مقاله انگلیسی رایگان در مورد کلان داده در خط مشی گذاری – اسپرینگر ۲۰۱۷

مقاله انگلیسی رایگان در مورد کلان داده در خط مشی گذاری – اسپرینگر ۲۰۱۷

 

مشخصات مقاله
انتشار مقاله سال ۲۰۱۷
تعداد صفحات مقاله انگلیسی ۱۶ صفحه
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نوع مقاله ISI
عنوان انگلیسی مقاله Big data for policymaking: fad or fasttrack?
ترجمه عنوان مقاله کلان داده در خط مشی گذاری: محو و نابودی یا احتمال ترقی
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مدیریت
گرایش های مرتبط مدیریت استراتژیک
مجله علوم سیاسی – Policy Sciences
دانشگاه Institute of Public Administration – Leiden University – Netherlands
کلمات کلیدی کلان داده، سیاستگذاری مبتنی بر شواهد، طراحی سیاسی، آمادگی داده ها، حکومت عصر دیجیتال، ابزارهای سیاست
کلمات کلیدی انگلیسی Big data, Evidence-based policymaking, Policy design, Data readiness, Digital-era governance, Policy instruments
شناسه دیجیتال – doi https://doi.org/10.1007/s11077-017-9293-1
کد محصول E8157
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Introduction

Big data is a broad term for the volume and complexity of data that is available. While there is no widely accepted definition of the term, the most basic description is that big data means datasets that are too large for traditional processing systems and require new technologies (Provost and Fawcett 2013). This not only refers to the size of the data, but also to its variety, velocity and veracity. This means that data is collected faster and that there is more variation of data that can be tapped into. Veracity refers to the uncertainty of data. This has to do both with the quality of the data, but also with the uncertainty of those dealing with the data of how accurate and complete this resource is. At the same time, the combination of digitizing administrative data, collecting data through various devices and storing more data has led to dedicated big and open data initiatives by governments. The increasingly affordable extraction of information from big data and the promise of cutting costs have also facilitated this movement. High-profile examples such as ‘data-driven campaigning’ in the 2012 and 2016 US election or the use of data for predicting where building are at risk for fires by the New York Mayor’s Office of Data Analytics (MODA) have spurred interest further. Similar developments took place in Europe, where, for example, the European Statistics Office has established a Big Data Group or the UK National Office of Statistics now has a dedicated Big Data Project. The use of big data has been categorized as a shift at the scale of the Industrial Revolution (Richards and King 2014). Others insist that essentially nothing has changed except for datasets getting bigger. Scholars at both ends of the spectrum, however, foresee changes in the way policymaking is being done and the way it affects citizens. The former group hopes for decisions that are faster, better supported by evidence and containing less uncertainty. More critical voices revisit the obstacles outlined by the evidence-based policy discussion where different forms of information compete in the policymaking process and further require the capacity of decision-makers to comprehend it. In short, using big data for policymaking is not new, but the way the potential or actual use of big data applications changes some of the theoretical and practical discussions surrounding decision-making is.

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