Thank you for everyone who joined the workshop and to all presenters for sharing their interesting research!
We made a compilation of the workshop presentations. You can watch it here on YouTube.
Check also the Program (at the end of the page) for slides and videos of each video (we will keep loading them as we get permission from the authors).
The recent advances in unravelling the secrets of human conditions and diseases have encouraged new
paradigms for their prevention, diagnosis and treatment. As the information is increasing at
unprecedented 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 proposed workshop aims at being, both, a starting meeting point for Information Systems,
Conceptual Modeling, and Data Management researchers working on health care and life science
problems, and 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 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 disease, the joined research communities of Information Systems,
Conceptual Modeling, and Data Management have an important role to play; they must help in providing
feasible solutions for a high-quality and efficient health care.
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 particular research methods and we will consider both conceptual and empirical research, as well as novel applications.
The topics of interest include, but are not limited to:
We invite submissions of high quality papers describing original and unpublished results regarding
any of the workshop’s topics of interest.
CMLS 2020 proceedings will be part of the ER 2020
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=cmls2020.
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 2020 will be electronically only.
For the preparation of their manuscript camera-ready version, authors should consult Springer’s
authors’ guidelines
and use their proceedings
templates, either for LaTeX or for Word,
for the preparation of their papers. The page limit for workshop papers is 10 pages, as for the
previously submitted version.
Springer encourages authors to include their ORCIDs in their papers.
In addition, the corresponding author of each paper, acting on behalf of all of the authors of that
paper,
must complete and sign a Consent-to-Publish
form.
The corresponding author signing the copyright form
should match the corresponding author marked on the paper.
Once the files have been sent to Springer, changes relating to the authorship of the papers cannot
be made.
We reached a preliminary agreement with BMC Bioinformatics journal (2-year IF 2.511, SJR 1.374) for a post-conference supplement related to Conceptual Modeling in Life Sciences. All the papers accepted to our workshop will be invited to submit a revised and extended version to the journal supplement.
For the best paper of the workshop (as assessed by the evaluations of the members of the Program Committee) the Article Processing Charges of the BMC Bioinformatics supplement will be fully covered by the organizers (GeCo at Politecnico di Milano & PROS at Universitat Politècnica de València).
The registration for the workshop is open via the ER website. At least one of the authors for each accepted paper must have an "Author Registration" (registration fee of € 150,-.) and attend the online conference for paper presentation.
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 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, 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 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.
We are glad to announce the CMLS 2020 Keynote Talk by
Paolo Missier: "Optimising the re-execution of analytics pipelines in response to
changes in the data: current results, open problems, and opportunities".
Paolo Missier is Professor of Big Data Analytics
with the School of Computing at Newcastle University,
with 20 years experience in CS research, development, and research management.
The broad goal of his research is to understand the role of metadata, most notably data provenance,
in making sense of the underlying (big) data as well as improving and optimising the processes that
produce and extract added value from the data (i.e. through "big data" analytics)—he calls
this
metadata analytics.
He has been leading (as Principal Investigator) the ReComp project (2016-2019, EPSRC) focused on
preserving value from large-scale data analytics over time through selective re-computation
(http://recomp.org.uk/)
where the challenge of collecting provenance metadata and extracting value from it through
analytics techniques is central to the research.
His talk will be focused on — but not limited to — the results of ReComp project and
explain
its application to Genomics and to the Simple Variant Interpretation (SVI) workflow.