While Vision-language models (VLMs) interpret text-rich images effectively, they struggle with reasoning across long, multi-page documents.We present Active Long-DocumEnt Navigation (ALDEN), a multi-turn reinforcement learning framework that fine-tunes VLMs as interactive agents capable of actively navigating long, visually rich documents rather than passive readers.ALDEN features a novel fetch action that allows direct page indexing, complementing the classic search action and better exploiting document structure.To ensure training efficiency and stability, we introduce a rule-based cross-level reward for dense supervision and a visual-semantic anchoring mechanism using dual-path KL-divergence constraints.We train ALDEN on a curated corpus built from open-source datasets, filtering out trivial samples and rewriting queries to incentivize multi-turn navigation and fetch usage.Empirically, ALDEN achieves state-of-the-art results on five long-document benchmarks, offering a more accurate and efficient path for long-document understanding.All of our code and datasets will be made publicly available at Github 1 .

Digital methods and collaborative research in virtual research environments are gaining in importance for the arts and humanities. The EU-funded project DARIAH aims to enhance and support digitally-enabled research across these disciplines. The most basic but nevertheless fundamental task of DARIAH is to provide sustainable storage for research data. Information contained in data like images, texts or music needs to be secured and to remain accessible even if the original information carrier becomes lost or corrupted. The heterogeneity of the humanistic data and the need for distributed, perform ant access are the main challenges in designing an archiving system for the arts and humanities. Using the "Virtual Scriptorium", a digitisation project in Trier, Germany, this paper exemplary identifies the humanistic researchers' storage needs and derives requirements for an infrastructure. As a solution, a generic architecture for a federated data zone based on the iRODS technologies is proposed. The system implemented in Trier and Karlsruhe is described and will be extended to other locations as the researchers benefit from the initial set-up.