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The Flavor of Complexity
Dan Barber, pioneer of the farm-to-table movement and James Beard award-winning chef, has a single, elegant term for the complex fabric of molecules, processes, and sequences that underpins great food: flavor.
Like great chefs, computer scientists grapple with complexity, seeking elegant ways to model and analyze increasingly complex--or perhaps, flavorful--phenomena. Across many business verticals, we are seeing knowledge graphs being leveraged to capture and model complexity, and food supply is no exception.
The emerging and relatively large interest area of knowledge graphs in food is composed of a wide range of interconnected domains: weather, soil science, plant breeding, farming, food processing, distribution, farmers markets, restaurants, groceries, schools, and so on.
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Resilience requires a whole systems approach
Knowledge graphs have the power to enable a more resilient, distributed food network, matching small-scale food producers and regional food processors directly to demand, and producing cascading benefits for local communities and environment.
To do so, we would need to link the relevant food data, to understand and leverage the inherent context of these nested systems and to enable critical information-sharing and communication.
The opportunity here is immense: transforming food consumption patterns – measured in $ trillions – would impact also on other areas of concern: energy use, carbon footprint, rural economics, chronic illness rates, desertification, rise of epidemics, etc.
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Image adapted from Bartos et al.
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EXPLORING NEW FOOD PATHWAYS
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The UN SDGs Clearinghouse
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At KGC 2020, the UN hosted a workshop together with Accenture Labs to explore how linked data projects can address the Sustainable Development Goals, several of which are interrelated with food security and health.
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The UN is inviting projects to be formulated throughout 2020, to be shared at next May’s KGC conference and collected under a Clearinghouse on the UN website. Echoing the words of UN Director Salem Avan, in what ways can kg technologies be leveraged to exchange ideas and facilitate paradigm-shifting solutions to global issues? Check out the winner of a related UN challenge for some inspiration.
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Healthy food suggestions for diabetics
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KGC Community member Oshani Seneviratne shares how RPI+IBM built a food kg to help diabetics and other sufferers of chronic disease self-manage their health through better food choices, enabled by a recipe kg.
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The project leverages the MIT recipe1M dataset, FoodOn concepts, and USDA data, together with NLP techniques (e.g, fuzzy matching and word embeddings, and semantic web techniques, such as semantic data dictionaries).
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- KGC co-founder François Scharffe is one of the creators of the Food Ontology, which describes ingredients and food products and is used by the Open Food Facts dataset.
- Luigi Assom uses knowledge graphs to model food networks and inform sustainability-oriented projects. Check out his presentation from the UN workshop here.
- Celia Ji is building her first-ever knowledge graph, which just so happens to be food-related. Looking to gain experience with building a kg as well? Reply to this email or on Slack to collaborate with her.
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DBPedia maintains an open-source knowledge graph, containing over 20 billion facts across domains. It's a common data source to start with for projects, such as this Food Waste Ontology.
If you're not familiar with DBPedia, it is a platform that enables the Wikipedia knowledge base to be combined with tools for ad-hoc structured data querying, business intelligence & analytics, entity extraction, natural language processing, reasoning & inference, machine learning services, and artificial intelligence generally.
It's a good time to learn how to get started with the DBPedia--they are running their 2nd ever tutorial on the DBPedia Stack next Tuesday, September 2nd, from 5-6 pm CEST.
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