Date : 2022-09-19
Lieu : Online Event
Paper submission deadline: 20 June 2022
Paper acceptance notification: 13 July 2022
Workshop date: Monday, Septembre 19th, 2022 (to be confirmed)
After many years of decline, the number and severity of food insecurity situations is growing again in recent years all over the world. Multiple and interrelated reasons can be identified for this generalized rise in hunger situations, that make it challenging to monitor an extremely complex phenomenon such as food security. While great quantities of open data are available, that are related at different levels with food security, there is a urgent need to develop advanced data science techniques able to process this data in order to produce effective answers to food security related problems.
The goal of the Open-SOFOS workshop, to be held in conjunction with ECML/PKDD 2022, is to bring together researchers and practitioners from around the world interested in developing data science techniques for food security related problems, preferably using open access data. Even though the focus is on computer science, the themes of the workshop also encourage interdisciplinary discussion about topics touching different fields such social science, humanities and geography.
This will allow to get an insight in the current status of research in data science for food security, showing how the possibility to exploit massive quantities of open data in this context can make it possible to improve solutions to classic tasks (e.g., the ones addressed by the existing Food Security Systems), but also to focus on research questions and practical problems that have not been deeply investigated so far.
Topics of interest include, but are not limited to:
– Prediction of Food Security Indicators
– Poverty Prediction
– Agricultural Monitoring
– Prediction of Economical Indicators
– Social Media Analysis
– Evolutionary Systems
– Landscape Analysis
– Modeling of Spatial and Social Dynamics
– Mobility Problems
– Complex Network Models for Food Security
– Machine and Deep Learning methods for Food Security
– Text Mining Methods for Food Security
– Heterogeneous Data Integration Methods for Food Security
– KMS for Food Security
We welcome original contributions, either theoretical or empirical, describing ongoing projects or completed work.
Contributions can be of two types: either short position papers (up to 6 pages including references) or full research papers (up to 10 pages including references). Papers must be written in LNCS format, i.e., accordingly to the ECML-PKDD 2022 submission format.
Accepted contributions will be made available electronically through the CEUR Workshop Proceedings platform (http://ceur-ws.org).
Roberto Interdonato, CIRAD, UMR Tetis, Montpellier, France, firstname.lastname@example.org
Mathieu Roche, CIRAD, UMR Tetis, Montpellier, France, email@example.com
Giulia Martini, World Food Programme (WFP), Rome, Italy, firstname.lastname@example.org
Sabrina Gaito, Computer Science Department, University of Milan, Milan, Italy, email@example.com
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