Parallel Session 13 – Opening Research Information
Date: Friday, 3 July 2026, from 09:00 to 10:30
Moderator: TBC
Location: R2
13.1) Monitoring Strategic Technologies Using Open Research Information
Presenter: Matthijs de Zwaan, Vrije Universiteit Amsterdam, The Netherlands
European and national policy frameworks addressing strategic autonomy and knowledge security, such as the EU Strategic Technologies for Europe Platform (STEP) and the Dutch National Technology Strategy (NTS), identify technologies that are expected to drive economic competitiveness and societal transitions. Monitoring progress in these areas informs funding and governance decisions, but the information used for this purpose often relies on proprietary data sources that limit transparency, reproducibility, and independent verification.
Our work presents a framework for profiling academic research in these strategic technologies using open research information. Developed in collaboration with Universiteiten van Nederland (the association of Dutch universities), the project examines the contribution of Dutch universities to the objectives of the NTS and demonstrates how research libraries can support policy monitoring using openly available metadata. This approach differs from previous approaches in two important ways. First, our approach is fully transparent. Second, it is relatively simple and flexible and can be quickly adapted to new developments in the technologies we are describing.
The framework is built on OpenAlex as the primary data source. A large language model is used to classify research outputs into the technology clusters defined in the NTS, enabling alignment between policy categories and scholarly research fields. We combine standard bibliometric indicators on research output and citation impact with a measure of relative specialisation, allowing institutional and national strengths to be assessed in an international context.
The results show that it is feasible to construct a transparent and reproducible evidence base for monitoring strategic technologies using open data and methods. The framework illustrates how research libraries can use their expertise in working with research data to offer strategic analytical support. As such, it provides a practical example of how open research information can be used to inform research assessment and policy discussions without dependence on proprietary systems.
13.2) Trajectory Modelling of OA Publishing Costs Using Open Research Information
Presenter: Cameron Neylon, Independent, Sweden
Understanding the full costs of scholarly publishing across national and regional systems remains a challenge. What information is available is generally limited and the best data is usually confidential and private. The argument for Open Research Information is that the benefits of sharing outweigh the risks. We sought to examine this by building a large scale model of costs and savings in the scholarly publishing system using public information.
Combining bibliographic resources including OpenAlex and OpenAIRE with cost information at the level of APCs (OpenAPC, DOAJ, and open datasets of archived list prices) and agreements (from full text agreements listed in ESAC) we can estimate the overall profile of OA publishing costs and use these to model the development of future costs under various sets of assumptions.
The cost model for a given institution, consortium or country starts with the overall output volume and the proportion of outputs in each Open Access category. Within each category the proportion of outputs with a corresponding author is estimated. This is then compared to the set of outputs that are known to have been covered within agreements. For each category of paid open access (hybrid and APC-gold) we estimate list price APCs. For those outputs within agreements we also calculate the average cost per output (separating hybrid and gold), taking into account ‘publish’ and ‘read’ parts of the agreement, where applicable.
Using this cost model, we then extrapolate to generate estimated future prices per output for each category (APC-gold, hybrid, within and outside agreements). These price estimates are then used to calculate the overall cost of each category in various scenarios. We use baseline estimates for subscription costs, andestimate current expenditure on repositories and diamond OA publishing venues as a baseline for infrastructure contributions.
Scenarios covered in the trajectory modelling can include increasing the number and coverage of R&P deals, paying APCs out of contract, switching to only full gold OA publishing deals, shifting focus to diamond OA and/or repository-based OA, as well as mixed scenarios.
The modelling approach can be validated by comparing data from open research information sources with data supplied by consortia directly. Consortial data can also be used to further refine the model, as these often include data that are not publicly available.
This includes data on articles published as part of publisher agreements, as well as additional financial information on publisher agreements (including on subscriptions) and investments in repositories, diamond OA publishing and (other) open infrastructures.
In this presentation, we will show how a national, regional and global model of publishing costs can be built using Open Research Information. Through two case studies, we will demonstrate the value of information shared by library consortia to this modelling approach, and encourage library consortia to make information on publishing costs information openly available.
13.3) Beyond Licences and APIs: A Human-Centred Decision Framework for Finance Data in Research Libraries
Presenter: Tsvetanka Slavcheva, Sofia University, Bulgaria
In today’s unpredictable environment, decisions about selecting materials in research libraries go far beyond issues of coverage and cost. These choices influence who gains access to knowledge, how reliably research can be replicated, and whether scholars can conduct their work with dignity and thoughtful support. The banking and finance sectors pose an especially complex challenge, given their rapidly evolving markets, multilayered regulations, and a patchwork of data sources that include proprietary databases, official statistics, academic indexes, and repositories.
This talk presents insights from a comprehensive scoping review of finance data sources conducted between 2019 and 2025 (with the latest update in September 2025). It introduces a human-centred framework to guide decisions in collection development and library service design. The review examines four types of sources: (1) global financial databases (like Bloomberg, Refinitiv, S&P Capital IQ, and FactSet); (2) official and regulatory statistics (such as those from the ECB, IMF, Eurostat, and national statistics agencies and central banks); (3) academic discovery platforms (including Scopus and Web of Science); and (4) repositories from institutions, nations, and central banks. The sources were evaluated through a mix of document analysis and comparative review, using weighted criteria like source authority, thematic and geographical scope, how often they’re updated, quality of data and metadata, discovery tools, and licensing terms.
Moving past just technical assessments, this framework also incorporates metrics rooted in care: the burden of ensuring reproducibility, the mental load required to use the data, the stress caused by restrictive licenses and use conditions, and the wider benefits to communities through open standards and machine-readable licenses. These care-based metrics are not arbitrary. They’re drawn from established research in reproducibility, human-computer interaction, care ethics, and open science, and have been translated into practical tools for library collection decisions. The findings highlight that while proprietary platforms are often timely and integrate well into workflows, they tend to obstruct transparency and reuse. Official statistics are authoritative but still struggle with integration across systems, and repositories bring valuable grey literature to light but remain poorly connected to broader systems. Ongoing gaps in FAIR data principles,especially regardingversioning, persistent IDs, and citation standards, continue to threaten research integrity.
The proposed framework brings together a scored evaluation rubric and a decision tree based on typical finance research scenarios. It helps libraries maintain a healthy balance between open and licensed resources, make hidden risks like vendor lock-in visible, and provide built-in support for user training and data literacy. Ultimately, it reimagines collection development as a form of scholarly care, blending human values with strong evidence to enhance equity, reproducibility, and researcher well-being.