[CFP]: 9th International Workshop on SEMANTIC WEB SOLUTIONS FOR LARGE-SCALE BIOMEDICAL DATA ANALYTICS (SeWeBMeDA-2026)- Dubrovnik , Croatia

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  Call for Papers to the International Workshop on

 "*9th International Workshop on SEMANTIC WEB SOLUTIONS FOR LARGE-SCALE
BIOMEDICAL DATA ANALYTICS (SeWeBMeDA-2026)*"

co- event with Extended Semantic Web Conference 2026, Dubrovnik , Croatia

website:  https://sewebmeda-workshop.github.io/sewebmeda26/index.html



*IMPORTANT DATES*
(All dates midnight Hawaii Time)

Submission deadline: Feb 25, 2026

Notifications: March 31, 2026

Camera-ready version: April 17, 2026

Workshop days: *May 10 or 11, 2026*





This workshop invites papers for life sciences and biomedical data
processing, as well as the amalgamation with Data and c Web technologies
for better data analytics, knowledge discovery and user-targeted
applications.

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 visualization 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 visualization, 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 Web and Data
technologies in the following areas:

   1. Data Integration
      - Dataspaces, data warehouses, and database solutions in healthcare
      and life sciences
      - Large-scale curation, integration, processing, and analysis of
      heterogeneous biomedical data
      - Cleaning, quality assurance, and provenance tracking for life
      sciences data
      - Biomedical data quality assessment and improvement
      - Implementation, governance, and assessment of FAIR data principles
      in life sciences
      - Data and metadata publishing, profiling, and discovery of new
      biomedical datasets
      - Data streams, Internet of Things, mobile platforms, cloud
      environment in life sciences
   2. Knowledge Representation
      - Biomedical ontology creation, mapping/ matching/ translation and
      reconciliation
      - Building and maintaining knowledge graphs in healthcare and life
      sciences
      - Knowledge graph enrichment using text mining and natural language
      processing techniques
      - Visualization and exploration of linked data, ontologies, and
      knowledge graphs in life sciences
   3. AI/ML/Reasoning over Ontologies and Knowledge Graphs
      - ML and relational learning over biomedical knowledge graphs
      - Neurosymbolic AI and hybrid reasoning approaches for biomedical data
      - Large language models integrated with biomedical knowledge graphs
      - Explainable AI approaches leveraging semantic technologies in life
      sciences
   4. Applications and Use Cases
      - Semantic technologies supporting research and clinical applications
      in life sciences
      - Querying and federating data over heterogeneous data sources
      - Virtual and augmented reality in life sciences education and
      applications
      - Generative AI and conversational AI applications in life sciences
   5. Ethical, Social, and Practical Considerations
      - Risks and opportunities of using Semantic Web and AI technologies
      in life sciences
      - Bias and fairness in AI systems for healthcare and life sciences
      - Challenges of explainability and accountability in AI systems for
      healthcare and life sciences
      - Responsible development of neuro-symbolic and generative AI in
      clinical workflows


 *JOURNAL OF BIOMEDICAL SEMANTICS*

*Top selected manuscripts will be invited for submitting paper for the
special call at "Journal of Biomedical Semantics"*

*SUBMISSIONS**: *Workshop accepts following types of submissions:

·       *Full papers (up to 15 pages)*: Presenting novel scientific
research pertaining to topics relevant for workshop topics.
·       *Short papers (up to 8-10 pages):* New system and Dataset
descriptions, relevant to the topics of interest.
·       *Demo/Poster papers (up to 4 pages):* Describe a demo or poster of
a tool on the workshop topics.
·       *Position Paper (up to 6 - 8 pages)*.
·       *European/ International Project Showcase (up to 6-8 pages)*:
Introduce and disseminate the findings from ongoing and/or recently (within
last12 months of this workshop) finished project.
·       *Work-In progress (up to 5-10 pages)*: Ideal opportunity to submit
the incomplete results/ trends and receive feedback from experts in the
area.

*Submissions* must be in English formatted in the style of the Springer
Publications format for Lecture Notes in Computer Science (LNCS)
instructions available at:
https://sewebmeda-workshop.github.io/sewebmeda26/call.html
*Workshop accepts PDF submissions only.*

Papers should be submitted through the EasyChair system (
https://easychair.org/conferences?conf=sewebmeda2026) no later than
midnight Feb* 25, 2026, midnight Hawaii Time* . Submissions will be
reviewed by members of the workshop program committee. Papers will be
evaluated according to their significance, originality, technical content,
style, clarity, and relevance to the workshop.



*ORGANISERS & CONTACT INFORMATION : * *(* sewebmeda@gmail.com  *)*

·       Dr. Ali Hasnain

·       Prof Dr. Michel Dumontier

·       Dr Rita T Sousa