Dettagli

Data Science Solutions to Address Environmental Challenges

7. novembre 2024, Ore 16:00 - Ore 17:00

Eawag Dübendorf, room FC-C20 & Online

Speaker
Dr. Robert M. Waterhouse, Director, Environmental Bioinformatics Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland

The seminar is open to the public. To join online, please contact seminars@eawag.ch for access details

Abstract

In September 2023 the SIB Swiss Institute of Bioinformatics launched the Environmental Bioinformatics Group, directed by Robert Waterhouse. The mission of the new group is to develop and extend SIB’s activities and research portfolio in planetary health informatics: data science solutions to address environmental challenges. The group strives to build capacities in coordinating biodata resources and developing data science tools and services that contribute to environmental preservation and restoration by addressing the global crisis and delivering benefits for society. One initial focus is on genomics data, as part of developing the broader biodiversity knowledge graph to connect and integrate diverse data types for enhanced understanding and monitoring of the health of species and ecosystems. Here the group is deeply involved in coordinating and leading European efforts for scaling up production of biodiversity genomics data and building data management infrastructures required for efficient processing and open data sharing. The group’s research focus is on downstream analyses: data science methods for developing the computational biology tools required to make sense of the molecular data in the context of connected knowledge, extracted from the scientific literature, or from species and environment observation and monitoring data, or from natural history collections and species trait information. Working with key partners in the domain like Eawag, the group aims to meet key needs in data collection, integration, and analysis, as well as facilitating the development of informatics tools and services to support data-driven, empirically informed, and model-guided policies and actions addressing environmental challenges.