隨著開放思潮進展，多年來各國普遍推動開放政府資料運動，廣泛釋出政府資料並號召民間個人或團體參與，期待以此類資料的應用效益活化不同領域的發展。然而，隨著越來越多人加入開放政府資料再利用的行列，身為資料提供者的政府機關有無提供民間適合再利用的開放政府資料，以及此類資料的價值能否於再利用的過程中獲得實踐並造福社會大眾等，諸多討論亦油然而生。為實務探知我國開放政府資料應用境況，本文以具有資料處理或編寫程式專業技能的開發人員為研究對象，藉由分析開發人員將開放政府資料開發為大眾實際可用產品的歷程，一窺開放政府資料精神獲得落實的情形，兼而探討開發人員所具有的資料開發者角色對開放政府資料加值應用之意義。

本研究為質性研究，首先自各式管道蒐集曾使用過開放政府資料開發產品的開發人員名單並寄送訪談邀請，總計招募35位開發人員參與；研究設計以半結構式訪談法蒐集開發人員第一手經驗後逐字謄錄為文本，接續參考紮根理論研究法的三階段譯碼策略進行持續比較分析；研究結果顯示，開發人員再利用開放政府資料開發產品的歷程係為具有明確目標的一系列行動。首先，開發人員會因六種類型需求決定再利用開放政府資料，各類型需求除具有心理學觀點的理論性，本研究亦發現其彼此間相互作用及滿足各需求條件之屬性；其次，開發人員再利用開放政府資料的行為呈現七個有序階段，本文借鏡資訊行為研究與軟體開發生命週期兩者內涵，充實其理論基礎；最後，開發人員再利用開放政府資料的經驗受到三大面向及五大因素影響，此發現不僅可對應至開放政府資料生態圈涉及的不同角色意涵，亦呼應資訊系統成功模式中所述對使用者經驗有著關鍵影響的不同要素。

本文各項研究結果對公部門具體改善開放政府資料應用環境有所實質助益，機關單位不僅可參考各需求類型，研擬並推展政策以吸引各界響應開放政府資料加值應用，也能基於對開放政府資料再利用行為的認識，於開發過程中提供開發人員適當的行政或技術奧援，降低開發成本以提升其應用此類資料的意願，更可針對影響開發人員經驗的各種因素或其對於開放政府資料的期許，逐步建置開發者友善的資料供用環境。綜言之，透過訪談實際的開放政府資料應用者，本研究得以深度分析其再利用開放政府資料的完整歷程，從中描繪公部門、開發人員與社會大眾彼此互動關係，同時理解公部門身為資料提供者應發揮的領導意義、開發人員以資料開發者角色將資料加值效益傳遞於民的公共價值，以及身為產品使用者的社會大眾藉由開放政府資料產品間接參與政府施政作為的民主精神。

未來研究除可轉向聚焦開放政府資料產品使用者，從消費市場角度探討此類資料發展良窳，亦可以資料或產品為導向探討不同單位的資料或服務品質有無差異，此外也能以有別與本研究執行期間適逢COVID-19疫情的時空背景，挖掘不同開發情境是否對開發人員再利用開放政府資料開發產品有所影響，甚或進一步參考本文研究設計以探討不同領域中資料再利用的實務。

As the wave of openness philosophy, many countries have been actively promoting the Open Government Data (OGD) movement over the past several years, involving the extensive release of government data and encouraging participation from citizens and communities. The aim is to activate the beneficial utilization of such data in various domains. However, with an increasing number of participants engaging in the reuse of OGD, questions arise regarding whether government agencies, as data providers, offer data suitable for reuse by the public. Additionally, discussions ensue concerning how the value and spirit of such data can be realized in the reuse process and how it can benefit society at large.

This dissertation focuses on developers with expertise in data processing and programming to gain practical insights into the state of OGD utilization in Taiwan. It seeks to analyze how developers transform OGD into practical and usable products for the public. The dissertation also aims to understand how the principles and values of OGD are effectively implemented in this context. Moreover, it delves into the significance of the roles that developers, as data practitioners, play in enhancing the value of OGD utilization.

This study employs qualitative research methods. Initially, it compiles a list of developers who have used OGD to create products from various sources and sends interview invitations. A total of 35 developers were recruited for participation. The research design adopts semi-structured interviews to collect firsthand experiences from developers, which are transcribed verbatim into textual data. Subsequently, continuous comparative analyses follow the three-stage coding strategy based on grounded theory.

The study results reveal that developers reusing OGD to create products is a sequence of actions with specific objectives. First, developers decide to reuse OGD based on six types of needs, which psychological aspects can demonstrate; moreover, the interactions among these needs and the conditional attributes for fulfilling specific needs are identified. Second, developers' actions in reusing OGD unfold through seven ordered phases, and the study enriches its theoretical foundation by drawing from information behavior research and the concepts of the software development life cycle. Third, three dimensions and five factors influencing developers' experiences reusing OGD are recognized; these dimensions and factors are relevant to various roles within the OGD ecosystem and align with certain critical elements in information system success models.

The outcomes of this study offer substantial practical insights to public sector entities. They can use the different needs identified in the study to devise and promote policies that attract a wide range of stakeholders to engage in the value-added utilization of OGD. Additionally, understanding developers' behaviors in reusing OGD can lead to the provision of appropriate administrative or technical support during the development process, which can reduce costs and enhance developers' willingness to reuse such data. Furthermore, the study enables the establishment of a developer-friendly data utilization environment based on various factors influencing developers’ experiences and expectations regarding OGD.

In summary, this study analyzes developers' reasons, behaviors, and experiences reusing OGD, offering insights into the interactions between the public sector, developers, and citizens. It underscores the leadership role that government agencies should play as OGD providers, the public value developers bring as OGD practitioners and the democratic spirit exhibited by the citizens as OGD product users who indirectly participate in government actions through the use of relevant products.

Future research can explore different aspects, including (1) discussing OGD utilization environment from a consumer perspective instead of a data practitioner viewpoint; (2) investigating whether data or service quality differs across various entities; (3) assessing the impact of different development contexts, especially given the unique circumstances of the COVID-19 pandemic during the study period, on developers reusing OGD to create products; (4) further considering different practical scenarios for data reuse across various domains.

文羽苹、江東亮（2002）。全民健康保險學術資料庫基本檔的應用經驗。台灣公共衛生雜誌，21卷2期，頁150-155。
王文科（2001）。教育研究法。臺北市：五南。
王文科、王智弘（2010）。質的研究的信度和效度。彰化師大教育學報，17，頁29-50.
王石番（1991）。傳播內容分析法：理論與實證。臺北市：幼獅文化。
王本正、許富榕（2016）。以延伸型整合性科技接受模式探討行動醫療App協助照護任務之接受度。福祉科技與服務管理學刊，4卷4期，頁483-494。
王守玉、Windsor, C., & Yates, P.（2012）。簡介紮根理論研究法，護理雜誌，59卷1期，頁91-95.
王宏仁（2019年6月13日a）。資料經濟新模式：日本出現企業資料異業共享平臺，靠區塊鏈強化資料溯源和交換。iThome網路新聞。上網日期2023年6月18日，檢自https://www.ithome.com.tw/news/131166
王宏仁（2019年6月13日b）。資料經濟新模式：自己的個資自己賣，新MyData模式讓民眾決定誰有權用個資。iThome網路新聞。上網日期2023年8月18日，檢自：https://www.ithome.com.tw/news/131167
王啟安、王秀琳、金少文、楊棋宇、盧巧梅、呂紹齊（2015年9月14日）。致命撞擊—被低估的死亡車禍數據。聯合新聞網。上網日期2023年8月25日，檢自：https://udn.com/upf/newmedia/2015_data/20150803_udntraffic/udntraffic
未來城市編輯部（2021年6月8日）。快來比對接觸史！台中確診足跡地圖上線｜城市防疫共筆。上網日期2023年8月27日，檢自未來城市（Future City@天下）：https://futurecity.cw.com.tw/article/2051
石育平、柯皓仁（2010）。半導體晶圓代工產業工程師資訊行爲之研究。教育資料與圖書館學，48卷1期，頁87-118。
行政院新聞傳播處（2020年11月19日）。蘇揆：創造資料經濟，推動臺灣成為數位化國家及智慧政府。上網日期2023年8月12日，檢自：https://www.ey.gov.tw/Page/9277F759E41CCD91/2ef6b7db-3424-49eb-a385-0a0e7029a476
何邡瑀（2019）。應用台北市政府開放資料開發APPs的旅程：以APP開發者角度分析。國立政治大學公共行政學系碩士學位論文。
何信弘、王立亭、張少熙（2020）。以科技接受模式探討中高齡者使用運動App之需求。福祉科技與服務管理學刊，8卷2期，頁137-147。
余至浩（2014年7月14日），政府開放資料大體檢，哪些民眾最愛用？。iThome網路新聞。上網日期2023年8月20日，檢自：https://www.ithome.com.tw/news/89376
吳芝儀（2011）。以人為主體之社會科學研究倫理議題。人文社會科學研究，5卷4期，頁19-39.
