This analysis reveals the importance of data round-tripping in enhancing community-driven knowledge management in Wikidata.
Abstract (max 500 words) In the evolving Semantic Web ecosystem, where centralized hubs such as Wikidata coexist with third-party databases, ensuring semantic consistency and data quality across platforms is both a technical necessity and a significant governance challenge. Data round-tripping—the bidirectional synchronization of data between Wikidata and external databases, including, more recently, Wikibase instances (Lindemann et al., 2026, submitted)—has gradually emerged as a critical practice. It is driven by the Wikimedia community’s vision and activities aimed at sustainable, participatory knowledge management (Pellizzari & Marchetti, 2025). This paper analyzes the evolution of the concept of data round-tripping within the Wikimedia ecosystem, tracing its origins from early GLAM-oriented activities focused on Wikimedia Commons (Larsson & Zeinstra, 2019) to its full adoption by Wikidata users, via the creation of a dedicated community page in July 2022. Within Wikidata, the term has been predominantly adopted by users active in the field of authority control (Pellizzari, 2023). Their practices evolved from simple data exchange into a co-creative process in which technical workflows are deeply intertwined with community collaboration and institutional dialogue, as can be traced in the history of the community pages on Wikidata. Volunteers and institutional staff of external databases collaborate to correct errors, reconcile divergent records, and negotiate data models, embedding metadata directly into the shared knowledge infrastructure (Pellizzari & Marchetti, 2025). Over time, such practices became increasingly visible, structured, and codified within the Wikidata community. Data round-tripping thus transformed from a niche activity focused on retropatrolling and data clean-up into a set of established practices and guidelines, reaching a milestone with the creation of a dedicated community project on Wikidata in October 2025. This paper investigates the evolving practical meaning of the concept across diverse contexts of Wikidata volunteer activity, as well as its presence within scholarly discourse. The term “data round‑tripping” (including variants such as “round‑tripped”) appears in recent scientific literature related to Wikidata also within the field of cultural heritage (Meiners & Bulle, 2025), where the concept first emerged, as well in other domains (von Mering et al., 2023; Braisher & Fitchett, 2025). Ultimately, this research provides a snapshot of the process’s current sociotechnical dimensions, including an evolving toolkit of community-developed solutions—such as community pages, queries, and shared files—which support complex synchronization workflows. It shows that data round-tripping has come to be recognized as more than a technical aspect within the Wikidata-Wikibase ecosystem. It constitutes a foundational practice for fostering ethically engaged and resilient digital communities, enhancing accountability, and strengthening durable connections among academic research, GLAM institutions, and volunteer networks.The paper concludes by offering governance recommendations to third‑party institutions, inviting them to understand how the Wikidata-Wikibase community is shaping the concept of data round‑tripping. Ultimately, the successful development of federated knowledge ecosystems for public metadata also depends on building a shared, cross‑stakeholder understanding of this practice. Bibliography Braisher, T., & Fitchett, D. (2025). The New Zealand Thesis Project: Connecting a nation’s dissertations using Wikidata. Journal of Librarianship and Scholarly Communication, 13(1), eP18295. DOI: http://dx.doi.org/10.31274/jlsc.18295Larsson, A., Ånäs, S., & Zeinstra, M. (2019). Wikimedia Commons Data Roundtripping: Final report. Retrieved from https://commons.wikimedia.org/wiki/File:Wikimedia_Commons_Data_Roundtripping_-_Final_report.pdf (last accessed: 5 January 2026). Lindemann, D., Candela, G., Marchetti, A., Pellizzari di San Girolamo, C. C., Olea, I., Varvantakis, C., Assis, T., Moitinho de Almeida, V., Obregón, Á., Santiago Faria, A., Schöch, C., & Trigo, L. (2026). The Wikibase ecosystem in DH and GLAM. Transformations: A DARIAH Journal. Retrieved from https://zenodo.org/records/18077409 (last accessed: 8 January 2026). Meiners, H.-L., & Bulle, K. (2025). Disrupting the dust: Identifier properties and the future of cultural heritage metadata in Wikidata. Journal of Open Humanities Data, 11, 65. https://doi.org/10.5334/johd.412 von Mering, S., Braun, P. J.-C., Cubey, R. W. N., Groom, Q., Haston, E. M., Hendriksen, A., Johaadien, R., Leachman, S., Marsden, L., Rainer, H., Santos, J., & Endresen, D. (2023). Modelling research expeditions in Wikidata: Best practice for standardisation and contextualisation [Conference abstract]. Biodiversity Information Science and Standards, 7, e111427. DOI: http://dx.doi.org/10.3897/biss.7.111427 Pellizzari di San Girolamo, C. C. (2023). Conflations and duplications in Wikidata items: Causes, detection, solutions, and issues. In Proceedings of the Wikidata’23: Wikidata workshop at ISWC 2023). Retrieved from https://ceur-ws.org/Vol-3640/paper4.pdf (last accessed: 8 January 2026). Pellizzari di San Girolamo, C. C,, & Marchetti, A. (2025). Data round-tripping for "Swiss WikiCite" [Conference presentation]. WikiCite 2025, Bern, Switzerland. https://commons.wikimedia.org/wiki/File:Data_round-tripping_for_Swiss_WikiCite_(WikiCite_2025).pdf (last accessed: 8 January 2026). Pellizzari di San Girolamo, C. C. (2025). Data round-tripping with authority files: An overview and some examples [Conference presentation]. Data Reuse Days 2025. https://commons.wikimedia.org/wiki/File:Data_round-tripping_with_authority_files_(Data_Reuse_Days_2025).pdf (last accessed: 8 January 2026). Keywords data round-tripping, authority control, Wikidata, participatory infrastructure, linked open data Topics Infrastructures of engagement: designing open, inclusive, collaborative, and sustainable platforms Co-creation, citizen science, public and participatory humanities, and community-driven, engaged scholarship New models of collaboration across academia, memory institutions, and society
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