政府開放資料現今在各國漸漸盛行，從 2009年美國和英國政府開放資料平台上線後，各個國家開始發展自有的政府開放資料平台。臺灣也不例外，臺北市政府首先推動台北市開放資料平台，給予民眾應用或資料查詢開發使用。但綜觀目前台灣各區的開放資料，雖然蘊含了各領域的大量資料，但卻遇到許多窘境，其中包含格式雜亂、格式不容易整合應用、資料授權複雜...等問題，使得民眾或開發者針對這些資料不易應用與開發服務。
本研究利用鏈結資料概念來用於開放資料上形成鏈結開放資料應用，透過統一轉換成RDF格式來描述資料並加以進行鏈結於雜亂資料中相互關係來增強資料可讀性和可行性，能使資料更容易被使用，開發上也更具有彈性。本研究利用臺北市的地理位置為情境感知的鏈結基礎，利用行動裝置定位功能，於臺北市開放資料平台中採用交通類別的停車場、微笑單車以及捷運形成鏈結開放資料集，再利用開放資料於時間軸上數據分析和列車到站時間計算，讓使用者能透過當下地理位置以及自行設定條件進行查詢、計算與服務整合串聯成由開車、停車、租借微笑單車以及搭乘捷運列車，進一步地搭配旅遊景點的動態情境資料分析或自行設計一套專屬於自己的客製化一日遊行程的情境分析應用。

Many countries has been developed their own open government data platform after Data.gov.(England) and Data.gov.(America) platform have been lunched since 2009. Government data platform has been established in each country, including Taiwan. Taipei City Government is the first local government which promotes the Taipei open data platform first and provides people to use this platform. Although there are amounts of data about various areas in the open data of Taiwan, it faces many data format problems including inconsistency, licensing etc.
This research uses the concepts of linking open data to analyze correlated open data via semantic web technology. The linking open data are transformed to an RDF (Resource Description Framework) format to enhance the readability and systematic development. Besides, our system provides a semantic web access interface which can enhance the usability of data. We develop a location-based context-aware service based on Taipei city open data to provide various smart city services. Through the integration of parking lots, public bicycle and MRT data, users can use their mobile devices to arrange activities according to the location of dynamic context data analysis and set their own requirements to design a one-day-traveling schedules.

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