吳昱瑾（2011）。軟體開發專案團隊之團隊特性、任務相依性對團隊效能之影響。國立臺北大學企業管理學系碩士學位論文。
吳嘉苓（2015）。訪談法。載於瞿海源、畢恆達、劉長萱、楊國樞（主編），社會及行為科學研究法：質性研究法（頁33-62）。臺北市：臺灣東華。
宋餘俠、李國田（2012）。政府部門資料加值推動策略與挑戰。研考雙月刊，36卷4期，頁10-21。
李坤清、王厚升（2015）。影響軟體人員開發行為之反模式探討。台灣管理學刊，15卷1期，頁77-101。
李孟洋（2014）。開放資料之產業效益—以天氣風險管理開發股份有限公司為例。國立清華大學經營管理碩士在職專班學位論文。
李治安、林誠夏、莊庭瑞（2014）。開放政府資料的基本原則與相關政策議題。公共治理季刊，2卷1期，頁65-76。
李建興（2015年3月7日）。政府與民間合辦開放資料App比賽，推廣開放政府政策。iThome網路新聞。上網日期2023年8月10日，檢自：https://www.ithome.com.tw/news/94394
李婷媛（2006）。研發機構工程師資訊行為及其在資訊服務應用之探討。國立臺灣大學圖書資訊學研究所碩士學位論文。
杜逸寧、徐維澤、黃祥晉、許明楷、林鈺翔、洪健傑（2018）。結合政府開放資料集於建構開業選址決策支援系統－以店址當地消費能力與鄰近產業特性觀點。科儀新知，215期，頁4-21。
周立生、林郁雯、沈哲緯、鄭錦桐、江陽聖、蔡世賢（2019）。政府防災公開資料與產業跨域整合應用初探－以天災保險為例。中興工程，142期，頁21-30。
周恆毅、張子瑩、黃俊宏（2016）。防救災開放資料之蒐整與應用。2016臺灣災害管理學會十週年年會，頁1-7。
林仁智、李亦君、黃俊豪（2014）。政府資料開放平台之應用:《e記帳》基於電子發票整合服務平台。電子商務研究，12：3期，頁337-355。
林玉書（2019年4月）。美國通過「開放、公開、電子化與必要的政府資料法」（Open, Public, Electronic, and Necessary Government Data Act）。上網日期2023年8月26日，檢自財團法人資訊工業策進會：https://stli.iii.org.tw/article-detail.aspx?no=64&tp=1&d=8210
林姸希、史孟蓉（2016）。運用政府開放資料發展交通便民服務之探討。電工通訊季刊，頁1-6。
林珊如（2005）。深度休閒與資訊行為研究。圖書資訊學刊，3卷1／2期，頁15-22。
林珊如（2006）。圖書資訊學與質性研究。中華圖書資訊學教育學會會訊，27期，頁2-16。
林彥臣（2020年3月11日）。台灣防疫經驗世界都在看！外交部列「20國媒體報導」。上網日期2023年8月26日，檢自：https://www.ettoday.net/news/20200311/1664616.htm
林翠儀（2020年3月10日）。NHK報導台灣防疫成功 可供世界參考。自由時報。上網日期2023年8月16日，檢自：https://news.ltn.com.tw/news/life/breakingnews/3095550
柯皓翔、林雨佑、陳潔、林慧貞、嚴文廷、許家瑜（文字）、黃禹禛、林珍娜、吳政達（設計）、李法賢、余崇任、曾清陽、方泰鈞（工程）、楊惠君（監製）（2020年2月19日）。從武漢到世界：COVID-19疫情即時脈動。報導者。上網日期2023年8月26日，檢自：https://www.twreporter.org/i/covid-2019-keep-tracking-gcs
胡幼慧（2008）。質性研究：理論、方法及本土女性研究實例。臺北市：巨流。
胡幼慧、姚美華（2008）。一些質性方法上的思考：信度與效度？如何抽樣？如何收集資料、登錄與分析。載於胡幼慧（主編），質性研究：理論、方法及本土女性研究實例（頁117-132）。臺北市：巨流。
胡欣男、李文正、葉德正（2020年3月23日）。夜店臨檢逮到檢疫男 重罰百萬。中國時報電子新聞。上網日期2023年8月24日，檢自：https://bit.ly/31lv8RW
徐宗國（譯）（1997）。質性研究概論（原作：Struss, B. & Cobin, A.）。臺北市：巨流。（原作出版年：1990）
徐莉芬（2008）。積體電路（IC）設計公司人員之資訊行為研究。國立臺灣師範大學教育學系在職進修碩士班學位論文。
祝康偉（2020）。疫情下的臺灣數位社會創新－專訪行政院唐鳳政務委員。國際開發援助現場，第2期，上網日期2023年8月25日，檢自： https://icdfblog.org/2020/12/31/development_focus_quarterly_issue2_07/
財團法人台灣網路資訊中心（2019）。2019台灣網路報告。上網日期2023年8月26日，檢自：https://report.twnic.tw/2019/TrendAnalysis_globalCompetitiveness.html
財團法人開放文化基金會（2017）。開放政府觀察報告：2014-2016。上網日期2023年8月24日，檢自：https://opengovreport.ocf.tw/report/
馬中哲（2016）。政府開放資料承辦人員之資料尋求歷程初探。國立臺灣大學圖書資訊學研究所碩士學位論文。
國家發展委員會（2013）。政府資料開放加值應用研究分析書面報告。上網日期2023年8月26日，檢自：https://bit.ly/47MVRXm
國家發展委員會（2015a），政府資料開放進階行動方案。上網日期2023年8月23日，檢自：https://bit.ly/3OPFctr
國家發展委員會（2015b）。政府資料開放（OPEN DATA）具體成效。上網日期2023年8月23日，檢自：https://bit.ly/2Tywe8m
國家發展委員會（2017年6月16日）。全球開放資料評比 台灣蟬聯全球第一。上網日期2023年8月20日，檢自：https://bit.ly/2YDNonE
國家發展委員會（2018）。106年持有手機民眾數位機會調查報告。上網日期2023年8月17日，檢自：http://bit.ly/2F4KcJb
國家發展委員會（2020a）。政府資料開放與利用：國際趨勢觀察。上網日期2023年8月26日，檢自：https://bit.ly/2UxY9bR
國家發展委員會（2020b）。政府資料開放與再利用精進規劃。上網日期2023年8月26日，檢自行政院公共數位創新空間（PDIS）：https://bit.ly/3zD3dLi
張心玲（2016）。Open Data, Big Data等資料經濟發展現況與趨勢探討。電工通訊季刊，第2季，頁16-29。
畢恆達（2015）。研究倫理。載於瞿海源、畢恆達、劉長萱、楊國樞（主編），社會及行為科學研究法：質性研究法（頁37-64）。臺北市：臺灣東華。
莊友欣（2012）。開放（政府）資料與非營利組織。研考雙月刊，36卷4期，頁39-49。
許哲銘（2019年5月）。歐盟將修正公部門資訊再利用（PSI）指令。上網日期2023年8月18日，檢自財團法人資訊工業策進會：https://stli.iii.org.tw/article-detail.aspx?no=64&tp=1&d=8241
連賢明（2008）。如何使用健保資料進行經濟研究。經濟論文叢刊，36卷1期，頁115-143。
陳伯安（2019年1月16日）。從 Redhat 到 GitHub，開源軟體為什麼開始火了？。科技報橘網路新聞。上網日期2023年8月20日，檢自：https://buzzorange.com/techorange/2019/01/16/open-sources-rule/
陳廷彥、林冠廷（2019年3月21日）。台灣如何用開放資料，爭取國際空間？。零時政府專題新聞。上網日期2020年6月23日，檢自：https://bit.ly/2AdFw32
陳育群、李偉強（2016）。醫療大數據：健保資料庫之臨床應用與研究。台灣醫學，20卷6期，頁602-608。
陳宜檉、蕭雅文、林怡倩（2017）。旅遊社群網站網路口碑信任對旅遊商品購買意願影響之研究：延伸科技接受模式的理論觀點。觀光與休閒管理期刊，5卷1期，頁28-41。
陳昺麟（2001）。社會科學質化研究之紮根理論實施程序及實例之介紹。勤益學報，19期，頁327-342。
