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Labelling relevant events to support the crisis management operator
Author(s) -
Zoppi Tommaso,
Ceccarelli Andrea,
Lo Piccolo Francesco,
Lollini Paolo,
Giunta Gabriele,
Morreale Vito,
Bondavalli Andrea
Publication year - 2018
Publication title -
journal of software: evolution and process
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 29
eISSN - 2047-7481
pISSN - 2047-7473
DOI - 10.1002/smr.1874
Subject(s) - situation awareness , computer science , correctness , operator (biology) , crisis management , situational ethics , relevance (law) , process (computing) , risk analysis (engineering) , computer security , data science , the internet , process management , data mining , business , world wide web , engineering , psychology , political science , biochemistry , chemistry , repressor , transcription factor , law , gene , aerospace engineering , operating system , social psychology , programming language
Thanks to the large availability of portable devices and the growing interest in the Internet of Things, during crises, social networks, or alerts sent through mobile devices or sensor networks are available and can be matched each other to perform situational analysis. However, the inclusion of multiple heterogeneous sources in situational analyses leads to 2 main issues: (1) a source could deliver (voluntarily or erroneously) wrong data damaging the integrity and the correctness of the analysis, and (2) a significant amount of heterogeneous data need to be processed. As a consequence, the crisis management operator faces a large amount of potentially unreliable data. In this paper, we present a relevance labelling strategy to process information gathered from heterogeneous data streams to select the most relevant events. These are presented to the crisis management operator with the highest priority. Our strategy is evaluated using events collected by the Secure! crisis management system, considering 3 real crisis scenarios happened in Italy in 2015. Results show that our strategy is able to correctly identify sets of relevant events, supporting the activities of the crisis management operator.