The Third Workshop on Data Engineering meets intelligent food and COoking Recipes (DECOR) aims to accelerate research in data science by providing a forum for the latest innovations in the intersection of Data Engineering and Intelligent Food and Cooking Recipes. This domain comprises not only process of cooking and cooking execution plans, but also includes data-oriented intelligent methods for enhancing human-food interactions, which include several data engineering challenges. These range from devising technology, playful interactions, multisensory and mulsemedia experience design, understanding cross-cultural food eating habits and perception, devising efficient and economical methods to meals/menus preparation, as well as making appropriate food choices and health connections. Consequently, we hope to improve data management to increase the ability of influencing food eating habits and choices that promote, simultaneously, healthful eating-decisions and creative new human-food interaction experiences.

Special events:

Keynote Speakers
Interactive Panel Discussions
Enlightening Student session

The goal of this workshop is:

To promote discussions on how to push forward innovative solutions for the challenging problem on how to store, access and retrieve pertinent information and knowledge from an increasing amount of data available to everyone. Particularly, this workshop will address several challenges associated with the progress of the multiple aspects of the Intelligent Food and Cooking Recipes domain.

Authors are encouraged to submit contributions addressing a range of topics in the intersection of Data Science, Data Engineering and Applied Computational Science, with impacts on on-going standardization, especially in cooperation with ISO/IEC JTC 1/SC 42, international standards committee responsible for standardization in the area of Artificial Intelligence (AI). We call for contributions related to model design, use case best practices, technologies and intelligent data management tools supporting Intelligent Food and Cooking Recipes processes. In addition to primary investigations applying advanced analytic pipelines to data already stored in repositories, desirable contributions also include the reports of the full set of digital and/or mulsemedia - multiple sensorial media - objects produced. These digital objects might include original data, software, software pipelines, models, workflows, containers, virtual machines, intermediary data, and metadata strategies.

Important Dates. (updated)
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Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. Authors are invited to submit long papers (6 pages), or  short papers (4 pages), or demonstrations (4 pages).  Students are also invited to submit long papers and short papers in the special enlightening student session. All products for review must be submitted through EasyChair using the link https://easychair.org/conferences/?conf=decoricde2020

Topics of interest include, but are not limited to:

Foundation and Technologies for Intelligent Food and Cooking Recipes

- Data engineering and Design Science in the food domain
- Big Data and cooking recipes
- Cooking and recipe computing
- Nutrition data mining
- Cooking recipe benchmarking
- Data semantic modelling and ontology engineering for food data
- Recipe data management

Data Analytics in Recipe Computing

- Recipe data analytics
- Open cooking linked data analysis
- Food ontology
- Social data analysis for recipe computing
- Eating behavior analysis
- Culture analytics for food recommender system
- Multimedia food data analysis

Machine Learning and Deep Learning for Computational Cooking

- Multi-modal representation learning (Image/text alignment)
- Recommendation systems, benchmarking and performance evaluation
- Classification for food data
- Multi-modal retrieval techniques for recipe management
- Content generation for recipe computing

Collective intelligence for Recipe Computing

- Knowledge discovery from recipe computing
- Data visualization for food decision making
- Decision-making in intelligent food system
- Interactions in recipe computing
- Food recommender systems for group
- Data visualization for enhance food sensorial experience

Nutritional Value and Applications for Intelligent Food Systems

- Automated recipe and nutrients conversion
- Nutritional model for the intelligent food system
- Healthy eating models
- Health-aware food recommender systems
- Personalization and health model

To be included in the IEEE Xplore Library, accepted papers must be registered and presented.

Committees

Workshop co-chairs

• F. Andres, National Institute of Informatics, JP
• G. Ghinea, Brunel University, UK
• W. Grosky, University of  Michigan-Dearborn, US
• M. Leite, University of South  Florida  St.Petersburg, US

Publicity co-Chairs

• X. Dai, The University of North Carolina, Chapel Hill, US
• N. Ranasighe, Univ. of Maine, US

Program Committee

• R. Agrawal, ERDC, US
• C. Anutariya, AIT, TH
• Y. Asano, Kyoto U, JP
• M. Bhardwaj, Halliburton, US
• S. Bhattacharya, FSU, US
• M. Dolejsova, J. Ev. Purk. U. CZC
• X. Dai, The University of North Carolina, Chapel Hill, US
• K. Doman, Chukyo Univ., JP
• L. D’Orazio, IRISA, FR
• F. Fotouhi, WSU, US
• N. Holden, UCD, IR
• I. Ide, Nagoya U, JP
• M. Jaglan NIT Hamirpur, IN 
• D. Jannach, Tech. U. of Dort, DE
• R. Kannan, HBC, IN
• A. A. Krisnadhi, U. Indonesia, IDN
• N. Kumar, Rama U, IN
• D.L. Lee, HKUST, HK
• Y-K Ng, Brigham Young U., US
• A. Nijholt, U. of Twente, NL
• F. Ofli, QCRI, QA
• E. Ogasawara, CEFET/RJ, BR
• H. Pendharkar,  U Sth Fl St.Pbg, US
• O. Salviano, PUC, Campinas, BR
• C. A. S. Santos, UFES, BR
• F. Sedes, IRIT, Toulouse, FR
• H. Om Sharan, Rama U, IN
• C. Shimizu, Kansas State U., USA
• I. Weber, QCR Institute, QA
• K. Yanai, UEC, JP
• A. Ziviani, LNCC, BR

Steering Committee

• Hevner, Alan. University  of South  Florida, US
• Ioannidis, Yannis.  University  of Athens, GR
• Kapetanios, Epaminondas. University of Westminster, UK
• Kitagawa, Takuya. Rakuten, JP
• Levy, Pierre. University of Ottawa, CA
• Nuessli Guth, Jeannette. ETH Zürich, CH
• Yamakata, Yoko. The University  of Tokyo, JP
• Zhang, Aidong, State University of  NY at Buffalo, US

Contact

All questions about submissions should be emailed to one workshop co-chairs.