The 3rd International Workshop
on Conceptual Modeling for Life Sciences

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17-20 October, 2022 in Hyderabad, India

Online workshop


In conjunction with the 41th International Conference on Conceptual Modeling (ER 2022)

About

The recent advances in unraveling the secrets of human conditions and diseases have encouraged new paradigms for their prevention, diagnosis, and treatment. As the information is increasing at an unprecedent rate, it directly impacts the design and future development of information and data management pipelines; thus, new ways of processing data, information, and knowledge in health care environments are strongly needed.
The third edition of the workshop aims to continue being a meeting point for Information Systems (IS), Conceptual Modeling (CM), and Data Management (DM) researchers working on health care and life science problems. It is also an opportunity to share, discuss and find new approaches to improve promising fields, with a special focus on Genomic Data Management - how to use the information from the genome to better understand biological and clinical features - and Precision Medicine - giving to each patient an individualized treatment by understanding the peculiar aspects of the disease.
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 the diagnosis and prevention of diseases, the joined research communities of IS, CM, and DM have an important role to play; they must help in providing feasible solutions for a high-quality and efficient health care.
The COVID-19 pandemic has attracted increasing attention to the genetic mechanisms of humans and viruses. CMLS may become an additional forum for discussing the responsibility of the conceptual modeling community in supporting the life sciences related to this new reality. This year – more than in the previous editions – we aim to welcome topics that have become of particular interest for the general ER community: conceptual modeling for big data analytics and AI-driven systems, particularly beneficial to life sciences disciplines.

Topics of interest

The third edition of the workshop focuses on Conceptual Modeling as a means for facing the challenges that emerge when designing and developing systems for life sciences, focused on genomics and precision medicine. 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:

  • Conceptual modeling for genomics
  • Modeling of complex biological systems and of health ecosystems
  • Information systems for healthcare, genomics, or medicine of precision
  • Design, implementation, and evaluation of health information systems
  • Electronic/digital health information systems
  • Life science-related domain specific modeling languages
  • Data management and integration for genomics and biology
  • Ontologies and workflows for life sciences
  • Clinical and biological data interoperability
  • Interoperability of health information systems
  • Knowledge-representation for genetics
  • Business process modeling for genetic/clinical diagnosis
  • Conceptual model-driven big data analytics for genomics, clinical diagnosis or biological problems
  • Conceptual models for data-driven AI systems in life sciences
  • Models for digital transformation of healthcare systems

As we wish to stimulate more discussion in the ER community regarding the use of models for life sciences, we welcome also “discussion papers”, particularly related to the following topics:

  • Conceptual models in life sciences: from theory to practice
  • Models to facilitate multidisciplinary exchange in healthcare contexts

Paper submission guidelines

We invite submissions of high quality papers describing original and unpublished results regarding any of the workshop’s topics of interest.

CMLS 2022 proceedings will be part of the ER 2022 Workshop volume published by Springer in the LNCS series. The authors must submit manuscripts using the Springer-Verlag LNCS style for Lecture Notes in Computer Science. For style files and details, see the page http://www.springer.de/comp/lncs/authors.html. The page limit for workshop papers is 10 pages. Papers must be submitted as PDF files using EasyChair at https://easychair.org/conferences/?conf=cmls2022.

To ensure high quality, all papers will be thoroughly peer reviewed by the Program Committee. Manuscripts not submitted in the LNCS style or having more than 10 pages will not be reviewed and thus automatically rejected. The papers need to be original and not submitted or accepted for publication in any other workshop, conference, or journal. Submission to CMLS 2022 will be electronically only.

Post-conference publication

We are working towards a preliminary agreement with BMC Bioinformatics journal (2-year Impact Factor: 3.169) for a post-conference supplement related to Conceptual Modeling in Life Sciences. If the agreement is reached, all the papers accepted to our workshop will be invited to submit a revised and extended version to the journal supplement.

