Omid Kalatpour, Iraj Mohammadfam, Rostam Golmohammadi, Hasan Khotanlou / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 4, Jul-Aug 2013, pp. 96-103 96 | P a g e Technological Emergency Planning Through An Ontology Oriented Approach. Omid Kalatpour 1 , Iraj Mohammadfam 2* , Rostam Golmohammadi 3 , Hasan Khotanlou 4 1 Department of Industrial Hygiene, Hamadan Medical Science University, Hamadan, Iran 2* Departments of Industrial Hygiene, Hamadan Medical Science University, Hamadan, Iran (Corresponding Author) 3 Departments of Industrial Hygiene, Hamadan Medical Science University, Hamadan, Iran 4 Department of Computer Engineering Bu-Ali Sina University Abstract Having access to the right information before and during an industrial emergency could save organizations and keep them safe and sustainable. Accident databases among other are used to provide such accesses. But, usual accident databases are lacking to provide enough emergency knowledge. This paper tries to improve the current process accident databases information retrieval through developing a process accident knowledge base (PAKB). Technological accident concepts and subconcepts were identified. Then, the relevant taxonomy for each concept was developed and the relationships among all concepts were formalized. This collection was transferred into the protégé software for more formal interpretation and representations. The established PAKB could improve information retrieval processes, reduce query time and fault results. Despite customary databases, it can disclose the hidden relations among different stored data. The accident knowledge base imagines knowledge epresentation and concept relationships that could help to understand the hidden relations among the needed data. Such features are vital in the emergency management. Keywords: Databases, knowledge base, Emergency management, Process Accident, Emergency Plan I. Technological emergencies and Business Continuity Chemical process industries face many potential risks inherited in their entities. Such risks can lead to emergency situations that interrupt organization continuity, endanger their lives or even surrounding communities. Many organizations use emergency management systems to control threatening events in dangerous contexts. To keep business safe and uninterrupted, many organizations plan to prevent and control technological emergencies as a known business interrupting cause. Emergency plans employ various approaches and strategies to manage the threats. Regardless the selected approach, planning for managing technological emergency needs a thorough approach to the risks data collection, analysis, communication and distribution (Pasman, 2009). So, it is necessary to have enough domain knowledge to manage the technological emergencies. Any domain knowledge is manageable through knowledge management (KM) process (Ly, Rinderle, & Dadam, 2008). Knowledge management refers to a systemic and specific frame to capture, organize, communicate and disseminate domain knowledge (Kim, Zheng, & Gupta, 2011). Thus, the KM can form a sound basis for emergency management planning and its subsequent implementation. It could be declared that these days, organizations are becoming aware the KM could help them survive in the threatening contexts (Simone, Ackerman, & Wulf, 2012). KM provides mechanisms allowing the right knowledge to be at the right place, right people and the right time (Oztemel & Arslankaya, 2012). Then, having emergency domain knowledge could ease the emergency control and business continuity. Process accident databases are the most known information resources for the technological accidents (Tauseef, Abbasi, & Abbasi, 2011). They are common tools to record the emergency information and are designed to collect and represent data, manage the experiences, serve the KM process and retrieve the required information for emergencies prevention and control purposes. But, these resources do not provide comprehensive domain knowledge for process accidents. The variables in an accident database are vectors whose parts comprise script data or strings of bits (Palamara, Piglione, & Piccinini, 2011). Normally, an accident database represents an expandable keywords list and then finds the most related stored cases. Emergency situation information are not related linearly. Any data might be correlated with many other data. For example, the cause consequence relation, chemical and equipment involved in the emergencies, time of occurrence, human factor role and so on are interrelated together.