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data sources and there is an increasing awareness of theneed to share data more widely, though many data inAfrica remain difficult to access.Many data innovations in Africa are developed by researchinstitutes and have not yet been used in channelsinfluencing national policy-making. To empower Africancountries to produce quality frequent data with goodcoverage, upscaling data innovations is critical.Novel approaches to data can cover data gaps in areascovered by the SDGsFor several topics covered by the SDGs, there are new dataapproaches in Africa, using new technologies, new methodsand/or new data sources. The innovations discussed in thischapter and summarized in Figure 8-13 are relevant forpoverty, education, water resources, terrestrialecosystems, natural disasters, climate, and food security. Inother countries in the world, novel Big data applications arebeing used – covering gender education, economic growth,peace and security, etc. - which may also be applicable inAfrica (see table 7-5 on Big data in Chapter 7).There is an increasing tendency to make use of multipledata sources: official statistics, geographic and satellitedata, big data, scientific data, data produced by NGOs andresearch foundations, data from the media, from the crowdand from the business sector. To explore the full potentialof these data sources, the data needs to be easilyaccessible and standardised – so that users are able tointegrate difference sources and types of information.Data, and its metadata, needs to be open access (i.e. freeand accessible). Most big data is currently owned by banks,mobile phone internet providers, social media providers,etc. Legislation must be put in place to provide secureaccess for those who need it to implement effectivesustainable development policies [D Sanga].In addition, data from unconventional sources should beprovided together with confidence intervals or anotheruncertainty measure. As different innovative sources comeinto play, inclusion of uncertainty measures becomes evenmore important to compare the reliability of different datastreams and for integrating them. Statistical models canalso assist in exploring hidden information in raw data, inintegrating different data sources and in providinginformation in the form of probabilities and scenarios to beused in decision making. More research will be needed tocalculate uncertainty measures for unconventional datasources, identify techniques to correct for selection bias(e.g. data collected through mobile phones or online have apotential selection bias from the fact that generally certainsegments of the population are not well covered) and tointegrate different data sources.High mobile phone penetration in Africa offers newmonitoring opportunitiesVast parts of African societies have leap-frogged the age ofanalogue technology with the help of mobile phones. Thisgives a window of opportunity to monitoring sustainabledevelopment. Across the African continent, greater accessto mobile phones has spurred new innovations in datacollection and less so in cell phone data use. Access to theinternet is still a challenge due to low internet connectivity,and data collection using internet platforms and usage ofdata produced in the internet - like from social media,online searches, online transactions, etc. - is rare.The potential of big data depends on country context. InAfrica cell phone has penetrated much more than internet.In African countries having very high penetration rates, cellphone data may be more valuable because it covers alarger proportion of the population. In these countries, cellphone records can be explored to increase either theavailability or the frequency of data. For countries with lowcell phone penetration rates, the usefulness of cell phonedetailed records (CDR) is more limited.Most of the big-data applications, but not all, need to becalibrated against official/traditional data. Therefore,strengthening traditional data sources must remain apriority, particularly in Africa where these sources are poor.Not having functional “small data” systems can be anobstacle for using big data, as there is no small data tovalidate the big data.The increasing use of geospatial information needs tocontinueGeospatial information is increasingly being used in Africa,but more capacity building will be needed to scale upexisting initiatives and to bring innovative applications fromother parts of the world to Africa. While the lack ofconsistent up-to-date base mapping – fundamentalgeographic datasets such as geodetic control, elevation,drainage, transport, land cover, geographic names, landtenure, etc. – across Africa remains a challenge, individualcountries are making progress. Imagery derived fromspace-based earth observation platforms are already beingused in Africa for improved weather forecasting, land usemapping, producing GHG inventories, and for disaster riskmanagement. Satellite imagery has also been used toaddress health-environment interlinkages, such as forcontrolling water quality in lakes, and identifyingenvironmental conditions prone to malaria and meningitis166