陳啟勳（2000）。正增強Positive Reinforcement。雙語詞彙、學術名詞暨辭書資訊網（國家教育研究院）。上網日期2023年8月26日，檢自：https://terms.naer.edu.tw/detail/8537999b13dc4cefc9372953ab12d47d/?startswith=zh&seq=4
陳啟勳（2000）。正增強物Positive Reinforcer。雙語詞彙、學術名詞暨辭書資訊網（國家教育研究院）。上網日期2023年8月26日，檢自：https://terms.naer.edu.tw/detail/24ff77e97c20fcec9349783988bfdf0d/?startswith=zh&seq=5
陳啟勳（2000）。負增強Negative Reinforcement。雙語詞彙、學術名詞暨辭書資訊網（國家教育研究院）。上網日期2023年8月26日，檢自：https://terms.naer.edu.tw/detail/dd9a1705c776964ae55a71164d8dbd5d/?startswith=zh&seq=5
陳啟勳（2000）。負增強物Negative Reinforcer。雙語詞彙、學術名詞暨辭書資訊網（國家教育研究院）。上網日期2023年8月26日，檢自：https://terms.naer.edu.tw/detail/7b5ac1533fa751fcf54258c06cd506fd/?startswith=zh&seq=8
陳欽雨、張書豪、張卿儀（2013）。網路口碑、社群認同與知覺利益對網購意願之影響：以台灣區Facebook粉絲專頁為例. Electronic Commerce Studies，11卷4期，頁403-429。
陳舜伶、林珈宏、莊庭瑞（2013）。《藏智於民—開放政府資料的原則與現況》。中央研究院資訊科技創新研究中心 台灣創用CC計畫發行。上網日期2023年8月24日，檢自：https://creativecommons.tw/sites/creativecommons.tw/files/download/handbook_open_gov_data.pdf
陳鈺馥（2019年7月21日）。總統盃「黑客松」7/27頒獎 行政院：台灣要成資料運用大國。自由時報。上網日期2023年8月26日，檢自：https://news.ltn.com.tw/news/life/breakingnews/2859522
陳慧玲（2015）。政府開放資料品質與滿意度之研究。淡江大學資訊管理學系在職專班碩士學位論文。
曾旭正（2016）。開放政府之現況與展望。國土及公共治理季刊，4卷4期，頁8-17。
游晁偉（2017）。資訊服務廠商運用政府開放資料之個案探討。國立暨南大學資訊管理學系碩士學位論文。
黃心怡、蘇彩足、蕭乃沂（2016）。再探開放政府資料的政策與發展。國土及公共治理季刊，4卷4期，頁18-28。
黃東益、蕭乃沂（2014）。電子治理與資訊產業發展。公共治理季刊，2卷2期，頁51-57。
黃泓瑜（2017年9月13日）。認識4種臺灣常見的資安保險。iThome網路新聞。上網日期2023年8月26日，檢自：https://www.ithome.com.tw/news/116740
黃俊豪（2015）。政府開放資料之應用—以《藝文控》推薦系統應用程式為例。國立臺北教育大學數位科技設計學系碩士學位論文。
黃昭謀（2015）。新自由主義下開放（政府）資料與商品化的困境分析。圖書館學與資訊科學，41卷1期，頁4-17。
黃曉雯（2014）。政府資料開放平臺—資訊加值輔以資料保險，提升產值與資安。會計研究月刊，343期，頁64-66。
楊東謀、吳怡融（2019）。台灣政府開放資料推行之近況調查與探討。教育資料與圖書館學，56卷1期，頁7-44。
楊美雪、陳家瑜、趙以寧、陳映蓉、黃郁涵、楊禮鴻（2017）。政府藝文資料的開放與加值推廣。臺中教育大學學報：人文藝術類，31卷1期，頁23-42。
經濟部工業局（2020年11月9日）。資料服務產業發展現況與後續推動作法。上網日期2023年8月25日，檢自行政院公共數位創新空間（PDIS）：https://bit.ly/2Wrjp41
萬文隆（2004）。深度訪談在質性研究中的應用。生活科技教育月刊，37卷4期，頁17-23。
廖洲棚、廖興中、黃心怡（2018）。開放政府服務策略研析調查：政府資料開放應用模式評估與民眾參與公共政策意願調查。國家發展委員會委託研究報告（計畫編號：NDC-MIS-106-003）。臺北市：國家發展委員會。
劉子寧（2020年1月21日）。2020大未來｜智慧醫療｜李友專：存下治療過程大數據，醫師更容易預測病人何時出院。上網日期2023年8月27日，檢自未來城市（Future City@天下）：https://futurecity.cw.com.tw/article/1188
劉子寧（2020年4月23日）。武漢肺炎》李友專：疫苗至少還要等1年，但科技能做4件事降恐慌。天下雜誌。上網日期2023年8月25日，檢自：https://futurecity.cw.com.tw/article/1394
劉俊彥（2020年3月22日）。勤洗手、戴口罩外，你還可以做甚麼？全球公民如何利用科技防疫？。The News Lens（關鍵評論）。上網日期2023年8月26日，檢自：https://www.thenewslens.com/article/133136
歐俐伶、楊東謀（2016）。台灣政府開放資料之詮釋資料建置探討。教育資料與圖書館學，53卷1期，頁63-102。
衛生福利部中央健康保險署（2020年1月27日）。防疫再升級 健保雲端系統提供高風險地區旅遊史。上網日期2023年8月26日，檢自：https://bit.ly/2YJ0oZz
鄧秀群（2012）。政府資料開放加值應用的契機與展望。研考雙月刊，36卷4期，頁3-9。
鄧詠竹、郭巧玲、陳建州、葉耀鮮、高瑞鴻、林柏丞、范毅軍、詹大千（2016）。利用政府開放性資料建構台灣線上互動式疾病死因地圖。台灣公共衛生雜誌，35卷5期，頁553-566。
蕭佳賓（2012）。深度休閒者知識獲取行為模式之研究。國立臺灣師範大學公民教育與活動領導學系博士學位論文。
蕭景燈（2012）。資料開放發展現況與展望。研考雙月刊，36卷4期，頁22-38。
謝雨生（2015）。研究設計。載於瞿海源、畢恆達、劉長萱、楊國樞（主編），社會及行為科學研究法：總論與量化研究法（頁65-106）。臺北市：臺灣東華。
賽明成、陳建維（2010）。紮根理論與質性研究：調和觀點。問題與研究，49卷1期，頁1-28。
鍾張涵（2020年3月19日）。以色列稱讚、美國想合作：揭密台灣科技防疫國家隊。天下雜誌。上網日期2023年8月26日，檢自：https://www.cw.com.tw/article/article.action?id=5099449
藍佩嘉（2015）。質性個案研究：紮根理論與延伸個案法。載於瞿海源、畢恆達、劉長萱、楊國樞（主編），社會及行為科學研究法：質性研究法（頁63-96）。臺北市：臺灣東華。
羅晉、楊東謀、王慧茹、項靖（2014）。政府開放資料的策略與挑戰：使用者觀點的分析。電子商務研究，12卷3期，頁283-300。
蘇文彬（2020年1月7日）。立專法保證政府開放資料品質，國發會揭臺灣首部開放資料法草案推動時程和方向。iThome網路新聞。上網日期2023年8月25日，檢自：https://www.ithome.com.tw/news/135213
蘭韻綺（2015）。我國產銷履歷開放資料現況與困境之研究。東華大學行政管理暨政策學系研究所碩士學位論文。
龔美文、楊惠如、曾梓展（2020）。衛生局運用政府開放品質指標經驗分享。醫療資訊雜誌，29卷1期，頁1-6。
Adolph, S., Hall, W., & Kruchten, P. (2011). Using grounded theory to study the experience of software development. Empirical Software Engineering, 16, 487-513. https://doi.org/10.1007/s10664-010-9152-6
Ae Chun, S., Luna-Reyes, L. F., & Sandoval-Almazan, R. (2012). Collaborative e-government. Transforming Government: People, Process and Policy, 6(1), 5-12.
