Dieses Fact-Sheet entstand aus einem Fragenkatalog des Use Cases „Publikation großer Datensätze“ des DiTraRe-Projekts. Es soll als Übersicht und Ressourcensammlung für in der Forschung häufig auftretenden Fragen dienen. Die Fragen haben ihre rechtlichen Schwerpunkte im Urheber- und allgemeinem Datenrecht.
This poster presents the Leibniz Science Campus Digital Transformation of Research (DiTraRe) in a concise way.
This is a ready-to-publish version of the interim report submitted on the 14th of February 2025 by the Leibniz Science Campus "Digital Transformation of Research" (DiTraRe) to the Leibniz Association. The report summarises the first 16 months of activity of DiTraRe.
In the petabyte-era of climate research, harmonising diverse environmental and geoscientific datasets is critical to improve data interoperability and support effectiveness of interdisciplinary studies. This paper presents an idea of designing an LLM-based tool to extract and standardize metadata from climate research repositories. The solution leverages the adaptability of LLMs that are able to understand contextual nuances. By addressing common inconsistencies such as varying parameters (observation types), units, and definitions, the proposed tool will significantly improve effective data integration. It will be the first step to facilitate the creation of a unified metadata schema adhering to the FAIR principles.
Digitale Transformationsprozesse wirken sich auf die Forschung & Wissenschaft aus. Einerseits bei der Erhebung, Auswertung & Aufbewahrung von Forschungsdaten, andererseits beim Einsatz digitaler Technologien auf die Forschenden selbst sowie auf die Gesellschaft. Eine besondere Rolle spielen dabei generative KI-Anwendungen, beispielsweise für die Recherche oder Analyse von Daten. Vor diesem Hintergrund ergeben sich auch neue Fragestellungen für die TA, etwa die Politikberatung. Im Projekt „Leibniz WissenschaftsCampus – Digital Transformation of Research“ (DiTraRe) widmen wir uns diesen Themen.
This vision/position paper shortly introduces and summarizes the DiTraRe project with a special focus on implementation of AI techniques to each use case by the dimension "exploration and knowledge organisation". The paper was accepted to be published and presented during the 4th International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment, co-located with the 23rd International Semantic Web Conference (ISWC) 2024.
A poster presenting the DiTraRe project in general as well as focusing on the current state and ideas of applying specific AI methods to each use case by the dimension "exploration and knowledge organisation". The poster was presented during the fPET 2024 conference (Forum on Philosphy, Engineering and Technology 2024).
In our contribution to the fPET 2024 conference (Forum on Philosphy, Engineering and Technology 2024), we present the concept of a Leibniz ScienceCampus and the specific characteristics of DiTraRe. One focus is the interface between natural sciences and engineering on the one hand and sociology, technology assessment, law and ethics on the other. We report on our experiences with the chosen interdisciplinary and multi-layered approach and present the first results of our work with a focus on current challenges.
The effective refractory period (ERP) is one of the main electrophysiological properties governing arrhythmia, yet ERP personalization is rarely performed when creating patient-specific computer models of the atria to inform clinical decision-making. This study evaluates the impact of integrating clinical ERP measurements into personalized in silico models on arrhythmia vulnerability.
Computer models for simulating cardiac electrophysiology are valuable tools for research and clinical applications. Traditional reaction-diffusion (RD) models used for these purposes are computationally expensive. While eikonal models offer a faster alternative, they are not well-suited to study cardiac arrhythmias driven by reentrant activity. The present work extends the diffusion-reaction eikonal alternant model (DREAM), incorporating conduction velocity (CV) restitution for simulating complex cardiac arrhythmias.
The role of the right atrium (RA) in atrial fibrillation (AF) has long been overlooked. Multiple studies have examined clinical conditions associated with AF, such as atrial enlargement, fibrosis extent, electrical remodeling, and wall thickening, but have been mainly concentrated on the left atrium (LA).
Computer models of the atria can aid in assessing how the RA influences arrhythmia vulnerability and in studying the role of RA drivers in the induction of AF, both aspects difficult to assess clinically and experimentally. This work assesses the “Creative Concept” of incorporating the RA in computational arrhythmia studies based on 1398 virtual pacing sequences in 8 biatrial and 8 monoatrial patient-specific models under 3 different substrate conditions, resulting in a total of 48 distinct model configurations.
This is the original proposal for the Leibniz Science Campus "Digital Transformation of Research" (DiTraRe). Within DiTraRe, the effects and potentials of the increasing digitalization of scientific work are investigated in four interdisciplinary research clusters. Based on use cases from different disciplines, concrete solutions for challenges arising from digitalisation are developed, which are then generalised.
A poster introducing the DiTraRe project to the community working on applying AI techniques in research presented at the workshop AI4RE (AI for the Reserach Ecosystem). A short wrap-up of the project in general together with a more detailed yet still preliminary view from the perspective of the dimension "exploration and knowledge organisation".