BFNDMA 2019 : Big Food and Nutrition Data Management and Analysis
Call For Papers
We are organizing the workshop “Big Food and Nutrition Data Management and Analysis (BFNDMA 2019)” at the 2019 IEEE International Conference on Big Data (http://cs.ijs.si/bfndma/BFNDMA.html) in Los Angeles, CA, USA.
The United Nations states “End hunger, achieve food security and improved nutrition and promote sustainable agriculture" as one of its sustainable development goals by the target date of 2030. To achieve these goals, global food and agriculture systems will require profound changes, in which big data and AI technologies can play significant roles. In the past decade, a huge amount of work has been done in biomedical predictive modeling. This would not be possible without the existence of diverse biomedical vocabularies and standards, which play a crucial role in understanding biomedical information, together with a large amount of biomedical data collected (e.g., drug, diseases and other treatments) from numerous sources. While there are extensive resources available for the biomedical domain, the food and nutrition domain is relatively low resourced. For example, there is no publicly available annotated corpus with food and nutrient concepts, and there are few food named-entity recognition systems for the extraction of food and nutrient concepts. In addition, the available food ontologies are developed for a very narrow use cases, and there are no links between these ontologies that can be used for food and nutrition data management.
In this workshop, we aim to focus primarily on methodologies for the management and analysis of food- and nutrition-related big data. BFNDMA 2019 will consider original and unpublished research articles that propose bold steps towards addressing the challenges of data management and analysis of food- and nutrition-related data. We welcome data-driven and rule-based approaches related to food and nutrition problems.
TOPICS OF INTEREST RELATED TO FOOD AND NUTRITION
- Information retrieval, information extraction, natural language processing techniques, computer vision - and artificial intelligence;
- Data normalization;
- Knowledge representation;
- Ontologies, vocabularies and ontology design patterns, with a focus on describing the modelling process;
- Crowdsourcing task designs that have been used and can be (re)used for building resources such as gold standards;
- Data mining and knowledge discovery;
- Analytics, including social media, text, or structured datasets;
- Recommendation of food, menu, or food- and nutrition-related habits;
- Policy analysis and recommendations relevant to citizens and governments;
- Wearable devices, quantified-self data for food, nutrition, and health.
- Prof. Karl Aberer, PhD, Ecole polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Prof. Nada Lavrač, PhD, Jožef Stefan Institute, Ljubljana, Slovenia
- Prof. Kari Nadeau, MD, PhD, Stanford University, CA, USA
Please submit a full-length paper (up to 10 page IEEE 2-column format), or short or position paper (2-4 page IEEE 2-column format), through the online submission system.
Paper Submission Page Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines.
Paper submission: Sep 15, 2019
Decision notification: Oct 15, 2019
Camera-ready submission: Nov 15, 2019
Workshop: Dec 9-12, 2019
- Tome Eftimov, PhD, Stanford University, CA, USA
- Bibek Paudel, PhD, Stanford University, CA, USA
- Prof. Barbara Koroušić Seljak, PhD, Jožef Stefan Institute, Ljubljana, Slovenia