從開發人員需求探討開放政府資料於公眾健康領域之應用

Why do data practitioners utilize open government data for public health?

10.6288/TJPH.202308_42(4).112024

鄭惟中(WEI-CHUNG CHENG)；邱銘心(MING-HSIN PHOEBE CHIU)

開放政府資料 ； 開發人員 ； 需求 ； 資料再利用 ； 質性分析 ； open government data ； data practitioner ； needs ； data reuse ； qualitative analysis

台灣公共衛生雜誌

42卷4期（2023 / 08 / 30）

436 - 449

繁體中文;英文

目標：近年受COVID-19疫情影響，開放政府資料於公眾健康領域的應用性漸受重視。本研究以使用過開放政府資料開發出健康資訊產品的人員為對象，分析其使用此類資料的需求並向公部門提出實務建議，以期活化開放政府資料於公共健康領域之科技應用。方法：本研究為質性取向，共訪談11位開發人員，並基於紮根理論研究法之精神，透過三階段譯碼過程分析訪談內容。結果：開發人員會因為職場任務（業務型）、成本效益（經濟型）、產品功能（功能型）、參加競賽（規範型）、參與公益（社會型）及個人需要（自我型）等需求使用開放政府資料，且開發人員評估需求是否獲得滿足時，其判斷具有個體（內在期待有無獲得滿足）及互動（有無順利回應外界情境）兩種屬性。結論：開發人員將開放政府資料轉化為可用的健康資訊服務後，有助民眾提升健康知能及素養，各種創新成果更可促進各界對公衛議題的理解及參與，顯見開發人員及開放政府資料兩者對於提升公眾健康領域的發展實為不可或缺。

Objectives: Governments have long encouraged professionals in various sectors to innovatively apply open government data (OGD). Because of the COVID-19 pandemic, the application of OGD in civil services to improve public health-related literacy has been discussed comprehensively. This study investigated the needs of practitioners utilizing OGD to develop specific products concerning public health to demonstrate the value of utilizing OGD to improve the quality of life of citizens. Methods: This study qualitatively analyzed 11 interviews with practitioners utilizing grounded theory. Results: (1) Six types of needs of practitioners utilizing OGD were identified, namely mission-oriented, cost-oriented, functionality-oriented, compliance-oriented, social-oriented, and self-oriented needs. (2) Two factors determining whether the practitioners' needs were met were identified. Conclusions: Practitioners can use OGD to provide services for citizens to use to access public health information. These OGD-based services not only enhance individuals' abilities to address questions about public health but also foster an understanding of and participation in public health. Because practitioners are crucial to the implementation of OGD, these findings enable governments to optimize policies to improve OGD utilization on the basis of data practitioners' experiences.

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