scholarly journals Governing Big Data

2014 ◽  
Vol 2 (1) ◽  
pp. 1-3 ◽  
Author(s):  
Andrej J. Zwitter ◽  
Amelia Hadfield

2.5 quintillion bytes of data are created every day through pictures, messages, gps-data, etc. "Big Data" is seen simultaneously as the new Philosophers Stone and Pandora's box: a source of great knowledge and power, but equally, the root of serious problems.

Author(s):  
Dawn E. Holmes

Since long before computers were even thought of, data has been collected and organized by diverse cultures across the world. Once access to the Internet became a reality for large swathes of the world’s population, the amount of data generated each day became huge, and continues to grow exponentially. It includes all our uploaded documents, videos, and photos; all our social media traffic; our online shopping; even the GPS data from our cars. Big Data: A Very Short Introduction explains how big data works and is changing the world around us, the effect it has on our everyday lives and in the business world, and it considers the attendant security risks.


Author(s):  
Adham Kalila ◽  
Zeyad Awwad ◽  
Riccardo Di Clemente ◽  
Marta C. González

Falling oil revenues and rapid urbanization are putting a strain on the budgets of oil-producing nations, which often subsidize domestic fuel consumption. A direct way to decrease the impact of subsidies is to reduce fuel consumption by reducing congestion and car trips. As fuel consumption models have started to incorporate data sources from ubiquitous sensing devices, the opportunity is to develop comprehensive models at urban scale leveraging sources such as Global Positioning System (GPS) data and Call Detail Records. This paper combines these big data sets in a novel method to model fuel consumption within a city and estimate how it may change in different scenarios. To do so a fuel consumption model was calibrated for use on any car fleet fuel economy distribution and applied in Riyadh, Saudi Arabia. The model proposed, based on speed profiles, was then used to test the effects on fuel consumption of reducing flow, both randomly and by targeting the most fuel-inefficient trips in the city. The estimates considerably improve baseline methods based on average speeds, showing the benefits of the information added by the GPS data fusion. The presented method can be adapted to also measure emissions. The results constitute a clear application of data analysis tools to help decision makers compare policies aimed at achieving economic and environmental goals.


2021 ◽  
Author(s):  
Samuel Langton ◽  
Jon Bannister ◽  
Mark Ellison ◽  
Salman Haleem ◽  
Karolina Krzemieniewska-Nandwani

Addressing public safety and welfare, inclusive of responding to incidents involving persons with mental ill-health (PMIH) has become an integral dimension of, and a significant challenge to, contemporary policing. Yet, little is known of the scale and severity of such PMIH-related policing demand, nor of the extent of frontline resource consumed in resolving such incidents. To address this shortfall, we deploy a bespoke text mining algorithm on police incident logs to estimate the proportion and severity of calls-for-service involving PMIH in a study of Greater Manchester, United Kingdom. Further, and using Global Positioning System (GPS) data, we then assess the amount of time spent by frontline officers responding to these calls. Findings suggest that existing police recording practices serve to significantly underestimate the scale and severity of PMIH-related demand. The amount of time spent dealing with PMIH-related incidents is both substantial and disproportionate relative to other forms of police demand.


Author(s):  
Pablo Cabrera-Álvarez

La encuesta es la técnica de investigación predominante en la investigación en Ciencias Sociales. Sin embargo, la aparición de otras fuentes de datos como las publicaciones en redes sociales o los datos generados por GPS suponen nuevas oportunidades para la investigación. En este escenario, algunas voces han defendido la idea de que, debido a su menor coste y la velocidad a la que se generan, los big data irán sustituyendo progresivamente a los datos de encuesta. Sin embargo, este optimismo contrasta con los problemas de calidad y accesibilidad que presentan los big data como la fata de cobertura de algunos grupos de la población o el acceso restringido a alguna de estas fuentes. Este artículo, a partir de una revisión profunda de la literatura de los últimos años, explora como la cooperación entre los big data y las encuestas resulta en mejoras significativas de la calidad de los datos y una reducción de los costes. Nowadays, while surveys still dominate the research landscape in social sciences, alternative data sources such as social media posts or GPS data open a whole range of opportunities for researchers. In this scenario, some voices advocate for a progressive substitution of survey data. They anticipate that big data, which is cheaper and faster than surveys, will be enough to answer relevant research questions. However, this optimism contrasts with all the quality and accessibility issues associated with big data such as the lack of coverage or data ownership and restricted accessibility.  The aim of this paper is to explore how, nowadays, the combination of big data and surveys results in significant improvements in data quality and survey costs.


Author(s):  
Zhong Zheng ◽  
Suhong Zhou

Scholars have explored urban structure from many perspectives. Developments in ICT have made it possible to discover spatial patterns in activities using big data. The identified patterns allow us to better understand urban structure. This chapter reports the collection of taxi GPS records for a single day in the inner city of Guangzhou, China. Taxi trips are connected to urban space by defining travel intensities. The spatial-temporal distribution of trips shows differences between three time periods (daytime, evening, before dawn). Different types of spatial facilities provide different activity places, the importance of which depends on their location and time of day. The study illustrates how descriptive analyses of taxi GPS data can enhance our understanding of urban space from the perspective of activities.


ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  

Find Out About 'Big Data' to Track Outcomes


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org


PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  

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