The KnowWhereGraph ontology

IF 2.1 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Web Semantics Pub Date : 2025-01-01 DOI:10.1016/j.websem.2024.100842

Cogan Shimizu , Shirly Stephen , 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 , Rui Zhu

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引用次数: 0

Abstract

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.

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来源期刊

Journal of Web Semantics 工程技术-计算机：人工智能

CiteScore

6.20

自引率

12.00%

发文量

审稿时长

14.6 weeks

期刊介绍： The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.