The KnowWhereGraph Ontology

Fuente: arXiv
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Autori principali: Shimizu, Cogan, Stephe, Shirly, Barua, Adrita, Cai, Ling, Christou, Antrea, Currier, Kitty, Dalal, Abhilekha, Fisher, Colby K., Hitzler, Pascal, Janowicz, Krzysztof, Li, Wenwen, Liu, Zilong, Mahdavinejad, Mohammad Saeid, Mai, Gengchen, Rehberger, Dean, Schildhauer, Mark, Shi, Meilin, Norouzi, Sanaz Saki, Tian, Yuanyuan, Wang, Sizhe, Wang, Zhangyu, Zalewski, Joseph, Zhou, Lu, Zhu, Rui
Natura: Preprint
Pubblicazione: 2024
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author Shimizu, Cogan
Stephe, Shirly
Barua, Adrita
Cai, Ling
Christou, Antrea
Currier, Kitty
Dalal, Abhilekha
Fisher, Colby K.
Hitzler, Pascal
Janowicz, Krzysztof
Li, Wenwen
Liu, Zilong
Mahdavinejad, Mohammad Saeid
Mai, Gengchen
Rehberger, Dean
Schildhauer, Mark
Shi, Meilin
Norouzi, Sanaz Saki
Tian, Yuanyuan
Wang, Sizhe
Wang, Zhangyu
Zalewski, Joseph
Zhou, Lu
Zhu, Rui
author_facet Shimizu, Cogan
Stephe, Shirly
Barua, Adrita
Cai, Ling
Christou, Antrea
Currier, Kitty
Dalal, Abhilekha
Fisher, Colby K.
Hitzler, Pascal
Janowicz, Krzysztof
Li, Wenwen
Liu, Zilong
Mahdavinejad, Mohammad Saeid
Mai, Gengchen
Rehberger, Dean
Schildhauer, Mark
Shi, Meilin
Norouzi, Sanaz Saki
Tian, Yuanyuan
Wang, Sizhe
Wang, Zhangyu
Zalewski, Joseph
Zhou, Lu
Zhu, Rui
contents KnowWhereGraph is one of the largest fully publicly available geospatial knowledge graphs. It includes data from 30 layers on natural hazards (e.g., hurricanes, wildfires), climate variables (e.g., air temperature, precipitation), soil properties, crop and land-cover types, demographics, and human health, various place and region identifiers, among other themes. These have been leveraged through the graph by a variety of applications to address challenges in food security and agricultural supply chains; sustainability related to soil conservation practices and farm labor; and delivery of emergency humanitarian aid following a disaster. In this paper, we introduce the ontology that acts as the schema for KnowWhereGraph. This broad overview provides insight into the requirements and design specifications for the graph and its schema, including the development methodology (modular ontology modeling) and the resources utilized to implement, materialize, and deploy KnowWhereGraph with its end-user interfaces and public query SPARQL endpoint.
format Preprint
id arxiv_https___arxiv_org_abs_2410_13948
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The KnowWhereGraph Ontology
Shimizu, Cogan
Stephe, Shirly
Barua, Adrita
Cai, Ling
Christou, Antrea
Currier, Kitty
Dalal, Abhilekha
Fisher, Colby K.
Hitzler, Pascal
Janowicz, Krzysztof
Li, Wenwen
Liu, Zilong
Mahdavinejad, Mohammad Saeid
Mai, Gengchen
Rehberger, Dean
Schildhauer, Mark
Shi, Meilin
Norouzi, Sanaz Saki
Tian, Yuanyuan
Wang, Sizhe
Wang, Zhangyu
Zalewski, Joseph
Zhou, Lu
Zhu, Rui
Artificial Intelligence
KnowWhereGraph is one of the largest fully publicly available geospatial knowledge graphs. It includes data from 30 layers on natural hazards (e.g., hurricanes, wildfires), climate variables (e.g., air temperature, precipitation), soil properties, crop and land-cover types, demographics, and human health, various place and region identifiers, among other themes. These have been leveraged through the graph by a variety of applications to address challenges in food security and agricultural supply chains; sustainability related to soil conservation practices and farm labor; and delivery of emergency humanitarian aid following a disaster. In this paper, we introduce the ontology that acts as the schema for KnowWhereGraph. This broad overview provides insight into the requirements and design specifications for the graph and its schema, including the development methodology (modular ontology modeling) and the resources utilized to implement, materialize, and deploy KnowWhereGraph with its end-user interfaces and public query SPARQL endpoint.
title The KnowWhereGraph Ontology
topic Artificial Intelligence
url https://arxiv.org/abs/2410.13948