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SeWeBMeDA 2019 : Third Workshop on Semantic Web solutions for large-scale biomedical data analytics


When Oct 26, 2019 - Oct 27, 2019
Where Auckland New Zealand
Submission Deadline Jun 28, 2019
Notification Due Jul 24, 2019
Final Version Due Aug 20, 2019
Categories    semantic web and linked data   biomedical, bio informatics   healthcare and life scieces   large scale data analytics

Call For Papers

SeWeBMeDA-2019: Semantic Web solutions for large-scale biomedical data analytics
Workshop at ISWC2018, Auckland, New Zealand on 26th or 27th of October 2019

Submission deadline: June 20, 2019 , mid night Hawaii Time
Notifications: July 24, 2019 , mid night Hawaii Time
Camera-ready version: August 20, 2019 , mid night Hawaii Time


A study from EMC in 2014 predicts the doubling of the available data in the “Digital Universe” every two years between now and 2020. This rapid growth is a challenge for society – how to put the available data to use effectively? This is a challenge in many areas including Medicine and Life Sciences as well as areas in Engineering and Science, which depend on data such as Energy and Materials research. Advanced technologies and the emerging Open Data phenomenon produce an ever-increasing amount of data, which needs to be interpreted and examined. To turn data into knowledge, data scientists need to effectively process, filter, interpret cluster and learn from the available data. This process currently is largely unsupported – data scientists are spending time and money on processing data, configuring infrastructure, writing code etc., which is a large loss of productivity and unexploited opportunities, if data scientists with the necessarily skills are available at all.

To meet these challenges technologies from different areas need to be combined which help to execute computationally demanding tasks.

Linked Data and Semantic Web technologies, coming from a different direction, help to bring heterogeneous data sources together to exploit and make sense of different datasets and making it easier to process semantically heterogeneous data.

This workshop aims to accept papers 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. Workshop 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.

Key Aims and Learning Objectives

Provide basic knowledge regarding the fundamentals of Large Scale Data in Life Sciences and related technologies.
Elaborate how semantic web technologies are useful for managing Large Scale Data.
Scalable integration and reproducible analysis of FAIR (Findable, Accessible, Interoperable and Reusable) data
Elaborate how to access and benefit from semantic data on the Web.
Elaborate how to make use of Large Scale Data and introduce some of the current applications based on Semantic Web technologies

Topics of interest include, but are not limited to Semantic Web and Linked Data technologies in the following areas:

- Techniques for analysing semantic data in the life sciences, medicine and health care
- The description, integration, analysis and use of data 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
- FAIR (Findable, Accessible, Interoperable and Reusable) publishing, usage and analysis of biomedical/ life science data
- Scalable integration and reproducible analysis of FAIR (Findable, Accessible, Interoperable and Reusable) data
- Querying and federating data over heterogeneous datasources
- 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
- 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 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.

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

Workshop accepts four 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 pages): Position papers, 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).

Submissions must be in English formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). For details on the LNCS style, see Springer’s Author Instructions.
We accept PDF submissions only.

Papers should be submitted through the EasyChair system no later than midnight June 20, 2019, 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. Camera-ready version: August 20, 2019, mid night Hawaii Time.

Proceedings of SeWeBMeDA-2019 are planned to published at CEUR Workshop Proceedings

- Following is the list of (confirmed) program committee members not in any particular order:
- Michel Dumontier - Maastricht University, Netherlands
- Qurratal Ain Fatimah - University Hospital Galway, Ireland
- M. Scott Marshall - Netherlands Cancer Institute, Netherlands
- Holger Stenzhorn Saarland University Hospital, Germany
- Vit Novacek - Insight Centre, NUI Galway, Ireland
- Muhammad Saleem - AKSW- University of Leipzig, Germany
- Mikel Egaña Aranguren - Eurohelp Consulting , Spain
- Adrien Coulet - LORIA - INRIA Nancy-Grand Est, France
- Dietrich Rebholz-Schuhmann - Insight Centre, NUI Galway, Ireland
- Claudia d'Amato - Università degli Studi di Bari
- Robert Hoehndorf - King Abdullah University of Science and Technology
- Oya Beyan - RWTH Aachen University
- Jodi Schneider - University of Illinois
- Alasdair Gray - Heriot-Watt University

• Dr. Ali Hasnain (CHAIR), (ali.hasnain['at'] Insight Centre for Data Analytics, National University of Ireland, Galway
• Dr Vit Novacek, Insight Centre for Data Analytics, National University of Ireland, Galway
• Prof Dr. Prof Michel Dumontier, Maastricht University Netherlands
• Prof Dr. Dietrich Rebholz-Schuhmann Scientific Director of ZB MED – Information Centre for Life Sciences, Cologne University

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