Exdigit Projects
Third-party funded projects bring ideas into practice.
Through external funding, they enable innovative research, interdisciplinary collaboration, and the transfer of scientific knowledge to society and industry. In national and international partnerships, third-party funded projects create opportunities for academic excellence, early-career researcher development, and sustainable innovation.
Putting cultural knowledge into context
a pilot project for the semantic linking of information at the Salzburg Open-Air Museum (KuWi)
Description
Like many other open-air museums, the Salzburg Open-Air Museum collects places. Not only buildings from the surrounding countryside have been moved to the museum grounds, but also a wealth of additional information about these places has been gathered. Although relevant knowledge is available, for example through research carried out at the museum, traditional forms of communication do not allow visitors to fully experience the richness of these places.
As part of the project, Eugen Unterberger and his colleagues are researching new forms of digital communication that combine multi- and intermedial elements into multimodal narratives. Using a special prototype, an investigation is being conducted into how these different forms of communication can be interwoven to create an interactive experience of the site—one that conveys both cultural and personal meaning.
The project is led by Eugen Unterberger and carried out in collaboration with Franz-Benjamin Mocnik, Peter Fritz, and Michael Span from the Salzburg Open-Air Museum. It is funded by the State of Salzburg.
Evaluating Digital Health Interventions with Complex Designs
Description
The digitalisation of healthcare is transforming prevention, diagnosis and therapy, particularly in cardiovascular medicine. Wearables, mobile sensors and health apps enable continuous, patient-centred data collection, offering unprecedented opportunities for personalised care. At the same time, these technologies generate data that are highly complex, irregular, and often incomplete, posing major methodological challenges for traditional statistical approaches.
This project develops new statistical methods specifically tailored to digital health data. The focus is on evaluating digital health interventions in settings where data are high-dimensional, noisy, and heterogeneous across individuals. Particular attention is given to complex study designs, including longitudinal monitoring, N-of-1 trials, and small-sample studies, which are increasingly common in both cardiovascular care and research on rare diseases.
The methodological framework is based on advanced nonparametric statistics. These approaches avoid strong distributional assumptions and are therefore well suited for data characterised by missing values, outliers, irregular measurement times, and strong inter-individual variability. The aim is to enable statistically robust and clinically meaningful conclusions even under challenging data conditions where conventional methods often fail.
A key objective of the project is practical implementation. The developed methods will be translated into user-friendly R software packages, making them accessible not only to statisticians but also to clinical researchers and applied scientists. By bridging methodological innovation and real-world applicability, the project supports evidence-based evaluation of digital health technologies and contributes to more reliable and personalised cardiovascular care.
The project is funded by the FWF under the Elise Richter Programme.
Key persons: Anna Eleonora Carrozzo (Principal Investigator)
Project partners: Salzburg Research (employing institution), PLUS (via EXDIGIT and habilitation)
Project start: 1 September 2025
Project duration: 48 months
