Workshop Description
DECOR 2022 envision that this workshop will continue:
The past decade has seen an enormous growth in the research related to the digital food and cooking recipes underpinnings of data engineering, as food is essential for human life and related health. The ability to collect, store, process, and evaluate cooking recipes has advanced immeasurably, and data science-driven methods have had unprecedented impact on food experience sharing and recommendations at large, mainly because of their success in analysing and predicting human cooking expectation, flavour, and taste preferences. Data Engineering stands to benefit from the food computing and recipe cooking revolution in similar ways, but realizing this vision requires thoughtful and concerted effort.
The 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 workshop is specifically focused on data science innovations that accelerate the organization, integration, access, and sharing of digital objects in support of the Intelligent Food and Cooking Recipes domain. This domain comprises not only the process of cooking, but also includes intelligent methods for enhancing human-food interactions, ranging from devising technology, playful interactions, multisensory experience design, understanding cross-cultural food eating habits and perception, as well as food choices and their health connections. Consequently, increasing the ability of influencing food eating habits and choices that promote, simultaneously, healthful eating-decisions and creative new human-food interaction experiences.
According to Trends on the Gartner Hype Cycle for Artificial Intelligence, Data Engineering will contribute to solve the complexity of a human-centred partnership model of people and AI working together to enhance cognitive performance related to sharing dish tasting experiences. Resilience and real-time adaptability are essential for health monitoring and predictive maintenance of complex food menus and diets where data-driven decisions can improve health and dish experience quality. The research design itself will enable us to integrate the user requirements and expectations, where data-driven modelling can accelerate the design cycle while yielding more capable and predictable social media tools for food experience and recommendation sharing.
Authors will be 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 will 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 objects that are produced. These digital objects might include original data, software, software pipelines, models, workflows, containers, virtual machines, intermediary data, and metadata strategies.
Timetable
Important Dates
First round:
Second round:
Workshop Format
Notes on Workshop Research Papers
Organizing Committee
Co-organizers:
Steering committee members: