It’s been almost two months since ICTD. For some reason, this summary which had been written immediately after we concluded our session on SRs, had not been posted. There is a degree of discomfort among some academics about systematic reviews (SRs). Researchers worry about the limited resources available from funders being channeled to SRs and quantitative research, at the expense of alternative methods. We believe that the debate will be more productive if people fully understand the subject under discussion.
Companies are increasingly relying on business analytics to extract value from the large volumes of computer-readable and analyzable (or “datafied”) data in their possession. Big data for development (BD4D) seeks to apply these techniques to big data held by both government and private entities to answer development-related questions. Given low levels of “datafication” of transactions and records in developing countries, analysis of credit-card use or even social-media use is unlikely to yield coverage approaching n=all as in developed countries. Mobile transaction-generated data (including Call Detail Records or CDRs) are an exception. Because they can yield information on movement of people, they have great potential to inform a host of policy domains: urban and transportation planning, health policy by enabling the modeling of the spread of infectious diseases, socio-economic monitoring, etc.
Hernan Galperin from DIRSI had organized a session entitled Data for development: the good, the bad and the ugly. Martin Hilbert was originally featured as the star speaker who would tell the audience about the wonders of big data. Well, he did not turn up. So it was left to LIRNEasia, where we actually get our hands dirty analyzing big data of relevance to our primary clients, the poor of the developing world, to talk about big data. The slides are here.