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Over the past few years, a growing number of (geo)portals have been developed to address this need. However, most existing (geo)portals are stacked by separated or sparsely connected data \u201csilos\u201d impeding effective data consolidation. A new way of sharing and reusing geospatial data is therefore urgently needed. In this work, we introduce KnowWhereGraph, a knowledge graph\u2010based data integration, enrichment, and synthesis framework that not only includes schemas and data related to human and environmental systems but also provides a suite of supporting tools for accessing this information. The KnowWhereGraph aims to address the challenge of data integration by building a large\u2010scale, cross\u2010domain, preintegrated, FAIR\u2010principles\u2010based, and AI\u2010ready data warehouse rooted in knowledge graphs. We highlight the design principles of KnowWhereGraph, emphasizing the roles of space, place, and time in bridging various data \u201csilos.\u201d Additionally, we demonstrate multiple use cases where the proposed geospatial knowledge graph and its associated tools empower decision\u2010makers to uncover insights that are often hidden within complex and poorly interoperable datasets.<\/jats:p>","DOI":"10.1111\/tgis.70184","type":"journal-article","created":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T04:01:07Z","timestamp":1770436867000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["The\n                    <scp>KnowWhereGraph<\/scp>\n                    : A Large\u2010Scale Geo\u2010Knowledge Graph for Interdisciplinary Knowledge Discovery and Geo\u2010Enrichment"],"prefix":"10.1111","volume":"30","author":[{"given":"Rui","family":"Zhu","sequence":"first","affiliation":[{"name":"University of Bristol  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