SeWeBMeDA-2025

8th Workshop on Semantic Web Solutions for Large-scale Biomedical Data Analytics

co event with The ESWC 2025: Extended Semantic Web Conference

1st of June 2025

Portorož, Slovenia

Final Submission deadline: March 24, 2025

The life sciences domain has been an early adopter of linked data and, a considerable portion of the Linked Open Data cloud is composed of life sciences data sets. The deluge of inflowing biomedical data, partially driven by high-throughput gene sequencing technologies, is a key contributor and motor to these developments. The available data sets require integration according to international standards, large-scale distributed infrastructures, specific techniques for data access, and data analytics. In combination, Semantic Web and Linked Data technologies, promise to enable the processing of large and semantically heterogeneous data sources capturing new knowledge from those.

This 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 contribution should provide useful information for the Knowledge Acquisition research community as well as the working Data Scientist.

This workshop 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 biomedical domain. SeWeBMeDA aims to provide researchers in biomedical and life science, an insight and awareness about large-scale 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).
Artificial intelligence including Neurosymbolic AI in health care and life science.
Dataspaces, Datawarehouse and Database Solutions and applications in Healthcare and life sciences.
Techniques for analyzing semantic data in the life sciences, medicine and healthcare
Integration, analysis & data use in pursuit of challenges in the life sciences, medicine & 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 visualization
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 & processes in Biomedical/ Life Science
Knowledge Graphs and Relational Learning for Life Sciences
Intelligent Visualizations 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

Proceedings

The Proceedings of SeWeBMeDA-2025 are planned to be published at CEUR Workshop Proceedings