Conference Agenda
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12 SES 12 A JS: Research Workshop: Open Data and Organizations
Research Workshop
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12. Open Research in Education
Research Workshop Open Data and Organizations 1: University Koblenz, Germany; 2: IQS – Institut des Bundes für Qualitätssicherung im österreichischen Schulwesen; 3: University of Gothenburg Presenting Author:The contemporary transformation of societies, institutions, and scientific practices is increasingly shaped by digital infrastructures and data-intensive modes of knowledge production. In a so-called 'data-driven society', data play an increasingly important role in knowledge generation, decision-making and governance processes (Nayak & Walton, 2024). Data are closely linked to both knowledge production and the actions and decisions derived from knowledge claims. Access to data, particularly research data, is also an important aspect of the open science movement. Open Science can be understood as an umbrella term for a range of movements and practices that have reshaped research processes, infrastructures, and norms since the early 2000s (Fecher & Friesike 2014). It is frequently discussed in relation to innovation, transparency, and the improvement of research and innovation systems, particularly at the European level (European Commission 2022). Open science is grounded not only in efficiency-oriented arguments, but also in a democratic rationale. It is expected to increase participation in the production of scientific knowledge and enhance the societal relevance of research (UNESCO, 2023). From this perspective, sharing research data can be seen as a way of strengthening democratic participation and accountability in educational research across Europe. These developments have significant organizational implications:
From an educational and organizational perspective, these challenges can be interpreted as learning processes at the organizational level. Organizational education, broadly understood as focusing on learning in, of, and between organizations (Göhlich et al. 2018), provides a useful lens for examining how data are transformed into knowledge, how knowledge informs action, and where tensions, resistances, or unintended effects emerge. Rather than assuming a linear relationship between data, knowledge, and action, this perspective invites reflection on the everyday practices through which organizations engage with data, negotiate openness, and balance competing demands. Against this background, the proposed workshop aims to open a space for joint reflection and exchange on open research data and organizations. The guiding question of the workshop is: What challenges and potentials does (open research) data in education bring at the organizational level? The workshop aims to address this question by bringing together different perspectives to explore how organizational contexts can shape, enable or constrain the preparation, sharing and reuse of data. Methodology, Methods, Research Instruments or Sources Used The workshop is designed as an interactive and collaborative space with an open and participatory format. It combines short input phases with structured opportunities for collective reflection and small-group work. In a first phase, the organizers will introduce the topic of open research data and organizations by briefly. 1. The workshop opens with an initial input that presents the topic of open science as an overarching social development and highlights its significance for changes in the provision and use of data on organizational Level. (-> Tamara Diederichs) 2. This topic is explored in depth using the example of data available for schools and school administration in Austria. IQS is responsible for central performance tests (iKMPLUS), ILSAs, and evaluation studies. In addition schools are obliged to generate data by internal evaluation. This opens up the perspective of what data is available in schools as an example and addresses the availability and use of data at the organisational level. It also addresses the challenges of integrating data from various sources and synopsis in order to generate knowledge and bring knowledge to action (Schildkamp, 2019). (-> Erich Svecnik) 3. The third input provides an organizational education/learning perspective. The focus would be on how open research data becomes (or fails to become) organizational learning in educational practice. This would particularly regard knowing–acting gaps, interpretive work, and the role of professional judgment and responsibility in data-informed educational settings. (-> Charlotte Arkenback-Sundström) In a second phase, participants will be invited to form small groups based on their own research interests, professional backgrounds, or practical experiences. These groups will work on selected sub-questions related to open data at the organizational level, such as organizational strategies for data sharing, ethical and legal constraints, data reuse in organizational learning, or the role of infrastructures and support mechanisms. Participants will be encouraged to draw on concrete cases and theories from their own contexts. This approach is based on the Bar Camp method. The small-group discussions will focus on identifying key tensions, practices, and questions rather than on producing finalized results. As a working output, groups will develop short discussion notes or conceptual sketches that summarize their reflections and highlight emerging themes. The results will be presented in a final plenary session. Conclusions, Expected Outcomes or Findings The workshop aims to create a reflective space for discussing open research data as an organizational issue in educational research. By bringing together participants from different institutional and national contexts, the workshop is expected to contribute to a more nuanced understanding of how openness, data practices, and organizational learning intersect. As an outcome, the workshop seeks to: • make visible the often implicit organizational conditions shaping data sharing and reuse in education, • identify recurring challenges and potentials across different organizational contexts, • stimulate further conceptual and empirical work on open data from an educational and organizational perspective. The workshop is conceived as a dialogue. Depending on participants’ interests, the discussion outputs may serve as a basis for further joint work. Participants will be invited to consider developing their discussion outputs into contributions for the special issue Open Research Data in Education: Reflections, Practices, and Reuse in the Journal of Open Research in Education (Network 12) NOTE: The research workshop should be submitted as a joint format for NW 12 and 32. References Fecher, B., & Friesike, S. (Hrsg.). (2014). Open science: One term, five schools of thought. In S. Bartling & S. Friesike (Hrsg.), Opening science: The evolving guide on how the internet is changing research, collaboration and scholarly publishing (S. 17–47). Springer. https://doi.org/10.1007/978-3-319-00026-8 Chauvette, A., Schick-Makaroff, K., & Molzahn, A. E. (2019). Open data in qualitative research. International Journal of Qualitative Methods, 18, 1–6. https://doi.org/10.1177/1609406918823863 Diederichs, T., & Fritz, M. (2024). Open-Science-Praktiken in der Erziehungswissenschaft (Preprint/Übersichtsbericht). Zenodo. https://doi.org/10.5281/zenodo.13880948 European Union. (2025). Data-driven learning: How open data powers the future of education. https://data.europa.eu/en/news-events/news/data-driven-learning-how-open-data-powers-future-education Göhlich, M., Novotný, P., Revsbaek, L., Schröer, A., Weber, S. M., & Yi, B. J. (2018). Research memorandum organizational education. Studia Paedagogica, 23(2), 205–215. Helbig, C., & Lukacs, B. (2019). Openness als Prinzip von Organisationsentwicklung: Werkbericht zu partizipationsorientierten Dialogformaten im Projekt OERlabs. Zeitschrift für Hochschulentwicklung, 14(2), 109–122. https://doi.org/10.3217/zfhe-14-02/06 Krammer, G., & Svecnik, E. (2020). Open science als Beitrag zur Qualität in der Bildungsforschung. Zeitschrift für Bildungsforschung, 10, 263–278. https://doi.org/10.1007/s35834-020-00286-z Nayak, B. S., & Walton, N. (2024). Limits of data society. In Political economy of artificial intelligence (Kap. 7, S. 145–160). Springer. Schildkamp, K. (2019). Data-based decision-making for school improvement: Research insights and gaps. Educational Research, 61(3), 257–273. https://doi.org/10.1080/00131881.2019.1625716 UNESCO. (2021). UNESCO recommendation on open science. https://unesdoc.unesco.org/ark:/48223/pf0000379949/PDF/379949eng.pdf.multi | ||