NEMO Summer School - the 10th Edition!
Focuses on the design and implementation of Enterprise Digital Twins and Ecosystems based on conceptual modelling methods. They enable the design of semantically rich diagrammatic models that are both human-understandable and machine-processable, while providing services for analyzing models and interoperating with open digital environments. Conceptual models can thus be used as the knowledge platform of an organization and their value can be co-created by flexible collaboration between digital engineers and stakeholders.
Working in and for digitized organizations where smart devices, digital artefacts, robots, data streams and connectivity are ubiquitous, you will be faced with challenges pertaining to human resources, process lifecycles, business or regulatory rules. NEMO provides a vertical overview across different application domains to prepare you for all dimensions of digitalization.
Become a Digital Leader!
The 10th Edition of the NEMO Summer School will take place at the University of Vienna between July 15th and 26th, 2024, from 09:00 to 17:30 CEST and explores the Digital Innovation Environment (
https://www.omilab.org/brochure) of OMiLAB.
Learn Conceptual Modelling to innovate, design, and engineer digital ecosystems!
Highlights of the NEMO2024 Program
Lectures
International professors, researchers and experts from academia and industry representing various institutions will be presenting their latest research findings, as well as holding practical sessions over the two weeks in Vienna at NEMO2024. Check directly the NEMO homepage for the latest updates.
ADOxx Practice Sessions
Explore hands-on the theoretical aspects and dive into domain-specific modelling methods and ADOxx tools.
How to model concepts of a Smart City? How to analyze Smart City models using query techniques?
Digital Leader Sessions
Design your own innovative scenario and build storyboards. Create a first design prototype of a disruptive business model. Experience the transformation of haptic figures in digitized objects using the Scene2Model tool. More information about the program at:
https://nemo.omilab.org/2024/
