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losses; predicting species distribution using a modellingtool; application of regional climate models in theprediction of surface temperature and precipitation; modelanalysis of non-CO 2 greenhouse gases; bio-dieselperformance and emissions; mobile health technology; andAfrican schistosomiasis control and drug research.7.5. Big data applications for sustainable developmentSo-called “big data” is another area in which scientists haveapplied new tools to provide information and analysis onaspects of sustainable development. Much of this emergingwork lies outside the official statistics systems and employsapproaches from the natural sciences to analyse social,economic and environmental questions. While chapter 8 ofthe present report provides a more in-depth account ofapplications of big data in the specific case of Africa, herewe provide a glimpse of the emerging broad picture of bigdata applications for sustainable development.“Big data” have been defined along divergent lines.According to one definition, big data are: high in volume,velocity, and variety; exhaustive in scope; fine-grained intemporal or spatial resolution, and inherently relational. 627Data might be user-generated (e.g. call records data,Twitter, Flickr), gathered by sensors (e.g., satellites, videos),or draw on data repositories made public by governmentsor corporations (e.g. real estate prices, subway records).Table 7-5 provides an overview of the wide range ofemerging big data applications and how they can supportthe whole range of SDGs at various geographical and timescales. At present, big data applications tend to be used insectors that are either correlated with big data productionof some kind, or that are currently monitored throughtraditional means. Some uses, such as for environmental orland-use monitoring through satellite data analysis havebecome commonplace. 634 Others like monitoring illegalfishing with satellites or literacy with cell phone recordshave just started.144“Big” may refer to gigabytes, terabytes or even topetabytes. 628 It is important to note that natural scientistshave long used these methods for production and analysisof scientific data. However, their diffusion into corporationsand the social sciences has attracted great attention by thewider public and earned the new label “big data”. Recentlybig data has been described as a complex ecosystem ofdata crumbs, capacity (tools and methods, the hardwareand software requirements) and community (producersand users of the data crumbs and capacities). 629The geographies of user-generated information are veryuneven between and within countries, and informationalpoverty has increased in some places. 630 In contrast, manydata gathered via sensors show a geographic coverage thatdoes not stop at national borders. For example, satellitedata is often global in scope - leaving no country “datapoor”, even though socio-economic, infrastructural, andeducational barriers to using these data remain.In the context of the SDGs, recent deliberations at the UNhave focussed on the question of whether big data couldcontribute to the monitoring of progress and theeffectiveness of policies, programmes andactivities. 631,632,633 They are envisaged to complementofficial statistics. This is in contrast to the monitoring ofMDGs which focussed exclusively on official statistics.A number of big data sources may be representative only ofparticular segments of society. 635 Data analysis methodsare being developed that aim to correct for sample bias andvarious types of data gaps, and to separate the sought-aftersignals from noise. For example, a Twitter-mining algorithmused to detect changes in food prices in Indonesiapredicted a food crisis where there was none. 636 In the2010 Haiti earthquake aftermath, social media dataproduction was only weakly (and inversely) correlated with637 638damage.Table 7-5. Big data applications in areas covered by the SDGs and in topics relevant for sustainable developmentSDGs What is measured? Data source Geographic scope of applicationSatellite images (night-lights) 639Global mapPovertyCell phone records 640Côte d’IvoirePoverty (SDG1)Price indexes 641 Online prices at retailers websites ArgentinaSocio-economic levels Cell phone records City in Latin America 642 ; UK 643Food price crises 644 Tweets IndonesiaHunger and foodsecurity (SDG2)Health (SDG3)Money spent on food 645,646 Cell phone data and airtime credit purchases A country in East-Central AfricaCrop productivity 647 Satellite images AfricaDroughtRemote sensingAustralia 648 ; Afghanistan, India, Pakistan 649 ;China 650Online searches US 651 ; China 652InfluenzaTwitter Japan 653 ; US 654Voluntary reporting through the internet 655,656 Belgium, Italy, Netherlands, Portugal, UnitedKingdom, United StatesMalaria 657 Cell-phone records KenyaPopulation movements658during an epidemicCell-phone records West Africa