Albano, C. S. & Reinhard, N. (2014). Open government data: Facilitating and motivating factors for coping with potential barriers in the Brazilian context. In M. Janssen, H. Scholl, M. Wimmer, & F. Bannister (Eds.), Proceedings of the 2014 International Conference on Electronic Government, 181-193.
Arispe, M. C. A., Jaucian, R. B., Platon, A. B., Relucio, F. S., & Saminiano, B. L. (2020). Developing an electrical outlet using internet of things (Iot). International Journal, 9(1.3).
Association of Research Libraries (2004). FRAMING THE ISSUE: OPEN ACCESS. Retrieved August 25, 2023, from: https://www.arl.org/wp-content/uploads/2004/05/framing-issue-open-access-may04.pdf
Attard, J., Orlandi, F., Scerri, S., & Auer, S. (2015). A systematic review of open government data initiatives. Government Information Quarterly, 32(4), 399-418.
Baddoo, N., Hall, T., & Jagielska, D. (2006). Software developer motivation in a high maturity company: a case study. Software process: improvement and practice, 11(3), 219-228.
Bandura, A. (2010). Self‐efficacy. In The Corsini encyclopedia of psychology. Retrieved August 25, 2023, from https://doi.org/10.1002/9780470479216.corpsy0836
Bartenberger, M. & Grubmüller, V. (2014). The enabling effects of open government data on collaborative governance in smart city contexts. eJournal of eDemocracy and Open Government, 6(1), 36-48.
Baumbusch, J. (2010). Semi-structured interviewing in practice-close research. Journal for Specialists in Pediatric Nursing, 15(3), 255.
Birks, M. & Mills, J. (2011). Grounded Theory: A Practical Guide. Sage.
Bishop, B. W., Hank, C., Webster, J., & Howard, R. (2019). Scientists' data discovery and reuse behavior:(Meta) data fitness for use and the FAIR data principles. Proceedings of the Association for Information Science and Technology, 56(1), 21-31.
Böhm, C., Freitag, M., Heise, A., Lehmann, C., Mascher, A., Naumann, F., Ercegovac, V., Hernandez, M., Haase, P., & Schmidt, M. (2012). GovWILD: integrating open government data for transparency. In E. Egyed-Zsigmond,Y. Gripay, C. Favre, & C. Largeron (Eds.) Proceedings of the 21st International Conference on World Wide Web, 321-324.
Borgman, C. L., Darch, P. T., Sands, A. S., & Golshan, M. S. (2016). The durability and fragility of knowledge infrastructures: Lessons learned from astronomy. Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives through Information & Technology, 1-10.
Botsis, T., Hartvigsen, G., Chen, F., & Weng, C. (2010). Secondary Use of EHR: Data Quality Issues and Informatics Opportunities. In M. Eneida (Ed.) Proceedings of Summit on translational bioinformatics, 1-5.
Breznau, N. (2020, April 9). Novel coronavirus pandemic and the limits of open science. Crowdid. Retrieved August 26, 2023, from: https://crowdid.hypotheses.org/270
Brhel, M., Meth, H., Maedche, A., & Werder, K. (2015). Exploring principles of user-centered agile software development: A literature review. Information and software technology, 61, 163-181.
Browne, K. (2005). Snowball sampling: using social networks to research non‐heterosexual women. International journal of social research methodology, 8(1), 47-60.
Buijink, A. W., Visser, B. J., & Marshall, L. (2013). Medical apps for smartphones: lack of evidence undermines quality and safety. BMJ Evidence-Based Medicine, 18(3), 90-92.
Byström, K. & Hansen, P. (2005). Conceptual Framework for Tasks in Information Studies. Journal of the American Society for Information Science and Technology, 56(10),1050–1061.
Byström, K. & Järvelin, K. (1995). Task complexity affects information seeking and use. Information Processing & Management, 31(2), 191-213.
Byström, K. (2005). Information activities in work tasks. In K. E. Fisher, S. Erdelez, & L. McKechnie (Eds.), Theories of Information Behavior (pp. 174-178). Information Today, Inc.
Cabinet Office of the United Kingdom (2012), Open Data White Paper: unleashing the potential. Retrieved August 27, 2023, from: https://www.gov.uk/government/publications/open-data-white-paper-unleashing-the-potential
Caplan, R., Davies, T., Wadud, A., Verhulst, S., Alonso, J., & Farhan, H. (2014). Towards common methods for assessing open data: workshop report & draft framework. Retrieved August 27, 2023, from: https://blog.thegovlab.org/towards-common-methods-for-assessing-open-data
Case, D. O. (2006). Information behavior. Annual review of information science and technology, 40(1), 293-327.
Case, D. O. (2007). Looking for Information: A Survey of Research on Information Seeking, Needs, and Behavior (B. Boyce, Ed.). Elsevier.
Caswell, T., Henson, S., Jensen, M., & Wiley, D. (2008). Open content and open educational resources: Enabling universal education. The International Review of Research in Open and Distributed Learning, 9(1), 1-11.
Chan, C. M. (2013). From open data to open innovation strategies: Creating e-services using open government data. In R. Sprague (Ed.), Proceedings of 2013 46th Hawaii International Conference on System Sciences, 1890-1899.
Cheng, W.-C. & Chiu, M.-H. (2019, October 27-November 11). How Do Medical Researchers Use Open Health Data? A Case Study on Data Reuse Behavior of Using NHIRD in Taiwan [Conference poster presentation]. 2017 Annual Meeting of the Association for Information Science and Technology, Washington D.C., VA, United States.
Chuttur M.Y. (2009). Overview of the Technology Acceptance Model: Origins, Developments and Future Directions. Sprouts: Working Papers on Information Systems, 9(37), 1-21.
Cole, C. (2011). A theory of information need for information retrieval that connects information to knowledge. Journal of the American Society for Information Science and Technology, 62(7), 1216-1231.
Corbin, J. & Strauss, A. (1990). Grounded theory research: Procedures, canons, and evaluative criteria. Qualitative sociology, 13(1), 3-21.

Creswell, J. (1998/2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches (3rd ed.). SAGE Publications.
Curty, R. G. & Qin, J. (2014). Towards a model for research data reuse behavior. Proceedings of the American Society for Information Science and Technology, 51(1), 1-4.
Curty, R. G., Crowston, K., Specht, A., Grant, B. W., & Dalton, E. D. (2017). Attitudes and norms affecting scientists’ data reuse. PloS one, 12(12). 1-22
Custers, B. & Uršič, H. (2016). Big data and data reuse: a taxonomy of data reuse for balancing big data benefits and personal data protection. International data privacy law, 6(1), 4-15.
Davies, T. (2010). Open data, democracy and public sector reform. A look at open government data use from data.gov.uk. Retrieved June 20, 2023, from: https://bit.ly/2VobLnB
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Unpublished doctoral dissertation]. Massachusetts Institute of Technology. https://dspace.mit.edu/bitstream/handle/1721.1/15192/14927137-MIT.pdf
Dawes, S., Vidiasova, L., & Parkhimovich, O. (2016). Planning and designing open government data programs: An ecosystem approach. Government Information Quarterly, 33(1), 15-27.
DeLone, W. H. & McLean, E. R. (2016). Information systems success measurement. Foundations and Trends® in Information Systems, 2(1), 3-11.
Deloitte LLP. (2012). Open Growth: Stimulating demand for open data in the UK. A briefing note from Deloitte Analytics. Deloitte Touche Tohmatsu Limited, London. Retrieved June 18, 2023, from: https://bit.ly/2BJh2Pt
deMarrais, K. B. (2003), Qualitative interview studies: Learning through experience. In K. deMarrais & S. Lapan (Eds.), Foundations for Research: Methods of Inquiry in Education and the Social Sciences (pp. 51-68). Routledge.
Dervin, B. & Foreman-Wernet, L. (2012). Sense-making methodology as an approach to understanding and designing for campaign audiences. In R. Rice & C. Atkin (Eds.), Public Communication Campaigns (pp. 261-283). Sage.
Desouza, K. C. & Bhagwatwar, A. (2012). Citizen apps to solve complex urban problems. Journal of urban technology, 19(3), 107-136.
Dugas, M. (2013). Why we need a large-scale open metadata initiative in health informatics-a vision paper on open data models for clinical phenotypes. Studies in health technology and informatics, 192, 899-902.
Duggan, J. & Brodie, M. L. (2015). Hephaestus: Data Reuse for Accelerating Scientific Discovery. Proceedings of the 7th Biennial Conference on Innovative Data Systems Research, 1-12.
