TY - GEN
T1 - A Methodological Approach Towards Crisis Simulations
T2 - 9th International Conference on Computational Collective Intelligence, ICCCI 2017
AU - Diakou, Chrysostomi Maria
AU - Kokkinaki, Angelika I.
AU - Kleanthous, Styliani
PY - 2017
Y1 - 2017
N2 - Low probability high impact events (LoPHIEs) disrupt organizations’ processes severely. Existing methods used for the anticipation and management of such events, suffer from common limitations resulting in a huge impact to the quantification of probability, uncertainty and risk. Continues studies in the field of Crisis Informatics, present an opportunity for the development of a framework that fits the uncertainty related properties of LoPHIEs. The paper identifies the need for the development and conduction of a series of experiments, aiming to address the factors that qualify Collective Intelligence-enabled Information Systems with respect to their applicability towards support for LoPHIEs; and aims to propose an experiment framework as a methodology for scenario design in LoPHIEs settings.
AB - Low probability high impact events (LoPHIEs) disrupt organizations’ processes severely. Existing methods used for the anticipation and management of such events, suffer from common limitations resulting in a huge impact to the quantification of probability, uncertainty and risk. Continues studies in the field of Crisis Informatics, present an opportunity for the development of a framework that fits the uncertainty related properties of LoPHIEs. The paper identifies the need for the development and conduction of a series of experiments, aiming to address the factors that qualify Collective Intelligence-enabled Information Systems with respect to their applicability towards support for LoPHIEs; and aims to propose an experiment framework as a methodology for scenario design in LoPHIEs settings.
KW - Collective Intelligence
KW - Emergencies
KW - High impact
KW - Low probability
UR - http://www.scopus.com/inward/record.url?scp=85030832480&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-67074-4_55
DO - 10.1007/978-3-319-67074-4_55
M3 - Conference contribution
AN - SCOPUS:85030832480
SN - 9783319670737
VL - 10448 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 569
EP - 578
BT - Computational Collective Intelligence - 9th International Conference, ICCCI 2017, Proceedings
PB - Springer Verlag
Y2 - 27 September 2017 through 29 September 2017
ER -