開放資料是近年來受到各界關注的熱門議題，透過將資料進行公開與共享，能為公眾創造更大的價值。而基於大數據的概念而誕生的各式研究，使得開放資料轉化成為有組織、有意義的資訊。然而，實務上在資訊的發布或是資料的檢索，都會發生許多的困難。
在本論文中，我們基於P2P同儕網路架構，並以智慧醫療大數據外溢保單的資訊系統為例，所實作的一個創新的開放式P2P資料管理平台，於其中提出計算工作分配的工作分配策略。我們依據不同的目標制定不同的節點工作分配方式，使大數據工作的分配更有效率完成。讓大數據相關演算法運用此平台進行快速運算，使資料提供者的資料能大幅提升其實用性與影響力。
我們在這個P2P資料平台分析了可能改善原始P2P架構的設計，並整合至平台的各個模組，在這個平台，將能讓參與者上傳資料、確保資料機密性、可靠度與正確性。未來也期待平台能持續結合更多的應用情境，至更為成熟的發展。

Open data is a hot issue that has attracted much attention in recent years. By publishing and sharing data, it can create great value for the public. There are various related researches that have proved to transform open data into organized and meaningful information. However, in practice, many difficulties arise in the release of information or the retrieval of data.
In this thesis, we design a P2P network architecture and implement an innovative open P2P data management platform, and take as an example, the smart medical big data spillover insurance policy. We propose task allocation strategies for P2P computing. According to user demands, an appropriate task allocation algorithm can be chosen to let computing work be finished efficiently. Thus, the value and influence for open data and big data can be greatly increased in practice.
Our P2P data management platform has more flexibility than the original P2P architecture and can be integrated into various of the computing modules. This platform allows participants to upload data and can ensure the data confidentiality, reliability and accuracy of the data. In the future, it is also expected that the platform can continue to integrate more application scenarios and achieve more values.
Keywords: open data, big data, P2P network architecture, P2P data management platform, P2P computing, data confidentiality.

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