【正文】 predicting traffic congestion[38] to fighting cancer.[39]該計劃包括國家科學(xué)基金會“計算探險”向加州大學(xué)伯克利分校AMPLab實驗室的5年1000萬美元的捐款，該實驗室（AMPLab）還受到了來自DAPARA的資金以及十?dāng)?shù)個行業(yè)贊助，目的是使用大數(shù)據(jù)來解決廣泛的問題，范圍從預(yù)測交通阻塞到與癌癥抗爭。The White House Big Data Initiative also included a mitment by the Department of Energy to provide $25 million in funding over 5 years to establish the Scalable Data Management, Analysis and Visualization (SDAV) Institute,[40] led by the Energy Department’s Lawrence Berkeley National Laboratory. The SDAV Institute aims to bring together the expertise of six national laboratories and seven universities to develop new tools to help scientists manage and visualize data on the Department’s superputers.白宮的大數(shù)據(jù)計劃還包括能源部承諾的提供2500萬美元的資金在5年內(nèi)建立可擴展的數(shù)據(jù)管理、分析和可視化（SDAV）研究所，由能源部的勞倫斯伯克利國家實驗室主導(dǎo)。SDAV實驗室旨在將六個國家實驗室和7所大學(xué)的專業(yè)人士聚合在一起開發(fā)新的工具來幫助科學(xué)家們對能源部的超級計算機上的數(shù)據(jù)進行管理和可視化。The . state of Massachusetts announced the Massachusetts Big Data Initiative in May 2012, which provides funding from the state government and private panies to a variety of research institutions.[41] The Massachusetts Institute of Technology hosts the Intel Science and Technology Center for Big Data in the MIT Computer Science and Artificial Intelligence Laboratory, bining government, corporate, and institutional funding and research efforts.[42]美國馬薩諸塞州政府在2012年5月宣布了馬薩諸塞州大數(shù)據(jù)計劃（Massachusetts Big Data Initiative），它從州政府和私人公司提供資金給各種研究所。馬薩諸塞技術(shù)研究所主辦的麻省理工學(xué)院（MIT）計算機科學(xué)和人工智能實驗室的大數(shù)據(jù)Intel科學(xué)與技術(shù)中心聯(lián)合了政府、公司和機構(gòu)資金進行研究工作。Critiquedanah Boyd has raised concerns about the use of big data in science neglecting principles such as choosing a representative sample by being too concerned about actually handling the huge amounts of data.[43] This approach may lead to results biased in one way or another. Integration across heterogeneous data resources — some that might be considered big data and others not — presents formidable logistical as well as analytical challenges, but many researchers argue that such integrations are likely to represent the most promising new frontiers in science.[44] Broader critiques have also been levelled at Chris Anderson39。s assertion that big data will spell the end of theory: focusing in particular on the notion that big data will always need to be contextualized in their social, economic and political contexts.[45] Even as panies invest eight and ninefigure sums to derive insight from information streaming in from suppliers and customers, less than 40% of employees have sufficiently mature processes and skills to do so. To overe this insight deficit, big data, no matter how prehensive or well analyzed, needs to be plemented by big judgment, according to an article in the Harvard Business Review.[46]Danah Boyd提出了對忽視科學(xué)準則使用大數(shù)據(jù)的擔(dān)憂，包括選擇過于專注對大量數(shù)據(jù)實際處理的代表性樣本。這種方式可能導(dǎo)致結(jié)果有某種偏見。對異構(gòu)數(shù)據(jù)源的集成（綜合）——有些人認為是大數(shù)據(jù)而另外一些則不同意——提出了巨大的物流和分析的挑戰(zhàn)，但是許多研究人員認為這種集成很可能代表最有前途的科學(xué)前沿。Broader critiques have also been levelled at Chris Anderson39。s assertion that big data will spell the end of theory:更廣泛的爭論在Chris Anderson的“大數(shù)據(jù)將終結(jié)的理論”的斷言所平息：關(guān)注在特定的概念上，就是大數(shù)據(jù)將總是需要存在在社會、經(jīng)濟和政治背景之中。根據(jù)哈佛商業(yè)觀察的一篇文章，當(dāng)公司向從來自供應(yīng)商和客戶的信息流推導(dǎo)洞察（這種解決方案）投資89位數(shù)時，低于40%的員工具備足夠的處理技能。為了克服這種洞察的不足，“大數(shù)據(jù)”，無論怎樣全面和很好的分析，都需要由“大判斷”來補充。Consumer privacy advocates are concerned about the threat to privacy represented by increasing storage and integration of personally identifiable information。 expert panels have released various policy remendations to conform practice to expectations of privacy.[47]消費者私密性倡導(dǎo)者們對由越來越多的個人身份信息的存儲和集成為代表的隱私（暴露）的擔(dān)憂。專家們已經(jīng)發(fā)布了各種策略建議來遵守預(yù)期的私密