AVOBMAT (Analysis and Visualization of Bibliographic Metadata and Text) is a multilingual text mining service created in close collaboration with researchers. It empowers scholars, educators, and students to explore large collections of textual and bibliographic data—without programming skills or costly hardware.
Built on an extensible, scalable, and modular cloud-based infrastructure, AVOBMAT ensures a transparent and reproducible research process supported by a wide range of analytical tools. Designed for environment-conscious use, it enables researchers to reveal 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 so researchers can focus on critical interpretation and discovery.
Access public databases or upload yours easily in various formats.
Clean your texts and configure the settings for all the analyses.
Interactive analysis and visualizations include topic modelling, Part-of-speech tagging, Named entity recognition, disambiguation and linking.
Export and import configuration settings. Save statistical data and visualizations. Share or make your databases public.
AVOBMAT can preprocess, analyse, and (semantically) enrich a large number of texts and metadata in several languages without coding skills.
The analytical and visualization tools provide interactive close and distant reading of texts and bibliographic data.
AVOBMAT has a transparent, peer-reviewed workflow with customizable parameter settings for all tools.
AVOBMAT combines bibliographic data and natural language processing research methods (e.g. transformer models) in an integrated, interactive and user-friendly web application.
AVOBMAT fosters critical analysis, for instance, by identifying data gaps and missing metadata values.
AVOBMAT offers multilingual comparative analysis with time-based components.
Researchers, students, teachers of digital humanities, and libraries.
How can AVOBMAT help researchers, libraries and institutions that support or conduct digital humanities research and teaching?
...your or your library’s large digital collections in innovative and interactive ways with customizable preprocessing, analysis & visualization tools;
...by combining bibliographical data and text analyses and using NLP techniques
...unveil overlooked connections, themes, trends & patterns
...and interpret texts, (meta)data & visualizations
(e.g. selection, metadata, classification) in your databases at scale to make more informed decisions about your research (questions)
...novel types of evidence and test old hypotheses
...digital humanities and highlight the challenges, limitations and strengths of computational text analysis and visual representation of digital texts and datasets
...with your colleagues, share your findings and make your databases public