Know, Know Where, KnowWhereGraph: A densely connected, cross-domain knowledge graph and geo-enrichment service stack for applications in environmental intelligence

被引：45

作者：

Janowicz, Krzysztof ^{[1
]}

Hitzler, Pascal ^{[2
]}

Li, Wenwen ^{[3
]}

Rehberger, Dean ^{[4
]}

Schildhauer, Mark ^{[1
,5
]}

Zhu, Rui ^{[1
]}

Shimizu, Cogan ^{[2
]}

Fisher, Colby K. ^{[6
]}

Cai, Ling ^{[1
]}

Mai, Gengchen ^{[7
]}

Zalewski, Joseph ^{[2
]}

Zhou, Lu ^{[2
]}

Stephen, Shirly ^{[1
]}

Gonzalez, Seila ^{[4
]}

Mecum, Bryce ^{[5
]}

Lopez-Carr, Anna ^{[8
]}

Schroeder, Andrew ^{[8
]}

Smith, David ^{[1
]}

Wright, Dawn ^{[9
]}

Wang, Sizhe ^{[3
]}

Tian, Yuanyuan ^{[3
]}

Liu, Zilong ^{[1
]}

Shi, Meilin ^{[1
]}

D'Onofrio, Anthony ^{[4
]}

Gu, Zhining ^{[3
]}

Currier, Kitty ^{[1
]}

机构：

[1] Univ Calif Santa Barbara, Santa Barbara, CA 93106 USA

[2] Kansas State Univ, Manhattan, KS 66506 USA

[3] Arizona State Univ, Tempe, AZ USA

[4] Michigan State Univ, Matrix, E Lansing, MI 48824 USA

[5] Natl Ctr Ecol Anal & Synth, Santa Barbara, CA USA

[6] Hydronos Labs, Princeton, NJ USA

[7] Stanford Univ, Stanford, CA 94305 USA

[8] Direct Relief, Santa Barbara, CA USA

[9] Esri, Redlands, CA USA

来源：

AI MAGAZINE | 2022年 / 43卷 / 01期

基金：

美国国家科学基金会;

关键词：

SCALE;

D O I：

10.1002/aaai.12043

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Knowledge graphs (KGs) are a novel paradigm for the representation, retrieval, and integration of data from highly heterogeneous sources. Within just a few years, KGs and their supporting technologies have become a core component of modern search engines, intelligent personal assistants, business intelligence, and so on. Interestingly, despite large-scale data availability, they have yet to be as successful in the realm of environmental data and environmental intelligence. In this paper, we will explain why spatial data require special treatment, and how and when to semantically lift environmental data to a KG. We will present our KnowWhereGraph that contains a wide range of integrated datasets at the human-environment interface, introduce our application areas, and discuss geospatial enrichment services on top of our graph. Jointly, the graph and services will provide answers to questions such as "what is here," "what happened here before," and "how does this region compare to horizontal ellipsis " for any region on earth within seconds.

引用

页码：30 / 39

页数：10

共 1 条

[1] Know, Know Where, KnowWhereGraph: A densely connected, cross-domain knowledge graph and geo-enrichment service stack for applications in environmental intelligence (vol 43, pg 30, 2022)
Janowicz, K.
Hitzler, P.
Li, W.
Rehberger, D.
Schildhauer, M.
Zhu, R.
Shimizu, C.
Fisher, C. K.
Cai, L.
Mai, G.
Zalewski, J.
Zhou, L.
Stephen, S.
Gonzalez, S.
Mecum, B.
Lopez-Carr, A.
Schroeder, A.
Smith, D.
Wright, D.
Wang, S.
Tian, Y.
Liu, Z.
Shi, M.
D'Onofrio, A.
Gu, Z.
Currier, K.
AI MAGAZINE, 2022, 43 (02) : 270 - 270

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