Scientific Symposium
Developments in data science offer enormous opportunities for the agri-food chain and life sciences. Advances in information science and technology, data science and analytics, combined with domain specific developments are expected to enable breakthroughs in the agri-food domain. Wageningen University & Research is building on current efforts of applied data science and actively surveying its research domain for new opportunities.
The Wageningen Data Competence Centre – part of Wageningen University and Research – is organising a one-day Scientific Symposium on FAIR Data Science for Green Life Sciences. The symposium focuses on state-of-the-art knowledge in data science and data management, new applications in the green life sciences, insights from other domains that could be transferred, all based on the internationally recognized FAIR data principles. The symposium aims to bring together researchers and domain experts for discussion and exchange of ideas of the latest developments in data science as well as on the best practices within the green life sciences. The day will consist of several plenary sessions, and in-depth parallel sessions where you will be able to connect with experts from various fields.
Key note speakers
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Prof. Dr. Ir. Arthur Mol, Rector Wageningen University & Research
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Dr. Suzanne Pierce, Texas Advanced Computing Center at the University of Texas, Austin
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Prof. Dr. ir. Wilco Hazeleger, Netherlands eScience Center
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Prof. Dr. Jaap Heringa, Bioinformatics, Free University Amsterdam
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Dr. Peter Wittenburg, Max Planck Institute for Psycholinguistics, Nijmegen
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Patrick Schelvis MSc, Netherlands Ministry of Economic Affairs and Climate Policy
Call for Abstracts
Scientists are welcome to present their research during the plenary session or one of the parallel sessions of the symposium. Contributions reporting on original ongoing research, or recently published results are welcome in the fields of:
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Research data infrastructures, related to physical infrastructure, architecture and service layer design, data management, (high performance) computing tools and parallel processing methods.
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Data science and analytics, machine learning algorithms and applications, data driven hypothesis development and testing, pattern recognition, visualisation tools, predictive analytics.
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Applications in and cross-overs with the green life sciences.
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Secure data governance and data sharing with special attention to the protection of privacy and commercial interests.
Abstracts (max. 400 words) are expected before October 15th, 2018. Information on admission will be made available from November 1st, 2018. Contributions will be included in electronic conference proceedings, under an open licence.
Abstracts can be submitted here.