Ellis, D. & Haugan, M. (1997). Modelling the information seeking patterns of engineers and research scientists in an industrial environment. Journal of documentation, 53(4), 384-403.
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4.
European Commission (2003), Directive 2003/98/EC of the European parliament and of the council on the re-use of public sector information. Official Journal of the European Union. Retrieved August 27, 2023, from: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2003:345:0090:0096:en:PDF
Executive Office of the President of the United States (2013), Open Data Policy-Managing Information as an Asset. Retrieved June 12, 2023, from: https://obamawhitehouse.archives.gov/sites/default/files/omb/memoranda/2013/m-13-13.pdf
Eysenbach, G. (2006). Citation advantage of open access articles. PLoS biology, 4(5), e157. 692-698.
Facilitate Open Science Training for European Research (n.d.). What is Open Science? Retrieved August 27, 2023, from: https://www.fosteropenscience.eu/node/1420
Ferro, E. & Osella, M. (2013, April 23-24). Eight Business Model Archetypes for PSI Re-Use. [Workshop presentation]. Open Data on the Web Workshop, Google Campus, Shoreditch, London. Retrieved August 27, 2023, from: http://www.w3.org/2013/04/odw/odw13_submission_27.pdf
Flora, H. K., Wang, X., & Chande, S. V. (2014). An investigation into mobile application development processes: Challenges and best practices. International Journal of Modern Education and Computer Science, 6, 1-9. https://doi.org/10.5815/ijmecs.2014.06.01
Füller, J., Hutter, K., & Faullant, R. (2011). Why co‐creation experience matters? Creative experience and its impact on the quantity and quality of creative contributions. R&D Management, 41(3), 259-273.
Gäde, M., Koolen, M., Hall, M., Bogers, T., & Petras, V. (2021). A Manifesto on Resource Re-Use in Interactive Information Retrieval. Proceedings of the 2021 Conference on Human Information Interaction and Retrieval, 141-149.
Gascó-Hernández, M., Martin, E. G., Reggi, L., Pyo, S., & Luna-Reyes, L. F. (2018). Promoting the use of open government data: Cases of training and engagement. Government Information Quarterly, 35(2), 233-242.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on engineering management, 50(3), 307-321.
Gerstberger, P. G. & Allen, T. J. (1968). Criteria used by research and development engineers in the selection of an information source. Journal of applied psychology, 52(4), 272-279
Glaser, B. & Strauss, A. (Eds.) (1967). The discovery of grounded theory: strategies for qualitative research. Aldine Pub. Co..
González-Prieto, Á., Perez, J., Diaz, J., & López-Fernández, D. (2023). Reliability in software engineering qualitative research through Inter-Coder Agreement. Journal of Systems and Software, 202, 111707.
Gonzalez-Teruel, A. & Abad-Garcia, M. (2012). Grounded theory for generating theory in the study of behavior. Library & Information Science Research, 34(1), 31-36.
Gonzalez-Zapata, F. & Heeks, R. (2015). The multiple meanings of open government data: Understanding different stakeholders and their perspectives. Government Information Quarterly, 32(4), 441-452.
Gregory, K., Groth, P., Scharnhorst, A., & Wyatt, S. (2019). Lost or found? Discovering data needed for research. Retrieved August 27, 2023, from arXiv: https://arxiv.org/abs/1909.00464
Gurstein, M. B. (2011). Open data: Empowering the empowered or effective data use for everyone?. First Monday, 16(2). Retrieved August 28, 2023, from: https://firstmonday.org/ojs/index.php/fm/article/view/3316/2764
Hablé, J. (2019). Value Drivers and Inhibitors in Municipal Open Government Data Ecosystems [Unpublished master’s thesis]. Delft University of Technology. http://resolver.tudelft.nl/uuid:1347feeb-dce7-44c7-b8b7-3f58f2dd254b
Hall, T., Sharp, H., Beecham, S., Baddoo, N., & Robinson, H. (2008). What do we know about developer motivation?. IEEE software, 25(4), 92-94.
Harrison, T., Pardo, T., & Cook, M. (2012). Creating open government ecosystems: A research and development agenda. Future Internet, 4(4), 900-928.
He, L. & Nahar, V. (2016). Reuse of scientific data in academic publications. Journal of Information Management. 68(4), 478-494.
Helbig, N., Cresswell, A., Burke, G., & Luna-Reyes, L. (2012). The dynamics of opening government data. Center for Technology in Government: A White Paper. Retrieved August 27, 2023, from https://ctg.albany.edu/media/pubs/pdfs/opendata.pdf
Herala, A., Kasurinen, J., & Vanhala, E. (2018). Views on open data business from software development companies. Journal of theoretical and applied electronic commerce research, 13(1), 91-105.
Holdren, J., Orszag, P., & Prouty, P. (2009). President’s memorandum on transparency and open government-Interagency collaboration. Retrieved August 27, 2023, from: https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/memoranda/2009/m09-12.pdf
International Telecommunication Union (2018, December 6), New ITU statistics show more than half the world is now using the Internet. Retrieved August 26, 2023 from: https://news.itu.int/itu-statistics-leaving-no-one-offline/
Janssen, M. & Zuiderwijk, A. (2014). Infomediary business models for connecting open data providers and users. Social Science Computer Review, 32(5), 694-711.
Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information systems management, 29(4), 258-268.
Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2012). The value of open government data: A strategic analysis framework. Proceedings of the 33th International Conference on Information Systems (Pre-ICIS Workshop). Retrieved August 27, 2023, from: https://bit.ly/2YG2Gs0
Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2013). Generating value from open government data. Proceedings of the 34th International Conference on Information Systems. Retrieved JAugust 27, 2023, from: https://aisel.aisnet.org/icis2013/proceedings/GeneralISTopics/5/
Jetzek, T., Avital, M., & Bjorn-Andersen, N. (2014). Data-driven innovation through open government data. Journal of theoretical and applied electronic commerce research, 9(2), 100-120.
Johanssen, J. O., Kleebaum, A., Bruegge, B., & Paech, B. (2019, September 23-27). How do practitioners capture and utilize user feedback during continuous software engineering? [Paper presentation]. 2019 IEEE 27th International Requirements Engineering Conference, Jeju Island, South Korea. https://ase.in.tum.de/lehrstuhl_1/research/paper/johanssen2019re.pdf
Johnson, P. & Robinson, P. (2014). Civic hackathons: Innovation, procurement, or civic engagement?. Review of Policy Research, 31(4), 349-357.
Johnstone, P. (2004). Mixed methods, mixed methodology health services research in practice. Qualitative health research, 14(2), 259-271.
Joo, S., Kim, S., & Kim, Y. (2017). An exploratory study of health scientists’ data reuse behaviors: Examining attitudinal, social, and resource factors. Aslib Journal of Information Management, 69(4), 389-407.
Juell-Skielse, G., Hjalmarsson, A., Johannesson, P., & Rudmark, D. (2014). Is the public motivated to engage in open data innovation?. In M. Janssen, H. Scholl, M. Wimmer, & F. Bannister (Eds.), Proceedings of the 2014 International Conference on Electronic Government, 277-288.
Kaasenbrood, M., Zuiderwijk, A., Janssen, M., de Jong, M., & Bharosa, N. (2015). Exploring the factors influencing the adoption of open government data by private organisations. International Journal of Public Administration in the Digital Age, 2(2), 75-92.
Kalampokis, E., Tambouris, E., & Tarabanis, K. (2011). A classification scheme for open government data: towards linking decentralised data. International Journal of Web Engineering and Technology, 6(3), 266-285.
Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government Information Quarterly, 30(4), 508-513.
Kebede, M., Adeba, E., & Chego, M. (2020). Evaluation of quality and use of health management information system in primary health care units of east Wollega zone, Oromia regional state, Ethiopia. BMC medical informatics and decision making, 20(1), 1-12.
Kipper, L. M., Iepsen, S., Dal Forno, A. J., Frozza, R., Furstenau, L., Agnes, J., & Cossul, D. (2021). Scientific mapping to identify competencies required by industry 4.0. Technology in Society, 64, 101454.
Kluth, A. (2020, April 22). If We Must Build a Surveillance State, Let’s Do It Properly. Retrieved June 18, 2023, from: https://bloom.bg/2NzXlwd
Krebs, P. & Duncan, D. T. (2015). Health app use among US mobile phone owners: a national survey. JMIR mHealth and uHealth, 3(4), e101, 1-12.
