ORONER: An Ontology for Representing interOrganizational Networks Resilience. A building block towards adaptive network reconfiguration[ORONER : Une ontologie pour représenter la résilience des réseaux interorganisationnels. Une brique fondatrice vers la reconfiguration adaptative des réseaux]

Organizations are regularly affected by crises (e.g., pandemics, financial crises, natural disasters) to which they must respond appropriately in order to maintain their functioning and prevent decline and failure. A possible direction to achieve this is to develop their resilience in order to mitigate, anticipate, respond to and recover from adversity through the creation of interorganizational networks. This article aims to contribute to the understanding and modeling of how a network of interdependent organizations can collectively develop their resilience and how to infer the possible resource sharing between them. This study is undertaken through a strong coupling between social sciences (organization studies) and computer sciences (knowledge representation). We propose an ontological model, named ORONER, which is able to represent such organizational networks configurations with two future objectives: (1) analyzing the resources distribution within a network over a crisis period, and (2) reorganizing it to develop collective resilience. This domain ontology is based on the consideration of knowledge about organizations: the missions, interactions, crisis management, spatial-temporal entities as well as human and material resources necessary to operate organizations. Concepts are formalized using description logic and a set of rules is defined to infer some possible resource sharing. The evaluation of ORONER is performed through a case study and a list of competency questions, which exhibit initial and inferred interactions between organizations (e.g., municipalities, hospitals and schools) during the COVID-19 crisis.