Open Science will be discussed along the methodological principles of Constructivist Grounded Theory (Charmaz, 2006; Grabensteiner, 2023). Research processes as communicative endeavor will be distinguished from methodically guided knowledge construction through an interlinkage of theoretical sensitivity and data collection. Data sharing practices of Open Science ask for standards, focusing on research data to be findable, accessible, interoperable and re-usable, as for instance stated in the European commission framework FAIR in Horizon Europe (European Commission, n.d.). Beyond that there are criteria for scientific practices to meet standards. Strübing et al. (2018) propose appropriateness towards a specific subject matter, empirical saturation, theoretical depth, writing performance and originality (Strübing et al., 2018, p. 85f) as quality criteria. Discussing frameworks, both for data sharing and for data collection, the question arises, how data and knowledge are intertwined and in what way qualitative research practice challenges and enables Open Science simultaneously by meeting its own quality criteria. Jesser (Jesser, 2011) proposes two forms of data information to be shared and archived along with the data. First, meta-information “necessary to understand the content and structure of the dataset” (Jesser, 2011, p. 8) and second “context information”, meaning “institutional, theoretical and methodological background” (Jesser, 2011, p. 8). This enables insight into ways of data collection, data processing as well as reflections by researchers in the course of dealing with the dataset. Writing memos is already an established practice in qualitative research whereas haring them in order to make data accessible for secondary analysis is still in progress of becoming a standard. New forms of Open Science shed a light on data documentation practices, making way for qualitative research to contribute to customs of “openness” in qualitative and quantitative research. Up to the point where research participants are not only “voices” heard in the research process, but also contributors to knowledge construction. Borg et al. (Borg et al., 2012) show at the example of Co-Operative Inquiry, they develop different criteria of openness, being consensus, historicity (process of knowledge production), reflexivity (especially on asymmetries) and knowledge co-production (interaction with participants, giving something back) (Borg et al., 2012, p. 10ff). Applying those as standards in the process of data construction, shared data gain a further dimension of depth and saturation. Synopsis of standards for data sharing and documentation of knowledge construction processes shall inspire reflections on future Open Science practices considering the whole research process.

Borg, M., Karlsson, B., Kim, H. S., & McCormack, B. (2012). Opening up for Many Voices in Knowledge Construction. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 13(1), Article 1. https://doi.org/10.17169/fqs-13.1.1793 Charmaz, K. C. (2006). Constructing grounded theory: A practical guide through qualitative analysis. SAGE Publications Ltd. European Commission. (n.d.). Open science. Retrieved 22 January 2024, from https://rea.ec.europa.eu/open-science_en Grabensteiner, C. (2023). Medienbildung im Medienhandeln. Rekonstruktion relationaler Bildungsprozesse am Beispiel von Instant Messaging in Schulklassen. Springer VS. https://doi.org/10.1007/978-3-658-40699-8 Jesser, A. C. (2011). Archiving Qualitative Data: Infrastructure, Acquisition, Documentation, Distribution. Experiences from WISDOM, the Austrian Data Archive. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 12(3), Article 3. https://doi.org/10.17169/fqs-12.3.1734 Strübing, J., Hirschauer, S., Ayaß, R., Krähnke, U., & Scheffer, T. (2018). Gütekriterien qualitativer Sozialforschung. Ein Diskussionsanstoß. Zeitschrift Für Soziologie, 47(2), 83–100. https://doi.org/10.1515/zfsoz-2018-1006