Crystal Clear: Investigating Databases for Research, the Case of Drone Strikes

Giampiero Giacomello,Damiano Martinelli

doi:10.3390/data6120124

Abstract

The availability of numerous online databases offers new and tremendous opportunities for social science research. Furthermore, databases based on news reports often allow scholars to investigate issues otherwise hard to tackle, such as, for example, the impact and consequences of drone strikes. Crucial to the campaign against terrorism, official data on drone strikes are classified, but news reports permit a certain degree of independent scrutiny. The quality of such research may be improved if scholars can rely on two (or more) databases independently reporting on the same issue (a solution akin to ‘data triangulation’). Given these conditions, such databases should be as reliable and valid as possible. This paper aimed to discuss the ‘validity and reliability’ of two such databases, as well as open up a debate on the evaluation of the quality, reliability and validity of research data on ‘problematic’ topics that have recently become more accessible thanks to online sources.

Highlights

In the last 20 years, scholarly research has benefited tremendously from the deluge of information available on the World Wide Web and other digital outlets
Using different sources of data collected for diverse purposes to find creative solutions to problems is one of the linchpins for Big Data (BD) analytical methods [1,2]
In the case of the TBIJ Pakistan and Yemen datasets, the total results, the militants’ data, the civilians’ data, the unknowns’ data and the link to we kept the columns related to the ‘Area’ and ‘Province’ of the strike

Summary

Introduction

In the last 20 years, scholarly research has benefited tremendously from the deluge of information available on the World Wide Web and other digital outlets. Greater care and scrutiny are necessary to ensure that data and sources used to investigate social phenomena are valid, reliable and trustworthy. Much as the orienteering method, the idea is to discover the “location” of a third point, by using two known relative positions, or, in this case, by comparing two different, independent sources of information on the same issues and seeing if their findings coincide, namely that they “say the same thing”. Correlation coefficients, with all the necessary due attention, may give the researcher an actual measure of “how much” the two independent sources overlap, increasing confidence about their reliability. Using different sources of data collected for diverse purposes to find creative solutions to problems is one of the linchpins for Big Data (BD) analytical methods [1,2]

Objectives

Methods

Results

Conclusion