Digital Requirement Development: Three Years of Using Digital Methods to Improve Standardization of Procurement Specifications

Joint Industry Program 33 (JIP33) was established through IOGP with backing from the World Economic Forum to drive industry level standardization for procurement of equipment and packages. During Phases 1 and 2 of JIP33 the traditional business applications Microsoft Word, Microsoft Excel and e-mail were used to develop, collaborate and publish 14 specifications. For phase 3 a digital requirements management platform was implemented to enhance capacity, efficiency and auditability of specification development and maintenance. This platform has subsequently been used to develop and publish 27 ‘exception' style specifications and 4 ‘narrative' style specifications, bringing the JIP33 published specification library to 45 since the program's commencement in 2016. JIP33 proposed that the adoption of a digital requirements management platform would reduce the cost and time of development, simplify collaboration and improve the quality and maintainability of output. The platform's original configuration and work processes have evolved to enhance collaboration and improve traceability. Natural language processing technology has been integrated into the platform to support JIP33 writing protocols and reduce user dependence on external tools. Document production is automated using customised data transformations to output the specifications in a publishable form. Requirement Interchange Format (ReqIF) data exports are being piloted in collaboration with the IOGP Standards committee to test the digital transfer of JIP33 specifications into user databases. Changes to JIP33 work processes aimed at improving user engagement also provided resilience to the Covid pandemic and the sudden shift globally to virtual working. However, notwithstanding improvements in the tools and process, timely engagement of collaborators in content development and reviews remains a significant area for improvement. Resistance to ‘sentence centric' requirement writing should decline as familiarity and culture change programs take effect. Improvements to JIP33 data transformations are predicted to streamline extraction of publishable specification documents from the platform. Digital transfer of JIP33 specifications has also been piloted and advances in the standardisation of data attributes across the industry will drive the future evolution of the JIP33 program's use of these tools. This paper will present an update of the JIP33 program's sustained use of a requirement management platform and other digital tools for specification development and future digital integration of JIP33 specifications by users. © 2022, Offshore Technology Conference. All rights reserved.

Standardized Risk Mitigation Measurement in Extended Reality Environments Utilizing the IEEE Experience API (xAPI) Standard

Recent reports indicate increased organizational appetite and spend in the energy industry in both the areas of operational risk management training and enablement and in extended reality hardware and software, as part of larger automation and digital transformation initiatives. Furthermore, recent advances in immersive technology, along with more dispersed, asynchronous working conditions due to COVID, have resulted in scalable, immersive simulations that more and more closely resemble real world environments. While recent standards have defined JSON syntax appropriate for tracking and measuring human behavior data in generic learning environments (IEEE P9274.1) and in a manner that more closely approximates human behavior in the workplace, as typically tracked in operational risk management systems, no risk-based ontology has yet been defined that more closely crosswalks and correlates data from simulated environment systems to those in operational environments. Thus, the true efficacy of extended reality-based risk mitigation training cannot be fully measured. In this effort, a risk-based ontology and matrix was constructed in accordance with the xAPI standard syntax and allowable extensions and was utilized to transform a subset of historical data from simulated operational risk-based scenarios from the energy industry. Transformed data from this initial subset closely approximated operational risk reporting data and provided insights into human behavior data in simulated environments that can be easily compared and correlated to existing operational excellence and risk mitigation KPIs. Implications for mapping of additional advanced data from simulated environments in larger, more complex datasets, such as eye tracking and biometrics, were also considered and explored. © 2022 IEEE.

Data transformation in the Infectious Disease Surveillance System for the Public Health Information Management

This paper aims to solve the problem of large number of COVID-19 patients with paper form for COVID-19 investigation and to communicate between medical staffs and public health office center. We applied the agile model to design and develop data transformation in the infectious disease surveillance system to help a project to adapt to change requests quickly. This data transformations provide the public health emergency surveillance such as routine surveillance, COVID-19 surveillance, event-based surveillance and outbreak investigation. This approach can be useful to the Infectious disease situation. In additional, it can be provided greater contributions to manage public health data in term communicable diseases in the future. © 2022 IEEE.