BlueBRIDGE organized a webinar on 30 May 2017, 11am CEST with the aim to showcase how the BlueBRIDGE VREs can enable data sharing and experiments reproducibility and repeatability in the biodiversity conservation field. Examples of tools that can be adopted by the audience were also showcased.
 

 

Webinar Description

An e-Infrastructure is a distributed network of service nodes, residing on multiple sites and managed by one or more organizations. E-Infrastructures allow scientists residing at distant places to collaborate. They offer a multiplicity of facilities as-a-service, supporting data sharing and usage at different levels of abstraction, e.g. data transfer, data harmonization, data processing workflows etc. e-Infrastructures are gaining an important place in the field of biodiversity conservation. Their computational capabilities help scientists to reuse models, obtain results in shorter time and share these results with other colleagues. They are also used to access several and heterogeneous biodiversity catalogues. This webinar focused on how the BlueBRIDGE e-Infrastructure and Virtual Research Environments can enable data sharing and experiments reproducibility and repeatability in the biodiverisity conservation field. Examples of tools that can be adopted by the audience were also showcased. Webinar contents in brief:       

  • e-Infrastructures and Virtual Research Environments
  • Geospatial data visualization and representation
  • Statistical models for species distribution modelling
  • Accessing large heterogeneous biodiversity data catalogues
  • Signal processing of biodiversity-related observations
  • Machine Learning applied to species observation records
  • Lexical search in large taxonomic trees
  • Cloud computing applied to biodiversity analyses

Webinar info:

Presenter: Gianpaolo Coro, CNR-ISTI & BlueBRIDGE consortium
Duration: 1 hour
Start date: 30 May 2017
Start time: 11 am CEST
Timezone: Rome

 

Speaker profile 

Gianpaolo Coro is a Physicist with a Ph.D. in Computer Science. His research focuses on Artificial Intelligence, Data Mining and e-Infrastructures. He has been working for more than fifteen years on Machine Learning and Signal Processing with applications to Computational Biology, Brain Computer Interfaces, Language Technologies and Cognitive Sciences. The aim of his research is the study and experimentation of models and methodologies to process biological data and to apply the results to fields in Ecological Modelling, Vessel Monitoring Systems and Ecological Niche Modelling with an approach oriented to Science 2.0. His approach relies on distributed e-Infrastructures and uses parallel and distributed computing via Grid- and Cloud-based technologies. He is one of the authors of the CMSY model for stock assessment in data-limited scenarios.