隨著智慧城市建設及數位孿生（Digital Twin）技術的快速推進，地理資料與服務資源在決策支援、城市治理、基礎設施管理等領域的重要性日益提升。特別是在都市發展、環境監測、交通管理與公共安全等應用場景中，精確而即時的空間資訊成為推動智慧應用的核心要素。然而，隨著資料來源與型態的多樣化，包括傳統的二維資料（2D）、高精度三維模型（3D）乃至於涵蓋時間變化的四維資料（4D），結合物聯網之動態地理資源、服務與API等網路資源，資訊的管理、分享與應用面臨著更高的複雜性。為因應跨領域資料整合、即時更新與資源重用之需求，標準化且結構化的詮釋資料建構，成為提升跨域資源搜尋效率、判斷資料適用性及支持資源正確運用之重要基礎及必要條件。尤其以數位孿生這類必須涵蓋多元領域、包含時空面向及持續更新之資料機制而言，透過妥善設計的詮釋資料機制，數位孿生系統得以有效銜接現實世界與虛擬模型，提升系統運作效能，並加速智慧城市相關應用之落實。
目前既有的地理資源詮釋資料設計，多以靜態描述為主，未能充分回應多維資料結構與即時更新需求，亦未針對不同資源型態（如資料集、影像、API服務）提出細緻而適用性導向之設計。尤其當數位孿生系統需要整合大量異質資料源，並進行動態分析與決策支援時，傳統詮釋資料體系很容易因設定對象過於保守、描述資訊內容不足或缺乏統一格式而產生資源選取錯誤、整合困難及應用受限等問題。本研究認為數位孿生系統之詮釋資料必須滿足其操作之特性，至少同時支持資源發現（Resource discovery）、資源管理（Management）及適用性評估（Fitness for use）等多重功能的標準化框架，使得地理資訊在智慧應用、跨域整合及數位孿生技術推展過程中，以其將其後續之應用延伸至互操作應用層面。且此架構應以符合國際詮釋資料標準之方式設計與建立，以符合開放及跨域之國際接軌優勢。。
本研究以ISO 19115國際標準為基礎，參考Dublin Core與Open API等設計原則，採用子標準（Profile）設計概念，發展一套針對地理資料、圖徵、遙測影像（RS Imagery）、Coverage（通用網格）及API服務資源之詮釋資料架構。研究過程中，除依功能需求設計納入之項目及規劃記錄內容之配套外，並結合目前高度討論之FAIR（Findable, Accessible, Interoperable, Reusable）原則進行設計與驗證。子標準之設計將以符合數位孿生之需求觀點切入，涵蓋不同種類資源之特色，分析共通性與特殊性項目，以支援不同維度資料在數位孿生應用中的一致性與可用性，終極目標為完成一套兼顧多維資料、即時更新與跨域應用需求之標準化詮釋資料框架。該框架能有效支援多樣化地理資源的描述與分類管理，並能明確記錄資源之適用性條件，避免在資源整合或應用過程中發生錯誤引用的情形。此外，設計中納入整合式資源搜尋與篩選功能，讓使用者能依據特定條件迅速找到符合需求的資料、影像或服務，進一步提升數據利用效率。本研究所建構之詮釋資料設計，亦能滿足我國目前地理空間資料平台之發展需求，以實務應用於我國之地理資源分享環境
本研究已初步完成以 Profile 設計為核心的詮釋資料標準化框架，目前成果主要聚焦於建立基本之描述結構，對於實際應用中資料與服務資源的操作流程、平台整合與跨系統相容性等層面仍有進一步探討空間。未來將持續深化於詮釋資料於不同數位孿生場域中之實作測試，包含樣版設計與內容自動化建立、跨系統資料目錄架構與支援圖徵重複使用等操作性問題，仍須進一步驗證詮釋資料設計於多元應用架構下之擴充性，並逐步推展至即時資料整合與語意一致性驗證等進階議題。

The rapid advancement of smart cities and digital twin technologies has heightened the importance of geographic data and service resources in decision support, urban governance, infrastructure management, and related domains. Accurate and real-time spatial information is critical for applications such as urban development, environmental monitoring, traffic management, and public safety. Yet, the increasing diversity of data sources—including 2D datasets, high-precision 3D models, spatiotemporal 4D data, and dynamic Internet of Things–enabled services—has introduced significant challenges in data management, sharing, and utilization. Addressing cross-domain integration, real-time updates, and resource reuse requires standardized and structured metadata mechanisms to improve resource discovery, assess fitness for use, and ensure proper application.
This study proposes a profile-based metadata framework grounded in ISO 19115, complemented by principles from Dublin Core, OpenAPI, and the FAIR guidelines (Findable, Accessible, Interoperable, Reusable). The framework accommodates diverse resources such as geographic datasets, features, remote sensing imagery, coverage data, and API services. By identifying both commonalities and resource-specific characteristics, the framework ensures consistency, usability, and interoperability across multi-dimensional data in digital twin applications. Key features include structured descriptions, explicit documentation of fitness-for-use conditions, and integrated search and filtering functions to enhance data discovery and utilization.
Preliminary results focus on establishing the basic descriptive structures, while future work will extend towards operational workflows, platform integration, cross-system interoperability, and advanced topics such as real-time data assimilation and semantic consistency validation. This framework not only supports the evolving requirements of digital twins but also addresses practical needs for geospatial data-sharing platforms, with implications for smart city implementations in Taiwan and beyond.

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