Know, Know Where, KnowWhereGraph: A densely connected, cross‐domain knowledge graph and geo‐enrichment service stack for applications in environmental intelligence
Know, Know Where, KnowWhereGraph: A densely connected, cross‐domain knowledge graph and geo‐enrichment service stack for applications in environmental intelligence
复制标题
Know、KnowWhere、KnowWhereGraph：用于环境情报应用的密集连接的跨领域知识图谱和地理丰富服务堆栈
DOI：
10.1002/aaai.12043
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发表时间：
2022
期刊：
影响因子：
0.9
通讯作者：
Mai, Gengchen
中科院分区：
文献类型：
--
作者：
Janowicz, Krzysztof;Hitzler, Pascal;Li, Wenwen;Rehberger, Dean;Schildhauer, Mark;Zhu, Rui;Shimizu, Cogan;Fisher, Colby K.;Cai, Ling;Mai, Gengchen
知识图（KGs）是一种新的范式，用于表示，检索和集成来自高度异构源的数据。在短短几年内，知识库及其支持技术已经成为现代搜索引擎、智能个人助理、商业智能等的核心组成部分。有趣的是，尽管有大规模的数据可用性，但它们在环境数据和环境智能领域还没有取得成功。在本文中，我们将解释为什么空间数据需要特殊处理，以及如何以及何时语义提升环境数据到KG。我们将展示我们的KnowWhereGraph，它包含了人类环境界面上的各种集成数据集，介绍我们的应用领域，并在我们的图表上讨论地理空间丰富服务。结合起来，图表和服务将在几秒钟内为地球上的任何地区提供诸如“这里是什么”、“这里以前发生过什么”以及“这个地区与......相比如何”等问题的答案。
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…” for any region on earth within seconds.