******Workshop focus******
Our growing ability to unravel the complexities of life—from molecular biology to the diagnosis and treatment of diseases—is generating unprecedented amounts of data. This directly impacts the design and future development of information and data management pipelines; thus, new ways of processing data, information, and knowledge in life sciences environments are strongly needed.

The seventh edition of the workshop aims to remain a meeting point for researchers in Artificial Intelligence (AI), Information Systems (IS), Data Management (DM), and Conceptual Modeling (CM) working to develop sophisticated, scalable solutions to the complexity and scale of data generated in life sciences.

From the precise ontological characterization of the components involved in complex biological systems to the modeling of the operational processes and decision support methods used in, for instance, the diagnosis and prevention of diseases, the joined research communities of AI, IS, DM, and CM have an essential role to play; they must help in providing feasible solutions for high-demanding problems of life sciences. CMLS aims to become a forum for discussing the conceptual modeling community's responsibility to support life sciences in lght of these new realities.


******Topics of interest******

The seventh edition of the workshop focuses on Conceptual Modeling as a means to address the challenges that emerge when designing and developing systems for life. The workshop is not restricted to specific research methods; we will consider both conceptual and empirical research, as well as novel applications.

The topics of interest include, but are not limited to:

- AI for conceptual modeling in life sciences
- Conceptual Modeling approaches to One Health
- Large Language Models for improving conceptual modeling in life sciences
- Conceptual models for data-driven AI systems in life sciences
- Conceptual modeling for omics data
- Conceptual modeling of complex biological systems and health ecosystems
- Information systems for healthcare and precision medicine
- Design, implementation, and evaluation of life sciences information systems
- Life science-related domain-specific modeling languages
- Data management and integration for omics data and life sciences in general
- Ontologies and knowledge representation for life sciences
- Interoperability of life data and information systems
- Business process modeling for life sciences
- Conceptual model-driven big data analytics for life sciences problems
- Models for the digital transformation of life science systems
- Conceptual models in life sciences: from theory to practice
- Models to facilitate multidisciplinary exchange in life science contexts
- Pathogen-related conceptual models and their applications
- Models and information systems for fighting climate change and its effects on life sciences
- Reviews focusing on a relevant area of modeling in life sciences.


******Sumbission Guidelines******

CMLS 2025 proceedings will be part of the ER 2026 Workshop volume published by Springer. Submissions must conform to the Springer LNCS/LNBIP format. The page number for workshop papers is between 12 and 16 pages. Papers must be submitted as PDF files using EasyChair at https://easychair.org/my/conference?conf=er2026, choosing the track "CMLS Workshop papers".

For details, see the workshop website and the page "https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines".

******Organizing Committee******

Alberto García S., Universitat Politècnica de València, Spain
José Reyes, Universitat Politècnica de València, Spain
Nelly Barret, Politecnico di Milano, Italy
Mireia Costa, Universitat Politècnica de València, Spain
Carla Taramasco, Universidad Andrés Bello, Chile

Main contact: algarsi3@upv.edu.es