Fast Forward from Data to Insight: (Geographic) Knowledge Graphs and Their Applications

Krzysztof Janowicz; Kitty Currier; Cogan Shimizu; Rui Zhu; Meilin Shi; Colby K. Fisher; Dean Rehberger; Pascal Hitzler; Zilong Liu; Shirly Stephen

doi:10.1201/9781003308423-21

Fast Forward from Data to Insight: (Geographic) Knowledge Graphs and Their Applications

Krzysztof Janowicz, Kitty Currier, Cogan Shimizu, Rui Zhu, Meilin Shi, Colby K. Fisher, Dean Rehberger, Pascal Hitzler, Zilong Liu, Shirly Stephen

School of Geographical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter in a book

Abstract

In this chapter, we explain what knowledge graphs are, how they relate to GeoAI research such as knowledge engineering and representation learning, discuss their value proposition for geography and the broader geosciences, outline application areas for knowledge graphs across domains, and introduce the KnowWhereGraph as an example of a geospatially centered, highly heterogeneous graph consisting of billions of graph statements extracted from 30 different data layers at the intersection between humans and the environment.

Original language	English
Title of host publication	Handbook of Geospatial Artificial Intelligence
Publisher	CRC Press
Pages	411-426
Number of pages	16
ISBN (Electronic)	9781003814924
ISBN (Print)	9781032311661
DOIs	https://doi.org/10.1201/9781003308423-21
Publication status	Published - 1 Jan 2023

Bibliographical note

Publisher Copyright:
© 2024 selection and editorial matter, Song Gao, Yingjie Hu, and Wenwen Li; individual chapters, the contributors.

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10.1201/9781003308423-21

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AU - Janowicz, Krzysztof

AU - Currier, Kitty

AU - Shimizu, Cogan

AU - Zhu, Rui

AU - Shi, Meilin

AU - Fisher, Colby K.

AU - Rehberger, Dean

AU - Hitzler, Pascal

AU - Liu, Zilong

AU - Stephen, Shirly

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AB - In this chapter, we explain what knowledge graphs are, how they relate to GeoAI research such as knowledge engineering and representation learning, discuss their value proposition for geography and the broader geosciences, outline application areas for knowledge graphs across domains, and introduce the KnowWhereGraph as an example of a geospatially centered, highly heterogeneous graph consisting of billions of graph statements extracted from 30 different data layers at the intersection between humans and the environment.

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U2 - 10.1201/9781003308423-21

DO - 10.1201/9781003308423-21

M3 - Chapter in a book

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EP - 426

BT - Handbook of Geospatial Artificial Intelligence

PB - CRC Press

ER -

Fast Forward from Data to Insight: (Geographic) Knowledge Graphs and Their Applications

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