PROVIDEDH - PROgressive Visual DEcision-Making in Digital Humanities

The PROVIDEDH project (PROgressive VIsual DEcision-Making in Digital Humanities) aims to provide visual interactive tools that convey the degree of uncertainty of the datasets and computational models used behind, designed to progressively adapt the visualizations to incorporate the new, more complete or more accurate data. It aims to give DH scholars a space to explore and assess the completeness and evolution of the involved research objects, the degree of uncertainty that the models applied to the data incorporate, and to share their perspectives and insights to other stakeholders of society. PROVIDEDH revolves around two key scientific questions: 1. Is it possible to assess the degree of uncertainty that a particular DH dataset incorporates, tracking such degree during the evolution of the dataset and how it is affected when different computational models are applied to it? 2. Is it possible to convey this evolution of uncertainty by means of interactive multimodal interfaces that progressively adapt to the moment in which they are used and permit the users to make decisions accordingly? The methods used include state-of-the-art computational methods in computer science and data visualisation, together with Open Innovation, Design Thinking and Citizen Science approaches. With this cross-disciplinary approach we aim at fostering ecosystem centric networks, contributing to the sustainability and accuracy of the data as well as reproducibility of workflows. The novelity of the proposed project lies in its interdisciplinary approach combining state of the art methods in computer science and visualisation methods on the one hand, and Open Innovation approaches, methods in Design thinking and the involvement of Citizen Science from the Digital Humanities perspectives on the other. This cross-disciplinary approach to data treatment, dissemination and access makes results more sustainable, provides better and wider-reaching access as well more accurate data.

PROVIDEDH develops a new approach to dealing with uncertainty in data-driven knowledge systems. At its core is the idea that uncertainty should not be reduced or eliminated, but made visible, understandable, and productively usable. In a world increasingly shaped by complex data, this shift is essential for enabling more reflective and responsible decision-making. On an epistemic level, the project establishes open structures and standards that support the differentiated representation and interpretation of complex and ambiguous data, particularly within the Digital Humanities. These include contributions to established frameworks such as TEI-based data modeling, adapted to account for uncertainty, multiplicity, and context-dependency. Rather than treating uncertainty as a deficit, PROVIDEDH frames it as an integral component of knowledge, thereby enabling more nuanced and transparent ways of working with cultural and societal data. On a methodological level, PROVIDEDH develops new forms of collaboration. Through participatory approaches, open social innovation, and futuring processes, the project creates collective ways of engaging with knowledge that connect scientific, societal, and artistic perspectives. Participants are not only recipients of knowledge but active contributors, exploring data, reflecting on uncertainty, and co-creating possible futures. In particular, the integration of art and science through art-driven innovation opens up new modes of thinking, experimenting, and reflecting, allowing uncertainty to be explored in experiential and creative ways. On a transformative level, these approaches are translated into concrete formats and structures. Educational initiatives such as "Multisensory Classrooms" and "Journeys of Uncertainty" make complex relationships tangible and accessible, fostering new forms of learning that engage both cognitive and sensory dimensions. At the same time, the platform URBANITARIUM emerges from the project as a lasting structure that connects research, practice, and society. Formalized as an association, it enables the continuation, scaling, and transfer of the project's approaches into new domains and collaborations. The methods and concepts developed within PROVIDEDH continue to inform ongoing work at the intersection of data, art, and ecological systems, including emerging approaches to understanding complex spatial and environmental dynamics. In this way, the project extends beyond its original scope and contributes to broader discussions on sustainability, justice, and future-oriented knowledge production. By combining open knowledge structures, innovative collaborative methods, and scalable formats, PROVIDEDH establishes a foundation for a reflective, inclusive, and future-oriented engagement with uncertainty-one that is increasingly relevant across scientific, societal, and environmental contexts.