Krikelas, J. (1983). Information-seeking behavior: Patterns and concepts. Drexel library quarterly, 19(2), 5-20.
Kubler, S., Robert, J., Neumaier, S., Umbrich, J., & Le Traon, Y. (2018). Comparison of metadata quality in open data portals using the Analytic Hierarchy Process. Government Information Quarterly, 35(1), 13-29.
Kuhlthau, C. (2005). Kuhlthau’s information search process. In K. E. Fisher, S. Erdelez, & L. McKechnie (Eds.), Theories of Information Behavior (pp. 230-234). Information Today, Inc.
Kvale, S. (1996). Interviews: an introduction to qualitative research interviewing. Sage Publications.
Lakhani, K. & Wolf, R. (2003). Why hackers do what they do: Understanding motivation and effort in free/open source software projects. Retrieved August 27, 2023, from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=443040
Laplante, P. (2007). What every engineer should know about software engineering. (chapter 5, pp.113-144). Routledge.
Lassinantti, J., Ståhlbröst, A., & Runardotter, M. (2019). Relevant social groups for open data use and engagement. Government Information Quarterly, 36(1), 98-111.
Leau, Y. B., Loo, W. K., Tham, W. Y., & Tan, S. F. (2012). Software development life cycle AGILE vs traditional approaches. International Conference on Information and Network Technology, 37(1), 162-167. Retrieved August 27, 2023, from: https://ku-fpg.github.io/files/agile-traditional.pdf
Leckie, G. (2005). General model of the information seeking of professionals. In K. E. Fisher, S. Erdelez, & L. McKechnie (Eds.), Theories of Information Behavior (pp. 158-163). Information Today, Inc.
Leckie, G., Pettigrew, K, & Sylvain, C. (1996). Modeling the information seeking of professionals: A general model derived from research on engineers, health care professionals, and lawyers. The Library Quarterly, 66(2), 161-193.
Lee, L.-W. & Chu, P.-Y. (2018). A User Approach to Open Government Data Impact Assessment. In R. Bouzas-Lorenzo & A. Ramos (Eds.), Proceedings of the 18th European Conference on Digital Government, 111-121.
Lee, M., Almirall, E., & Wareham, J. (2014). Open Data & civic apps: First generation failures, second generation improvements. Communications of the ACM, 59(1), 82-89.
Lee, Y. (2022). Development of Rapid, Low-cost, and Portable Device to Detect Infectious Diseases [Unpublished master’s thesis]. University of British Calgary. https://prism.ucalgary.ca/server/api/core/bitstreams/d83394d1-7a03-4750-ba1d-63f6a29e51a5/content
Lew, P., Olsina, L., & Zhang, L. (2010). Quality, quality in use, actual usability and user experience as key drivers for web application evaluation. In B. Benatallah, F. Casati, G. Kappel, & G. Rossi (Eds.), Proceedings of the International Conference on Web Engineering, 218-232.
Li, M.-F. & Pan, L.-C. (2012). Applications on Mobile-health. The Journal of Long-term Care, 16(3), 237-250.
Li, Y. F., Kennedy, G., Ngoran, F., Wu, P., & Hunter, J. (2013). An ontology-centric architecture for extensible scientific data management systems. Future Generation Computer Systems, 29(2), 641-653.
Linders, D. (2012). From e-government to we-government: Defining a typology for citizen coproduction in the age of social media. Government Information Quarterly, 29(4), 446-454.
Magalhaes, G. & Roseira, C. (2020). Open government data and the private sector: An empirical view on business models and value creation. Government Information Quarterly, 37(3), 1-10.
Magalhaes, G., Roseira, C., & Manley, L. (2014). Business models for open government data. Proceedings of the 8th International Conference on Theory and Practice of Electronic Governance, 365-370.
Mann, S. (Ed.) (2016). The research interview: reflective practice and reflexivity in research processes. Palgrave Macmillan.
Manyika, J., Chui, M., Buhin, J., Dobbs, R., & Roxburgh, C. (2011, May 1). Big Data: The Next Frontier for Innovation, Competition, and Productivity (A report by McKinsey Global Institute). Retrieved August 27, 2023, from: https://mck.co/2Z98ZU0
Manyika, J., Chui, M., Farrell, D., Kuiken, S., Groves, P., & Doshi, E. (2013, October 1). Open data: Unlocking innovation and performance with liquid information (A report by McKinsey Global Institute). Retrieved August 27, 2023, from: https://mck.co/2YEvXDB
Marangunić, N. & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal access in the information society, 14, 81-95.
Martin, E. G. & Begany, G. M. (2017). Opening government health data to the public: benefits, challenges, and lessons learned from early innovators. Journal of the American Medical Informatics Association, 24(2), 345-351.
Martin, E., Helbig, N., & Birkhead, G. (2015). Opening health data: what do researchers want? Early experiences with New York's open health data platform. Journal of Public Health Management and Practice, 21(5), E1-E7.
Martin, E., Helbig, N., & Shah, N. (2014). Liberating data to transform health care: New York’s open data experience. Journal of American Medical Association, 311(24), 2481-2482.
Martin, E., Law, J., Ran, W., Helbig, N., & Birkhead, G. (2017). Evaluating the quality and usability of open data for public health research: a systematic review of data offerings on 3 open data platforms. Journal of Public Health Management and Practice, 23(4), e5-e13.
Martin, E., Shah, N., & Birkhead, G. (2018). Unlocking the Power of Open Health Data: A Checklist to Improve Value and Promote Use. Journal of Public Health Management and Practice, 24(1), 81-84.
Maxwell, J. (2008). Designing a qualitative study. In L. Bickman & D. Rog (Eds.), The SAGE handbook of applied social research methods (2nd ed., pp. 214-253). Sage.
Mayernik, M. (2017). Open data: Accountability and transparency. Big Data and Society, 4(2), 1-5.
McBride, K., Aavik, G., Toots, M., Kalvet, T., & Krimmer, R. (2019). How does open government data driven co-creation occur? Six factors and a ‘perfect storm’; insights from Chicago's food inspection forecasting model. Government Information Quarterly, 36(1), 88-97.
McCusker, K. & Gunaydin, S. (2015). Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion, 30(7), 537-542.
Mergel, I. & Desouza, K. C. (2013). Implementing open innovation in the public sector: The case of Challenge.gov. Public administration review, 73(6), 882-890.
Mergel, I. (2014). The Long Way From Government Open Data to Mobile Health Apps: Overcoming Institutional Barriers in the US Federal Government. JMIR mHealth and uHealth, 2(4), e58, 1-13.
Meystre, S. M., Lovis, C., Bürkle, T., Tognola, G., Budrionis, A., & Lehmann, C. U. (2017). Clinical data reuse or secondary use: current status and potential future progress. Yearbook of medical informatics, 26(01), 38-52.
Milletler, B. (2019). Data Economy: Radical Transformation or Dystopia?. Frontier Technology Quarterly. Retrieved August 27, 2023, from: https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/FTQ_1_Jan_2019.pdf
Missier, P. (2016). Data trajectories: tracking reuse of published data for transitive credit attribution. International Journal of Digital Curation, 11(1), 1-16.
Moe, N. B., Šmite, D., Paasivaara, M., & Lassenius, C. (2021). Finding the sweet spot for organizational control and team autonomy in large-scale agile software development. Empirical Software Engineering, 26(5), 1-41.
Mohagheghi, P., Lassenius, C., & Bakken, I. O. (2020). Enabling Team Autonomy in a Large Public Organization. Agile Processes in Software Engineering and Extreme Programming – Workshops: XP 2020 Workshops, Copenhagen, Denmark, June 8-12, 2020, Revised Selected Papers, 396, 245–252. https://doi.org/10.1007/978-3-030-58858-8_25
Mourtzis, D. & Doukas, M. (2014). Knowledge capturing and reuse to support manufacturing of customised products: A case study from the mould making industry. Procedia CIRP, 21, 123-128.
National Network of Libraries of Medicine (n.d.). data reuse. Retrieved August 27, 2023, from: https://www.nnlm.gov/guides/data-glossary/data-reuse
Nelson, J. D., McKenzie, C. R., Cottrell, G. W., & Sejnowski, T. J. (2010). Experience matters: Information acquisition optimizes probability gain. Psychological science, 21(7), 960-969.
O’Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., & Cook, D. A. (2014). Standards for reporting qualitative research: a synthesis of recommendations. Academic medicine, 89(9), 1245-1251.
