What is LILY?

LILY is an innovative research platform that digitalizes, modularizes, and makes the entire scientific workflow more accessible. The platform's goal is to make research more efficient, collaborative, and technology-independent for a wide range of stakeholders – from universities and non-university research institutions to companies and civil society initiatives.

The platform combines advanced analytical tools, high-performance computers, cloud and quantum computing, as well as intelligent assistance systems in a unified, intuitive environment. LILY follows the principle of open science and focuses on democratizing research – meaning fewer access barriers, more reusability of results, and stronger participation of broader social groups.

The Building Blocks of LILY

LILY is modularly designed and consists of several functional core areas:

• LAB: The virtual research laboratory. Here users create scientific workflows – structured process chains of analysis, simulation, or visualization steps.
• HUB: The community and publication center of the platform. Researchers can share and collaboratively develop models, data, results, or ideas here.
• DECK: The resource manager. This area coordinates computing power, laboratory equipment, or quantum resources – whether from one's own institute or from the shared pool.
• ZONE: A presentation module that allows research to be presented interactively and comprehensibly for outsiders, such as in the form of dashboards or AI-supported question-answer systems.
• CHAT and DOCS: Communication and documentation areas that facilitate exchange and ensure traceability.

Collaboration Instead of Silo Thinking

A key feature of LILY is interdisciplinary collaboration without technical entry barriers. Researchers from different disciplines can collaborate on the platform without having to deeply familiarize themselves with each other's technologies. This is made possible by a system of encapsulated "features" – building blocks like AI models, data analyses, or device drivers – that can be combined via drag-and-drop. This makes it possible, for example, for biologists to use AI-supported image analyses without programming machine learning themselves.

Application in Research, Education, and Business

LILY is deliberately broadly positioned and suitable for a variety of application fields:

• In medical research, the platform enables combined analysis of clinical, laboratory, and image data – with clear separation of professional responsibilities and automated data processing.
• In educational research, LILY supports evidence-based policymaking by analyzing educational data and directly testing simulations of new measures.
• For small and medium-sized enterprises (SMEs), LILY creates access to data-based research without requiring their own IT department. Pre-trained models and simple analysis workflows enable innovations even with limited resources.
• In university teaching, students benefit from realistic research environments that they can help shape themselves – including cloud resources, laboratory connections, and publication tools.

Technology Meets Accessibility

Technologically, LILY combines state-of-the-art components – including classical high-performance computers, quantum computing, specialized simulation environments, and AI libraries – in a thoughtful user interface. Automation, version control, and smart assistants help minimize routine tasks and maximize time for creative research.

A central concern is: hide complexity, don't complicate. The platform was designed so that it can be effectively used by both computer science experts and non-technical disciplines.