In the name of Development: Power,profit and the datafication of the global South

We examine the current ‘datafication’ process underway in low- and middle-income countries (LMICs), and the power shifts it is creating in the field of international development. The use of new communications and database technologies in LMICs is generating ‘big data’ (for example from the use of mobile phones, mobile-based financial services and the internet) which is collected and processed by corporations. When shared, these data are also becoming a potentially valuable resource for development research and policy. With these new sources of data, new power structures are emerging within the field of development. We identify two trends in particular, illustrating them with examples: first, the empowerment of public–private partnerships around datafication in LMICs and the consequently growing agency of corporations as development actors. Second, the way commercially generated big data is becoming the foundation for country-level ‘data doubles’, i.e. digital representations of social phenomena and/or territories that are created in parallel with, and sometimes in lieu of, national data and statistics. We explore the resulting shift from legibility (Scott, 1998) to visibility, and the implications of seeing development interventions as a byproduct of larger-scale processes of informational capitalism.     

一张相图引发的奇迹——论活动论构造—古地理

构造-古地理在地学基础研究与能源矿产勘查中具有重要的指导意义,国内外学者与勘探家进行了长期卓有成效的探索。本文以四川盆地东北部二叠、三叠系礁滩天然气勘探为例,探讨了沉积相图在油气勘探发现中的重要作用,以及活动论思想在相图编制中的指导意义。结果表明,40余年对四川盆地晚二叠世-早三叠世沉积相的研究,引发了长兴组生物礁、飞仙关组鲕滩天然气勘探的突破与普光、龙岗、元坝等大气田的持续发现,相图的创新与发展带来了油气田大发现的奇迹;将盆地与周缘造山带相结合,探索晚二叠世-早三叠世的原型盆地,表明四川盆地内部及周缘在该时期内构造-古地理环境发生了巨大变迁,台地边缘是礁、滩发育的有利场所,台地内凹陷则是烃源岩分布的有利地区;对沉积盆地的复位与复原有助于矿产资源的预测。新一轮活动论"构造-古地理"研究将基于海量地质调查与油、气、煤勘探等资料,大数据时代下的活动论古地理重建必将带来地学的进步与资源勘查的系列发现。     

Digital Earth: a new challenge and new vision

ABSTRACT

Digital Earth has seen great progress during the last 19 years. When it entered into the era of big data, Digital Earth developed into a new stage, namely one characterized by ‘Big Earth Data’, confronting new challenges and opportunities. In this paper we give an overview of the development of Digital Earth by summarizing research achievements and marking the milestones of Digital Earth’s development. Then, the opportunities and challenges that Big Earth Data faces are discussed. As a data-intensive scientific research approach, Big Earth Data provides a new vision and methodology to Earth sciences, and the paper identifies the advantages of Big Earth Data to scientific research, especially in knowledge discovery and global change research. We believe that Big Earth Data will advance and promote the development of Digital Earth.     

A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data

ABSTRACT

Pushed by the Internet of Things (IoT) paradigm modern sensor networks monitor a wide range of phenomena, in areas such as environmental monitoring, health care, industrial processes, and smart cities. These networks provide a continuous pulse of the almost infinite activities that are happening in the physical space and are thus, key enablers for a Digital Earth Nervous System. Nevertheless, the rapid processing of these sensor data streams still continues to challenge traditional data-handling solutions and new approaches are being requested. We propose a generic answer to this challenge, which has the potential to support any form of distributed real-time analysis. This neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve interoperability. As a proof of concept, we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental monitoring. The developed system is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user.     