OECD (2016). Open Government Data Review of Mexico: Data Reuse for Public Sector Impact and Innovation. OECD Digital Government Studies, OECD Publishing, Paris. Retrieved August 29, 2023, from: https://www.oecd.org/gov/digital-government/open-government-data-review-of-mexico-9789264259270-en.htm
OECD (2019). The Path to Becoming a Data-Driven Public SectorOECD. Digital Government Studies. OECD Publishing, Paris. Retrieved August 29, 2023, from: https://www.oecd.org/gov/the-path-to-becoming-a-data-driven-public-sector-059814a7-en.htm
OECD (n.d.-a). Open Government Data. Retrieved June 28, 2023, from: https://www.oecd.org/gov/digital-government/open-government-data.htm/
OECD (n.d.-b). Rebooting Public Service Delivery-How can Open Government Data help drive innovation?. Retrieved August 29, 2023, from: https://www.oecd.org/gov/digital-government/rebooting-public-service-delivery.htm
Open Knowledge Foundation (2017). Global Open Data Index. Retrieved June 28, 2023, from: https://index.okfn.org/place/
Open Knowledge Foundation (n.d.-a). Why open data?. Retrieved August 29, 2023, from: https://opendatahandbook.org/guide/zh_TW/why-open-data/
Open Knowledge Foundation (n.d.-b). Why open data?. Retrieved August 29, 2023, from: https://opendatahandbook.org/guide/zh_TW/what-is-open-data/
Open Source Initiative (n.d.). About the Open Source Initiative. Retrieved August 29, 2023, from: https://opensource.org/about
Opher, A., Onda, A., Chou, A., & Sounderrajan, K. (2016). The Rise of the Data Economy: Driving Value through Internet of Things Data Monetization. Retrieved August 29, 2023, from: https://admin02.prod.blogs.cis.ibm.net/blogs/think/2016/03/iot-data-monetization/
Pam, M. (2013). QUASI NEED. Retrieved August 29, 2023, from PsychologyDictionary.org: https://psychologydictionary.org/quasi-need/
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of marketing, 49(4), 41-50.
Pasquetto, I., Randles, B., & Borgman, C. (2017). On the reuse of scientific data. Data Science Journal, 16, 1-9.
Peixoto, T. (2012). The Uncertain Relationship between Open Data and Accountability: Response to Yu and Robinson's the New Ambiguity of Open Government. UCLA Law Review Discourse, 60, 200-213.
Pereira, G. V., Macadar, M. A., Luciano, E. M., & Testa, M. G. (2017). Delivering public value through open government data initiatives in a Smart City context. Information Systems Frontiers, 19(2), 213-229.
Perez, S. (2020, April 30). Twitter launches a COVID-19 data set of tweets for approved developers and researchers. Retrieved August 29, 2023, from: https://tcrn.ch/2Zh0pmj
Perrin, A. & Kumar, M. (2021, March 26). About three-in-ten U.S. adults say they are “almost constantly” online. Retrieved August 29, 2023, from: https://pewrsr.ch/3dHypNX
Pew Research Center (2021, April 7). Internet/Broadband Fact Sheet. Retrieved August 29, 2023, from: https://www.pewinternet.org/fact-sheet/internet-broadband/
Piwowar H, Priem J, Larivière V, Alperin JP, Matthias L, Norlander B, Farley A, West J, Haustein S. (2018). The state of OA: a large-scale analysis of the prevalence and impact of Open Access articles. PeerJ 6, e4375. https://doi.org/10.7717/peerj.4375
Piwowar, H. & Vision, T. (2013). Data reuse and the open data citation advantage. PeerJ, 1, e175.
Piwowar, H., Day, R., & Fridsma, D. (2007). Sharing detailed research data is associated with increased citation rate. PloS one, 2(3), e308.
Ponte, D. (2015). Enabling an open data ecosystem (ECIS 2015 Research-in-Progress Papers, Paper 55). Retrieved August 29, 2023, from: http://aisel.aisnet.org/ecis2015_rip/55
Pontika, N., Knoth, P., Cancellieri, M., & Pearce, S. (2015). Fostering open science to research using a taxonomy and an eLearning portal. Proceedings of the 15th international conference on knowledge technologies and data-driven business, 1-8.
Provost, F. & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big data, 1(1), 51-59.
Rea, S., Pathak, J., Savova, G., Oniki, T., Westberg, L., Beebe, C., Tao, C., Parker, C., Haug, P., Huff, S., & Chute, C. (2012). Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: the SHARPn project. Journal of biomedical informatics, 45(4), 763-771.
Reeve, J. (2015). Understanding motivation and emotion (6th ed.). John Wiley & Sons, Inc.
Rosenbaum, S. (2010). Data governance and stewardship: designing data stewardship entities and advancing data access. Health services research, 45(5p2), 1442-1455.
Ruijer, E., Grimmelikhuijsen, S., & Meijer, A. (2017). Open data for democracy: Developing a theoretical framework for open data use. Government Information Quarterly, 34(1), 45-52.
Ryan, R. & Deci, E. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary educational psychology, 25(1), 54-67.
Safran, C. (2017). Update on Data Reuse in Health Care. Yearbook of medical informatics, 26(01), 24-27.
Sands, A., Borgman, C. L., Wynholds, L., & Traweek, S. (2012). Follow the data: How astronomers use and reuse data. Proceedings of the American Society for Information Science and Technology , 49(1), 1-3.
Saravanan, T., Jha, S., Sabharwal, G., & Narayan, S. (2020). Comparative Analysis of Software Life Cycle Models. Proceedings of 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 906-909.
Schoenherr, T. & Speier‐Pero, C. (2015). Data science, predictive analytics, and big data in supply chain management: Current state and future potential. Journal of Business Logistics, 36(1), 120-132.
Schultheiss, O. & Brunstein, J. (Eds.) (2010). Implicit motives. Oxford University Press.
Seidel, S. & Urquhart, C. (2013). On emergence and forcing in information systems grounded theory studies: The case of Strauss and Corbin. Journal of Information Technology, 28(3), 237-260.
Sharp, H., Baddoo, N., Beecham, S., Hall, T., & Robinson, H. (2009). Models of motivation in software engineering. Information and software technology, 51(1), 219-233.
Shaw, E. (2014, June 25). The Impact of Open: Keeping you healthy. Retrieved August 29, 2023, from: https://sunlightfoundation.com/2014/06/25/the-impact-of-open-keeping-you-healthy/
Shen, Y. & Varvel Jr, V. (2013). Developing data management services at the Johns Hopkins University. The Journal of Academic Librarianship, 39(6), 552-557.
Shih, F., Seneviratne, O., Liccardi, I., Patton, E., Meier, P., & Castillo, C. (2013). Democratizing mobile app development for disaster management. Joint Proceedings of the Workshop on AI Problems and Approaches for Intelligent Environments and Workshop on Semantic Cities, 39-42.
Snah, S (2019, January 15). US signs act that opens government data to the public into law. Retrieved August 29, 2023, from: https://www.engadget.com/2019/01/15/open-government-data-act-law/
Solar, M., Concha, G., & Meijueiro, L. (2012). A model to assess open government data in public agencies. In H. Scholl, M. Janssen, M. Wimmer, C. Moe, L. Flak (Eds.), Proceedings of the 2012 International Conference on Electronic Government, 210-221.
Sollazzo, G. & Miller, D. (2017). Open data in the health sector-Users, stories, products and recommendations. Retrieved August 29, 2023, from: http://openhealthcare.org.uk/open-data-in-the-health-sector/
Stebbins, R. (2001). The costs and benefits of hedonism: Some consequences of taking casual leisure seriously. Leisure studies, 20(4), 305-309.
Suber, P. (2012). Open access. MIT Press. Retrieved August 29, 2023, from: https://dash.harvard.edu/handle/1/10752204
Sui, C. (2020, March 14). What Taiwan can teach the world on fighting the coronavirus?. Retrieved August 29, 2023, from: https://nbcnews.to/2YFjuPX
Susha, I., Grönlund, Å., & Janssen, M. (2015). Driving factors of service innovation using open government data: An exploratory study of entrepreneurs in two countries. Information Polity, 20(1), 19-34.
Tansley, S. & Tolle, K. (2009). The fourth paradigm: data-intensive scientific discovery (Vol. 1). In T. Hey (Ed.). Microsoft research.
Tashakkori, A. & Creswell, J. W. (2007). Exploring the nature of research questions in mixed methods research. Journal of Mixed Methods Research, 1(3), 207-211.
