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https://ceur-ws.org/Vol-3726/preface.pdf
Proceedings of the 7th International Workshop on
Semantic Web Solutions for Large-scale Biomedical
Data Analytics - SeWebMeDa-2024
Ali Hasnain1 , Michel Dumontier2 , Alba Morales Tirado3 and
Dietrich Rebholz-Schuhmann4
1
Royal College of Surgeons, Ireland
2
Maastricht University, Maastricht, Limburg, NL
3
The Open University, United Kingdom
4
ZB MED, Cologne, DE
Abstract
This preface summarises the 7th International Workshop on Semantic Web Solutions for Large-scale
Biomedical Data Analytics (SeWebMeDa-2024), a co-event with The ESWC 2024: Extended Semantic
Web Conference, held on May 26th 2024 in Hersonissos, Greece.
1. Introduction
The seventh edition of this International workshop invites papers for life sciences and biomedical
data processing, as well as the amalgamation with Linked Data and Semantic Web technologies
for better data analytics, knowledge discovery and user-targeted applications. This research con-
tribution should provide useful information for the Knowledge Acquisition research community
as well as the working Data Scientist.
This workshop at the Extended Semantic Web Conference (ESWC) seeks original contributions
describing theoretical and practical methods and techniques that present the anatomy of large-
scale linked data infrastructure, which covers: the distributed infrastructure to consume, store
and query large volumes of heterogeneous linked data; using indexes and graph aggregation to
better understand large linked data graphs, query federation to mix internal and external data
sources, and linked data visualisation tools for health care and life sciences. It will further cover
topics around data integration, data profiling, data curation, querying, knowledge discovery,
ontology mapping / matching / reconciliation and data / ontology visualisation, applications /
tools / technologies / techniques for life sciences and the biomedical domain. SeWeBMeDA aims
to provide researchers in biomedical and life science, an insight and awareness about large-scale
SeWebMeDa-2024: 7th International Workshop on Semantic Web solutions for large-scale biomedical data analytics,
May 26, 2024, Hersonissos, Greece
Envelope-Open alihasnain@rcsi.ie (A. Hasnain)
GLOBE https://www.rcsi.com/people/profile/alihasnain (A. Hasnain)
Orcid 0000-0003-4014-4394 (A. Hasnain); 0000-0003-4727-9435 (M. Dumontier); 0000-0001-6984-5122 (A. M. Tirado);
0000-0002-1018-0370 (D. Rebholz-Schuhmann)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
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http://ceur-ws.org
ISSN 1613-0073
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Proceedings
data technologies for linked data, which are becoming increasingly important for knowledge
discovery in the life sciences domain.
Topics of interest include, but are not limited to Semantic Web and Linked Data technologies
in the following areas:
• Generative AI and conversational AI applications in healthcare and life sciences
• New technologies and exploitation of existing ones in Linked Data, Semantic Web and
Large Language Models (LLMs).
• Techniques for analyzing semantic data in the life sciences, medicine and healthcare
• Integration, analysis and data use in pursuit of challenges in the life sciences, medicine
and health
• Tools and applications for biomedical and life sciences
• Large-scale biomedical data curation and integration
• Processing biomedical data at scale
• Knowledge representation and knowledge discovery for biomedical data
• Data and metadata publishing, profiling and new datasets in biomedical and life sciences
• Question answering over biomedical/ life science Linked Data, Ontologies and Knowledge
Graphs
• Querying and federating data over heterogeneous data sources
• Biomedical ontology creation, mapping/ matching/ translation and reconciliation
• Biomedical Ontology and data visualisation
• Building and maintaining biomedical knowledge graphs
• Machine learning with biomedical knowledge graphs
• Virtual and Augmented Reality in Biomedical/ Life Science education and applications
• Risks and opportunities of using Semantic Web technologies in Healthcare and Life
science
• Data resources, tools and technologies relevant to research COVID-19 pandemic
• Cleaning, quality assurance, provenance of data, services and processes in Biomedical/
Life Science
• Knowledge Graphs and Relational Learning for Life Sciences
• Intelligent Visualisations of Linked Life Science Data
• Biomedical data quality assessment and improvement
• From Semantics to Explanations in biomedicine and life sciences
• Data streams, Internet of Things, mobile platforms, cloud environment in life science
• Text analysis, text mining and reasoning using semantic technologies
• New technologies and exploitation of existing ones in Linked Data and Semantic Web
• Social, ethical and moral issues publishing and consuming biomedical and life sciences
data
2. Organisation
2.1. Workshop Chairs
• Ali Hasnain, Royal College of Surgeon, Ireland.
• Michel Dumontier, Maastricht University, Maastricht, Limburg, NL.
• Alba Morales Tirado, The Open University, United Kingdom.
• Dietrich Rebholz-Schuhmann, ZB MED, Cologne, DE.
2.2. Programme Committee
• Ali Hasnain, Royal College of Surgeon, Ireland
• Maria Esther-Vidal, Leibniz University Hannover
• Remzi Çelebi Maastricht University
• Claudia D’Amato University of Bari
• William Van Woensel, University of Ottawa
• Holger Stenzhorn, University of Tübingen
• Shruthi Chari, Rensselaer Polytechnic Institute
• Catia Pesquita, LaSIGE, Faculdade de Ciências, Universidade de Lisboa
• Dietrich Rebholz-Schuhmann,ZB MED Cologne, DE
• Michel Dumontier, Maastricht University, NL
• Sabbir Rashid, Rensselaer Polytechnic Institute
• Mikel Egaña Aranguren, University of Basque Country (UPV/EHU)
• Alba Morales Tirado, The Open University, UK