政府公開資料(Open Gov Data)在各國逐漸盛行，2009年美國政府公開資料平台(data.gov)以及英國政府公開資料平台(data.gov.uk)上線以來，各國家都開始發展自己的政府公開資料平台。台灣也不落人後，從台北市政府開始、陸續有台北市公開資料平台、政府公開平台...等等資料，供人民或開發者使用。但是綜觀目前台灣各中央、地方政府，雖然陸陸續續開放了很多資料，但是卻遇到了很多問題：格式雜亂、格式不易運用、資料授權複雜...等等，使得人民、開發者難以針對這些資料進行應用、開發服務。
本研究利用鏈結公開資料(Linked Open Data)的概念，使用語意網路技術，加強資料的可讀性、開發性，並且提供語意網路存取語言的介面，讓資料更容易被使用，以便從資料中挖掘更多的價值。另一方面，為了讓應用更貼近使用者，本研究採用了情境感知(Context Awareness)方式開發應用，讓應用能更貼近使用者的生活。為了驗證上述概念，本研究實作台北市公開資料中的三個資料集整合至停車場推薦系統，從應用的起點：『開放資料』，一路到『使用者端』，實作一個有效、可塑型高、且更親切的系統模型。

Open Government Data gradually prevailed across the world. Since data.gov and data.gov.uk launched one by one in 2009, lots of countries developed their own Open Government Data platform, and so does Taiwan. The Platform of data.taipei.gov.tw is the first Open Gov Data platform in Taiwan. Now there are many Open Gov Data platforms, such as data.gov.tw and data.taichung.gov.tw, for any usage of people or developer. These platforms have numerous data, however, with messy format and poor data retrievability, which is hard for developer to implement services. Therefore, this study follow the standard of Linked Open Data, using Semantic Web Technique to normalize data, and providing Semantic Web Query Interface, SPARQL, to access data. By doing so, we can use these open data much easier, and discover more information from data, to create more value from these.
Besides, in order to create better application experience for users, this study includes Context Awareness to make the application fit the user’s life. To implement these concepts, this study implement a Taipei Parking Garage Recommendation System, which combined three of datasets on Taipei open gov data platform, to create an efficient, convenient and flexible system model.

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