Summary of The Knowwheregraph Ontology, by Cogan Shimizu et al.
The KnowWhereGraph Ontology
by Cogan Shimizu, Shirly Stephe, Adrita Barua, Ling Cai, Antrea Christou, Kitty Currier, Abhilekha Dalal, Colby K. Fisher, Pascal Hitzler, Krzysztof Janowicz, Wenwen Li, Zilong Liu, Mohammad Saeid Mahdavinejad, Gengchen Mai, Dean Rehberger, Mark Schildhauer, Meilin Shi, Sanaz Saki Norouzi, Yuanyuan Tian, Sizhe Wang, Zhangyu Wang, Joseph Zalewski, Lu Zhou, Rui Zhu
First submitted to arxiv on: 17 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary KnowWhereGraph is a massive publicly available knowledge graph that integrates data from 30 layers on various topics, including natural hazards, climate variables, soil properties, demographics, and human health. The graph has been used in applications addressing food security, agricultural supply chains, sustainability, farm labor, and emergency humanitarian aid. This paper introduces the ontology that serves as the schema for KnowWhereGraph, outlining its design specifications, development methodology, and resources utilized to implement and deploy it with end-user interfaces and a public query SPARQL endpoint. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary KnowWhereGraph is a big database that helps people make sense of lots of information about the world. It has 30 layers of data on things like weather, soil, and people. People use this data to solve problems like getting food to those who need it after a disaster or making sure farmers are treated fairly. This paper tells us how they created the rules that help organize all this information, so we can better understand it. |
Keywords
» Artificial intelligence » Knowledge graph