are essential parts of the scientific reputation system and evidence of scientific expertise and success. They are integral components of rankings like the Shanghai Ranking and subject to science studies, research reporting and institutional research information management. In its current release, CERIF considers prizes and awards with a specific entity (cfPrize). Notwithstanding, there is a lack of systematic data and data standards for prizes and prize awardings on the international and national levels which might hamper the systematic integration of such information in Current Research Information Systems – CRIS. In Germany, the Commission for Research Information in Germany that is in charge of maintaining the KDSF standard (formerly known as Kerndatensatz Forschung), the German research information standard and blueprint for research information systems, recently published a new and freely accessible data service: the Open Registry for Awards and Prizes (ORAP) provides curated lists of prizes and awards along with relevant metadata. In this paper, we describe the background and key aspects of this new master data service. Next, we present the current data model for information about prizes and prize awardings at the University of Münster, discuss design rationales and decisions as well as the planned integration of ORAP data in the local CRIS. The paper concludes with a summary of findings and an outlook.

Abstract. Scientific instruments remain insufficiently represented as interoperable metadata entities within current CRIS implementations. This gap is particularly critical in conflict-affected research environments, where structured metadata is required not only for infrastructure visibility but also for damage assessment, recovery planning, and preservation of scientific capacity. Since the full-scale Russian invasion of February 2022, approximately 35% of Ukrainian research infrastructure has been damaged or destroyed, including 251 units of scientific equipment. This paper presents results from an ongoing project investigating metadata requirements for scientific instruments within the Ukrainian research information ecosystem. Drawing on policy analysis, stakeholder requirements, and comparative assessment of CERIF, MERIL, PIDINST, OpenAIRE, and B2INST, the study identifies two systematic gaps: the absence of recovery-oriented metadata support across all examined systems, and insufficient instrument-level CRIS integration within URIS. In response, the project outlines a FAIR-aligned, CERIF-compatible conceptual framework representing scientific instruments as first-class CRIS entities and proposes a recovery-oriented metadata layer comprising six structured dimensions, operational status, damage classification, relocation history, software dependencies, recovery priority, and knowledge preservation. The framework will be empirically validated through a structured pilot implementation involving 60–100 instrument records from Ukrainian research institutions, planned for 2027.

Abstract. European research infrastructures increasingly emphasize cross-institutional knowledge graphs, linked open data, and interoperability across national and disciplinary boundaries. This paper highlights gaps in and contributions to the research knowledge graph (RKG) integration in Europe, focusing on the role of institutional knowledge graphs (IRKG) as central hubs in a vertically integrated ecosystem. The findings underscore the need for widespread OpenAIRE compliance and open infrastructure to build a trustworthy, reusable research information commons across Europe, and the role that knowledge-graph-based open-source research information systems like VIVO can play in this.