Robust Decision Engineering: Collaborative Big Data and its application to international development/aid

Abstract

Much of the research that goes into Big Data, and specifically on Collaborative Big Data, is focused upon questions, such as: • how to get more of it? (e.g., participatory mechanisms, social media, geo-coded data from personal electronic devices) and • how to handle it? (e.g., how to ingest, sort, store, and link up disparate data sets). A question that receives far less attention is that of Collaborative analysis of Big Data; how can a multi-disciplinary layered analysis of Big Data be used to support robust decisions, especially in a collaborative setting, and especially under time pressure? The robust Decision Engineering required can be achieved by employing an approach related to Network Science, that we call Relationship Science. In Relationship Science, our methodological framework, karassian netchain analysis (KNA), is utilized to ascertain islands of stability or positive influence dominating sets (PIDS), so that a form of annealed resiliency or latent stability is achieved, thereby mitigating against unintended consequences, elements of instability, and 'perfect storm' crises lurking within the network. © 2012 ICST.