This presentation will focus on the problematization of semantic data structuring through the lens of situated curating in two digital platforms, ParVO and ecHoimages, both of which focus on research on arts education. Arts education is not merely an application field for these platforms, but an epistimological zone that spans, for instance, cultural mediation, teaching, design, and artistic practices. So the platforms are built, problematized, and inscribed in this framework. Both platforms are Wikibased (https://parvo.wikibase.cloud/ and https://echoimages.labs.wikimedia.pt/) and are being tested with students in the arts field. From this experience, we developed the concept of decyclopedization [1] and explored situated knowledge [2] as an archival possibility [3], [4], [5], [6]. Right now, we mobilise the concept of decyclopeding as a way of (un)learning [4], [7], using subversive strategies and tactics within the Wikimedia ecosystem to achieve alternative and marginal knowledge. We also strive to promote educational exercises and challenges that incorporate error, playfulness, and fiction into the dynamics of research and pedagogy with these tools. These dynamics allowed us to question assumptions of neutrality and universality embedded in dominant data models and encyclopedic platforms, and to reflect on how relational, partial, and context-dependent forms of knowing can inform the conception of data models. It also highlights how digital systems classify, relate, and legitimize knowledge. Rather than sharing results, we expose the relational logics through which data are organized, allowing others to reconfigure the ways a problem is investigated. 

More recently, we have been developing the idea of situated curating [8], [9], as a way of resignifying heritage from a fixed object of preservation to a living, relational, and contested process, grounded in the investigation of ruins as spaces for artistic practices and curatorial actions. In this sense, these spaces are seen not only as architectural remains, but also through the entanglements between surrounding nature, human communities, and more-than-human inhabitants. Situated curating challenges the way we think of arts education and the respective platforms for teaching and research. In this sense, what kinds of platforms and data models should be developed for arts education in the context of situated curating?

We mobilize situated curating here as a reference for understanding how positionality and political concerns inform data practices. In both cases, knowledge emerges from following relations rather than from fitting phenomena into predefined categories. So it becomes concrete in everyday decisions about how data are entered, described, and connected in the platforms. While data is usually employed as a technical task, our project approaches it as a curatorial process in which decisions about entities, properties, and relations shape what becomes visible within a cataloguing system. 

This approach requires new perspectives and languages that question traditional methods of archiving as well as broader regimes of knowledge organization and production. Regarding data collection and cataloging, this poses an enormous challenge, as situated and context-dependent forms of knowledge cannot be fully accommodated by fixed, universal categories, requiring a restructuring of semantic data through new vocabularies, models, and ontologies. It also becomes important when the data are intended to be shared and reused by others, a central concern in open research and educational data practices. In this regard, we seek the FAIR (Findable, Accessible, Interoperable, Reusable) [10] and CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) [11] frameworks.

Complex transdisciplinarity and epistemological intersections require new knowledge graphs (KG) assisted interfaces that enable research across heterogeneous systems and evolving research questions, treating data as capta [12] by supporting narrative, relational, and exploratory modes of inquiry. In this sense, KG supports exploration across relations, not just record storage. Our platforms promote visual querying by graphs and spacetime views.

Our methodological approach is based on the design and experimental use of open semantic data infrastructures built with the Wikibase framework [13]. We developed ParVO and echoImages as platforms in which vocabularies and interface choices are treated as part of the research process, rather than as technical steps that follow data collection. In this scenario, entity types and relations can be created and revised over time through FAIR and CARE principles and ongoing modeling and discussion, allowing the data structure to change as research questions evolve, rather than being fixed in advance. The statements as claims in Wikibase enable a flexible workflow for handling different data models and for interoperability with Linked Open Data (LOD) via Wikidata. A central methodological aspect is the close link between data preparation, documentation, and modeling. Data is entered manually and collaboratively by students and researchers. Modeling decisions are discussed in relation to how they affect later possibilities for searching, comparing, and reusing the data. This dynamic includes decisions about which actors, materials, and processes are explicitly represented, and how relations between them are described. In this sense, cataloging is approached as an interpretive practice, not merely a technical procedure. User interface (UI) and user experience (UX), along with their respective tests, are also treated as part of the research method. The platforms are organized to support relational and narrative exploration rather than linear, record-based browsing. In the case of echoImages, with a React front-end, researchers and students can follow material trajectories, connect different stages of production, and trace socio-environmental relations across artistic, industrial, and ecological contexts. This approach supports exploratory and comparative ways of working with data, which are common in transdisciplinary and arts-based research. Perspectives from feminist and intersectional epistemologies [14], [15], infrastructural critique [16], [17], [18], critical data studies [19], and digital humanities inform reflections on how infrastructures embed values and assumptions. Situated curating functions as a conceptual reference that helps keep attention on context, positionality, and relations when making technical design choices, especially in practices of data preparation, documentation, and reuse.

The usability tests are exciting, not only for prototype development but also as formative testing opportunities. Students and researchers are not only testing the platform but also learning about the content. This whole experience allowed us to explore the idea of data as capta so that users can inscribe their narratives on the platforms. We constantly discuss the FAIR and CARE principles, which allow us to think not only ethically about the information we are working on, but also to draw insights into interoperability between Wikibase and Wikidata, situated knowledge, and universalizing knowledge. Based on the experience of situated curating in extreme places, such as industrial ruins, we began to develop a controlled, operational vocabulary that includes properties and objects from fields such as the arts, architecture, archaeology, and the natural sciences. Humans and more-than-humans relate to extreme places curated and intervened upon by artists. Finally, the experience of situated curating as capta seems to be, for the working group, a new transdisciplinary field that opens up for future work, particularly in digital platforms with LOD.

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