The aim of this paper is to introduce the rationale, history, and challenges behind the design and creation of AVOBMAT (Analysis and Visualization of Bibliographic Metadata and Texts), a multilingual text-mining tool developed at the University of Szeged and hosted on the infrastructure of the Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen (GWDG). AVOBMAT is available at avobmat.hu and has been accessed from 40 countries since its launch in October, 2025.

AVOBMAT is a multilingual text-mining service created in close collaboration with researchers, including members of the DARIAH Bibliographical Data Working Group. It empowers scholars, educators, and students to explore large collections of textual and bibliographic data without requiring programming skills or costly hardware. Built on an extensible, scalable, modular cloud-based infrastructure, AVOBMAT supports a transparent and reproducible research process through a wide range of analytical tools, enabling socially responsive scholarship grounded in verifiable results. It enables researchers to identify hidden connections, enrich texts and metadata, and collaborate by sharing private databases. With support for 25 languages and customizable features, AVOBMAT makes advanced text analysis accessible and inclusive, allowing researchers to focus on critical interpretation and discovery.

AVOBMAT’s public, participatory infrastructure offers an inclusive model of collaboration among students, researchers, and GLAM institutions by enabling them to publish digital collections and, where appropriate, to make private databases public after the conclusion of research projects. AVOBMAT also supports pedagogies of engagement in digital humanities education: teachers and students can use a browser-based platform with comprehensive documentation (interface overview, step-by-step workflows, configuration settings, glossary, appendices) to support seminar-based teaching. It further supports DH teaching by providing more than 30 ready-to-use literary and historical corpora in 16 languages. By lowering technical barriers, AVOBMAT broadens participation in critical text and metadata analysis: non-coding users can explore databases interactively using diverse analytical tools and customizable features. Research groups and labs can coordinate shared databases and methods across projects to improve reproducibility. Libraries can publish curated collections for in-depth exploration.