Tauberer, J. (2014). Open Government Data: The Book (2nd ed.). Retrieved August 29, 2023, from: https://opengovdata.io/2014/8-principles/
Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., ... & Frame, M. (2011). Data sharing by scientists: practices and perceptions. PloS one, 6(6), e21101.
Tenopir, C., Dalton, E., Allard, S., Frame, M., Pjesivac, I., Birch, B., Pollock, D., & Dorsett, K. (2015). Changes in data sharing and data reuse practices and perceptions among scientists worldwide. PloS One, 10(8), 1-24.
The Economist (2017, May 6). The world's most valuable resource; regulating the data economy. The Economist, 423(9). Retrieved August 29, 2023, from: https://www.proquest.com/magazines/worlds-most-valuable-resource-regulating-data/docview/1895941741/se-2?accountid=14229
Tolle, K., Tansley, D., & Hey, A. (2011). The fourth paradigm: Data-intensive scientific discovery. Proceedings of the IEEE, 99(8), 1334-1337. Retrieved August 29, 2023, from: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5958175
Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. International journal for quality in health care, 19(6), 349-357.
Tongco, M. (2007). Purposive sampling as a tool for informant selection. Ethnobotany Research and applications, 5, 147-158.
Toots, M., McBride, K., Kalvet, T., Krimmer, R., Tambouris, E., Panopoulou, E., Panopoulou, E., Kalampokis, E., & Tarabanis, K. (2017). A framework for data-driven public service co-production. In M. Janssen, K. Axelsson, O. Glassey, B. Klievink, R. Krimmer, I. Lindgren, P. Parycek, H. Scholl, & D. Trutnev (Eds.), Proceedings of the 2017 International Conference on Electronic Government, 264-275.
Ubaldi, B. (2013). Open Government Data: Towards Empirical Analysis of Open Government Data Initiatives (OECD Working Papers on Public Governance, No. 22). OECD Publishing. Retrieved August 29, 2023, from: http://dx.doi.org/10.1787/5k46bj4f03s7-en
Ullman, J. (2017). Technical Perspective: Building a safety net for data reuse. Communications of the ACM, 60(4), 85.
Unger, R. (2019). The knowledge economy. Retrieved August 29, 2023, from: https://www.oecd.org/naec/THE-KNOWLEDGE-ECONOMY.pdf
United Nations Educational, Scientific and Cultural Organization (2022). UNESCO Recommendation on Open Science. Retrieved August 29, 2023, from: https://unesdoc.unesco.org/ark:/48223/pf0000379949.locale=en
Vadlamani, S. L., & Baysal, O. (2020). Studying software developer expertise and contributions in Stack Overflow and GitHub. Proceedings of 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME), 312-323.
Vakkari, P. (2003). Task‐based information searching. Annual review of information science and technology, 37(1), 413-464.
van de Sandt, S., Lavasa, A., Dallmeier-Tiessen, S., & Petras, V. (2019). The Definition of Reuse. Data Science Journal, 18(22), 1-19.
Vasa, M. & Tamilselvam, S. (2014). Building apps with open data in India: An experience. Proceedings of the 2014 International Workshop on Inclusive Web Programming-Programming on the Web with Open Data for Societal Applications, 1-7.
Verhulst, S. G. (2020, May 15). Unlock the Hidden Value of Your Data. Retrieved August 29, 2023, from Harvard Business Review: https://hbr.org/2020/05/unlock-the-hidden-value-of-your-data
Vetrò, A., Canova, L., Torchiano, M., Minotas, C. O., Iemma, R., & Morando, F. (2016). Open data quality measurement framework: Definition and application to Open Government Data. Government Information Quarterly, 33(2), 325-337.
Vila-Henninger, L. A. (2019). Turning talk into “rationales”: Using the extended case method for the coding and analysis of semi-structured interview data in ATLAS. ti. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 143(1), 28-52.
Wang, H.-J. (2020). Adoption of open government data: perspectives of user innovators. Information Research, 25(1). Retrieved August 29, 2023, from: http://informationr.net/ir/25-1/paper849.html
Wang, X., Duan, Q., & Liang, M. (2021). Understanding the process of data reuse: An extensive review. Journal of the Association for Information Science and Technology, 72, 1161-1182.
Wang, X., Liu, C., Mao, W., & Fang, Z. (2015). The open access advantage considering citation, article usage and social media attention. Scientometrics, 103, 555-564.
Weiskopf, N. & Weng, C. (2013). Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. Journal of the American Medical Informatics Association, 20(1), 144-151.
Widén, G., Steinerová, J., & Voisey, P. (2014). Conceptual modelling of workplace information practices: a literature review. Information Research, 19(4), Retrieved August 29, 2023, from: https://informationr.net/ir/19-4/isic/isic08.html#.XtOUry9Djw4
Wijnhoven, F., Ehrenhard, M., & Kuhn, J. (2015). Open government objectives and participation motivations. Government information quarterly, 32(1), 30-42.
Wiley, D. (n.d.). open content definition. Retrieved August 29, 2023, from: https://www.opencontent.org/definition/
Wiley, D., Bliss, T.J., McEwen, M. (2014). Open Educational Resources: A Review of the Literature. In: Spector, J., Merrill, M., Elen, J., Bishop, M. (eds) Handbook of Research on Educational Communications and Technology. Springer. https://doi.org/10.1007/978-1-4614-3185-5_63
Wilkinson, M., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., ... & Bouwman, J. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3, 160018.
Williams, J. (1988). A structured interview guide for the Hamilton Depression Rating Scale. Archives of general psychiatry, 45(8), 742-747.
Wilson, T. (1999). Models in information behaviour research. Journal of documentation, 55(3), 249-270.
Wilson, T. (2000). Human information behavior. Informing science, 3(2), 49-56.
Woolley, K. & Fishbach, A. (2015). The Experience Matters More Than You Think: Weighting Intrinsic Incentives More Inside Than Outside of an Activity. Proceedings of the 2015 Association for Consumer Research, 62-67.
World Wide Web Consortium (2013). 5 Star Linked Data. Retrieved August 29, 2023, from: https://www.w3.org/2011/gld/wiki/5_Star_Linked_Data
Wu, C., Kao, S.-C., Shih, C.-H., & Kan, M.-H. (2018). Open data mining for Taiwan’s dengue epidemic. Acta tropica, 183, 1-7.
Yang, B., Liu, Y., Liang, Y., & Tang, M. (2019). Exploiting user experience from online customer reviews for product design. International Journal of Information Management, 46, 173-186. http://doi.org/10.1016/j.ijinfomgt.2018.12.006
Ye, Y. & Kishida, K. (2003). Toward an understanding of the motivation of open source software developers. Proceedings of the 25th International Conference on Software Engineering, 419-429.
Yoon, A. & Kim, Y. (2017). Social scientists' data reuse behaviors: Exploring the roles of attitudinal beliefs, attitudes, norms, and data repositories. Library & Information Science Research, 39(3), 224-233.
Yoon, A. & Kim, Y. (2020). The role of data-reuse experience in biological scientists’ data sharing: an empirical analysis. The Electronic Library. 38(1), 186-208.
Yoon, A. & Lee, Y. Y. (2019). Factors of trust in data reuse. Online Information Review, 43(7), 1245-1262.
Yoon, A. (2015). Data reuse and users' trust judgments: Toward trusted data curation. [Unpublished doctoral dissertation]. University of North Carolina at Chapel Hill. https://www.proquest.com/dissertations-theses/data-reuse-users-trust-judgments-toward-trusted/docview/1718199510/se-2
Yu, H. & Robinson, D. (2011). The new ambiguity of open government. UCLA Law Review Discourse, 59, 178-208.
Zarour, A. & Zein, S. (2019). Software development estimation techniques in industrial contexts: An exploratory multiple case-study. International Journal of Technology in Education and Science, 3(2), 72-84. http://doi.org/10.1007/978-3-319-22689-7_3
Zeleti, F. A., Ojo, A., & Curry, E. (2016). Exploring the economic value of open government data. Government Information Quarterly, 33(3), 535-551.
Zhang, Y. & Wildemuth, B. M. (2009). Unstructured interviews. Retrieved August 30, 2023, from: https://www.ischool.utexas.edu/~yanz/Unstructured_interviews.pdf
Zhang, Y.-C. (2017). The information economy. In J. Johnson, A. Nowak, P. Ormerod, B. Rosewell, & Y.-C. Zhang (Eds.), Non-Equilibrium Social Science and Policy (pp. 149-158). Springer.