Research Article
Robust Decision Engineering: Collaborative Big Data and its Application to International Development/Aid
@INPROCEEDINGS{10.4108/icst.collaboratecom.2012.250715, author={Steve Chan and Wesley Rhodes and Charles Atencio and Caroline Kuo and Brent Ranalli and Anna Miao and Simone Sala and Stephen Serene and Robert Helbling and Sarah Rumbley and Marc Clement and Lisa Sokol and Loren Gary}, title={Robust Decision Engineering: Collaborative Big Data and its Application to International Development/Aid}, proceedings={International Workshop on Collaborative Big Data}, publisher={IEEE}, proceedings_a={C-BIG}, year={2012}, month={12}, keywords={decision engineering science robust decision engineering complexity ceiling selection bias compressed decision cycles gestaltian closure decision-making faster decisions better decisions intelligent decisions high adaptation cycles perfect storm crises smart power times velocity volume and vectors of big data collaborative big data bigger data provenanced/pedigreed data big compute layered analytics content analytics entity resolution predictive analytics complexity theory social complexity science high performance computing computational intelligence sparse data sparse networks social influence network participatory revolution network science relationship science relationship manager 3d 5d big insights common operating picture aegis system unintended consequences condition-creating cyber-physical supply chain karassian netchain analysis local community structures network shapes memes motifs fifth column dualistic actors insider threats sentiment analysis flash mobs islands of stability sandpile effect cascading failure positive influence dominating sets civil society democratic governance science of development brittleness annealed resiliency latent stability}, doi={10.4108/icst.collaboratecom.2012.250715} }- Steve Chan
Wesley Rhodes
Charles Atencio
Caroline Kuo
Brent Ranalli
Anna Miao
Simone Sala
Stephen Serene
Robert Helbling
Sarah Rumbley
Marc Clement
Lisa Sokol
Loren Gary
Year: 2012
Robust Decision Engineering: Collaborative Big Data and its Application to International Development/Aid
C-BIG
ICST
DOI: 10.4108/icst.collaboratecom.2012.250715
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.