Important dates

  • Paper submission: June 15th, 2022 July 4th, 2022 (EXTENDED!)
  • Notification: July 14th, 2022 August 12th, 2022
  • Camera-ready version: July 31st, 2022 August 26th, 2022 (firm deadline)
  • ER online conference dates: October 17-20, 2022

Organizers

Anna Bernasconi, Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB)
Politecnico di Milano, Italy
anna.bernasconi@polimi.it

Anna Bernasconi works as a researcher in Politecnico di Milano, within the “Data-driven Genomic Computing” ERC Awarded project (2016-2021), under the supervision of Professor Stefano Ceri. In 2015 she obtained a Master of Science in Computer Engineering from Politecnico di Milano and a Master of Science in Computer Science from University of Illinois at Chicago with a thesis on Formal Methods. Her research is on bioinformatics data and metadata integration methodologies to support complex biological query answering. Main expertise areas include conceptual data design, data integration, data cleaning, semantic web, data analysis; she is passionate about models and methods formalization.



Arif Canakoglu, Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB)
Politecnico di Milano, Italy
arif.canakoglu@polimi.it

Arif Canakoglu currently works as a postdoctoral researcher at Politecnico di Milano; he is involved the “Data-driven Genomic Computing” ERC Awarded project (2016-2021), where he contributes for developing integration methods for heterogenous genomic data and computational methods for genomic applications. In 2016 he received his PHD on biomolecular knowledge data integration (by using a modular schema data warehouse). His research interests include data integration and data driven genomic computing, big data analysis and processing on cloud computing, as well as artificial intelligence applications. His main areas of expertise are heterogenous data integration, data driven/machine learning knowledge discovery approaches in genomics, and big data processes with focus on cloud computing.



Ana León Palacio, Research Center on Software Production Methods (PROS)
Universitat Politècnica de València, Spain
aleon@pros.upv.es

Ana León, PhD in Computer Science (2019, Universitat Politècnica de València), is also University Expert in Medical Genetics and Genomics by the Universidad Católica de Murcia. Her main research topics include Conceptual Modeling, Genomic Data Science, Explainable AI, Data Quality and Information Systems. Currently, she is researcher at the Research Center on Software Production Methods (PROS-UPV) where her research activity is focused on the use of conceptual models for the development of Genomic Information Systems, as well as the definition of a systematic process for the search, identification, load and exploitation of DNA variants in the context of Precision Medicine.



José Fabián Reyes Román, Research Center on Software Production Methods (PROS)
Universitat Politècnica de València, Spain
jreyes@pros.upv.es

José F. Reyes R. is a researcher at PROS Research Center at Universitat Politècnica de València (Spain). He holds a Ph.D. in Computer Sciences (2018) from Universitat Politècnica de València (UPV, Spain), a MSc in Software Engineering, Formal Methods and Information Systems (2013) from UPV (Spain), a Diplomate of Analysts and Systems Designers (2011) and a University Degree in System Engineering (2010) from Universidad Central del Este (Dominican Republic). Currently, his main research activities are centered on the use of Conceptual Models for the development of Genomic Information Systems (GeIS). His main research interests include Conceptual Modeling, Genomic Data Science, Engineering Requirements, SE and Information Systems.

Program Committee

  • Giuseppe Agapito, Magna Graecia University, Italy
  • Samuele Bovo, University of Bologna, Italy
  • Bernardo Breve, Università degli Studi di Salerno, Italy
  • Mario Cannataro, Magna Graecia University, Italy
  • Stefano Cirillo, Università degli Studi di Salerno, Italy
  • Johann Eder, University of Klagenfurt, Germany
  • Jose Luis Garrido, University of Granada, Spain
  • Giancarlo Guizzardi, University of Twente, Netherlands
  • Khanh N.Q. Le, Taipei Medical University, Taiwan
  • Sergio Lifschitz, Pontifical Catholic University of Rio de Janeiro, Brazil
  • Paolo Missier, Newcastle University, United Kingdom
  • José Palazzo, Federal University of Rio Grande do Sul, Brazil
  • Ignacio Panach, University of Valencia, Spain
  • Barbara Pernici, Polytechnic University of Milan, Italy
  • Rosario Michael Piro, Polytechnic University of Milan, Italy
  • Maria Rodriguez Martinez, IBM Zurich Research Laboratory, Switzerland
  • Monjoy Saha, National Cancer Institute, USA
  • Domenico Vito, Università degli Studi di Pavia, Italy
  • Emanuel Weitschek, Uninettuno University, Italy

Program

TBD

Collaborations

This workshop is supported by the data-driven Genomic Computing group at Politecnico di Milano and by the VRAIN Research Center at Universitat Politecnica de Valencia (INNEST/2021/57 - Agència Valenciana de la Innovació and PDC2021-121243-I00 - Spanish State Research Agency)

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