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Resilience is presented in literature as the capacity of a system to disarm, adapt and recover from unexpected events. Despite the increase of interest of industries and academia in the subject, there are a lack of models that describes the elements that condition and determines resilient performance. This article presents a knowledge model that characterizes intangibles which determine resilient responses and is a central piece in a data science strategy supporting monitoring and analysis of potential for resilience in high-risk industries. Through an interdisciplinary approach, this model was established using an integrative review of the literature and the contribution of experts from several areas. The potential for resilience is represented by a set of leading indicators that allows continuous monitoring of both static characteristics of complex operations and dynamic resource mobilization in the face of unexpected events. Knowledge engineering and data science techniques are applied to treat data from various sources. The established approach addresses several elements that are not traditionally explored in safety management systems, including those related to knowledge that determine resilient responses, as well as factors related to human, structural and relational capital that condition resilient performance. Results of the application of the model are presented, including how the analytical model supports the definition of knowledge management and safety investment strategies in oil and gas companies in Brazil. The approach supports the prioritization of actions and investments to promote safety and enable strategies to learn from accidents and positive conditions that make operations safer despite unpredictability in daily operational routine.

Human Factors is a broad area of interdisciplinary and transdisciplinary studies and research focused on the perspective of the interaction between organizational, group and individual factors that aims at improving the performance and safety of people in complex organizations and socio-technical environments.  Knowledge to develop solutions to the complex problems that arise in this context can be co-produced by academic and non-academic actors through a transdisciplinary research framework that integrates the daily practices of stakeholders and creates structures that make co-production spaces effective for corporate’s practices. This paper present and discuss the strategies and challenges for developing spaces for human factors-based knowledge co-production on a transdisciplinary research project during the pandemic period of COVID-19. This ongoing research was designed to develop interactions and to co-produce knowledge aimed at the safety culture of companies in the oil and gas sector. Under the imposition of social distance and its consequent challenges, strategies to promote interaction, iteration, sharing, integration, co-creation, and co-production of knowledge had to be redesigned. Based on partial results, the research discusses and analyze the main dilemmas for the knowledge coproduction focusing on the 30 researchers, and on the knowledge coproduction between researchers and stakeholders. Although the COVID-19 pandemic had imposed new forms of relationships, the main challenges remained on the integration of knowledge as perceived by the research team. This paper presents the confrontation of the knowledge co-production challenges imposed by the new context associated with addressing two new constructs for the oil and gas industry, human factors and resilience, to improve safety culture. The discussion suggests and presents possibilities to overcome these challenges to continuous stimulate co-production of knowledge in these organizational environments.