工程地质数据处理方法探讨以水利枢纽工程为例

以水利枢纽工程为例,通过分析工程地质的工作内容、工作流程和数据(信息)分析与处理流程,认为工程地质数据是一种典型的大数据。可以通过地质语义及数据库技术提高数据的有序性和共享性,通过地质语法、模式、CAD技术和三维可视化技术,提高二维地质制图的效率与规范化,提高工程区地上、地下地质结构的直观性与地质分析的洞察力; 通过多传感器数据的融合与挖掘技术,提高地质监测分析与应用的深度与广度; 通过网络技术提高协同工作的效率和数据共享的方便性; 通过双C模式对工程地质数据及各种分析进行简洁有序的集成,从而对传统工程地质数据从采集到归档管理这一传统主流程进行信息化改造,达到促进行业信息化、数字化的目的。     

大数据时代城市地质信息的集群与产业化发展

以城市地质调查成果为依托,深化城市地质信息的集群化与产业化,是顺应大数据时代发展的必然要求。阐述了大数据的基本特征、城市地质信息集群化与产业化的工作准则与技术途径;结合上海地区实践,探讨城市地质信息集群化与产业化的社会应用及服务领域开拓。     

等离子天体物理学与现代等离子体宇宙观

现代科学表明宇宙中99%以上的可观测物质都处于等离子体状态,从小尺度的微观粒子动力学集体过程与能量转换机制到大尺度的宇宙等离子天体结构状态与爆发活动现象,都是等离子天体物理学的研究课题.从宇宙演化历史、大尺度结构形成以及爆发活动现象等方面,系统地论述了等离子天体物理学在现代天文学发展以及现代等离子体宇宙观形成中的重要作用.同时,结合空间卫星科学探测研究及其对现代天文学的巨大影响,进一步阐述了地球磁层和日球层等空间等离子体实地探测研究在等离子天体物理学研究中所扮演的“天然实验室”的独特作用.     

Bayesian analysis of zero inflated spatiotemporal HIV/TB child mortality data through the INLA and SPDE approaches: Applied to data observed between 1992 and 2010 in rural North East South Africa

Longitudinal mortality data with few deaths usually have problems of zero-inflation. This paper presents and applies two Bayesian models which cater for zero-inflation, spatial and temporal random effects. To reduce the computational burden experienced when a large number of geo-locations are treated as a Gaussian field (GF) we transformed the field to a Gaussian Markov Random Fields (GMRF) by triangulation. We then modelled the spatial random effects using the Stochastic Partial Differential Equations (SPDEs). Inference was done using a computationally efficient alternative to Markov chain Monte Carlo (MCMC) called Integrated Nested Laplace Approximation (INLA) suited for GMRF. The models were applied to data from 71,057 children aged 0 to under 10 years from rural north-east South Africa living in 15,703 households over the years 1992–2010. We found protective effects on HIV/TB mortality due to greater birth weight, older age and more antenatal clinic visits during pregnancy (adjusted RR (95% CI)): 0.73(0.53;0.99), 0.18(0.14;0.22) and 0.96(0.94;0.97) respectively. Therefore childhood HIV/TB mortality could be reduced if mothers are better catered for during pregnancy as this can reduce mother-to-child transmissions and contribute to improved birth weights. The INLA and SPDE approaches are computationally good alternatives in modelling large multilevel spatiotemporal GMRF data structures.     

大数据:概念、技术及应用研究综述

随着物联网、云计算、移动互联网的迅猛发展,大数据(Big Data)吸引了越来越多的关注,正成为信息社会的重要财富,同时也给数据的处理与管理带来了巨大挑战.首先从大数据概念入手,阐述了大数据的来源、主要挑战、关键技术、大数据处理工具和应用实例等,并对比了大数据与云计算、物联网、移动互联网等技术之间关系,然后剖析了大数据核心技术、大数据企业解决方案,讨论了目前大数据应用实例,最后归纳总结了大数据发展趋势.旨在为了解大数据当前发展状况、关键技术以及科学地进行大数据分析与处理提供参考.     

基于GIS技术的重大危险源信息监控系统

对重大危险源信息监控系统建设中的数据库设计和相关功能的实现技术进行了详细探讨,并对系统在功能实现上的作用进行了介绍。