July's data meetup will be dedicated to highlighting the great work going on in data in Aberdeen.
Whether you are a data scientist, a researcher, or working with kids in the local community to understand and use data, come along, share your passion and listen to others.
If you want to grab a slot please email ian[at]codethecity[dot]co[dot]uk.
18:30 pizza and beer.
7pm - Autonomous Learning.
Pascal Chinedu will speak about his project which seeks to develop a learning algorithm that would allow an intelligent agent exhibit a high degree autonomy by interacting with it's environment. This integrates ideas from reinforcement learning; developmental psychology and supervised learning such as ANN.
7.20pm - free slot
7.45pm. Open Data Community - update.
Thanks to MBN Solutions and Data Lab Scotland for sponsoring this event.
Pascal will speak about his project which seeks to develop a learning algorithm that would allow an intelligent agent exhibit a high degree autonomy by interacting with it's environment.
This integrates ideas from reinforcement learning; developmental psychology and supervised learning such as ANN.
***************************
7.30pm - What can big data do for conservation? Modelling the distribution of wildlife watchers using social media - Francesca Mancini.
Wildlife watching activities are recognised as potential threats to the targeted wildlife. More than 5000 species are affected by tourism, and over 1000 of these species are Endangered or Critically Endangered. It is therefore extremely important to quantify these recreational activities in order to identify areas of conflict between humans and biodiversity, where high visitation could jeopardise the conservation status of the wildlife.
The widespread use of the Internet and social media offers the opportunity to use the data generated by their billions of users. We used pictures of wildlife posted on Flickr to quantify wildlife watching activities in Scotland. We first validated the use of this proxy by comparing it to visitor statistics collected through surveys. We then tested the effect of different environmental variables on the number of tourists visiting a certain area, such as the presence of different types of nature reserves or protected areas, and the presence of different types of infrastructures.
By using this novel data collection technique, we were able to make more precise inference on tourists’ preferences on larger areas. This information has implications for management and for conservation. It can be used to identify areas that are particularly vulnerable due to tourism pressure and need to be protected, thus helping with conservation prioritisation, and to inform sustainable planning of tourism development.
Francesca Mancini is an interdisciplinary conservation scientist. She uses computational methods and unconventional data sources to investigate sustainability of socio-ecological systems.
She has an undergraduate degree in Biological Sciences from La Sapienza University of Rome. After graduating Francesca moved to Aberdeen where she obtained a Master of Research in Applied Marine and Fisheries Ecology. She is currently completing her PhD in Ecology at the University of Aberdeen and her research focuses on sustainable management of wildlife tourism.
******************************
Thanks to MBN Solutions and Data Lab Scotland for sponsoring this event.
*****************************
Photo by Filios Sazeides on Unsplash.
