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Citizens and developers are gaining full access to public data sources through open data portals (ODPs). These datasets allow the creation of applications for helping citizens in different ways, allowing them to actively participate in government processes such as decision-making and policymaking. However, researchers have identified several drawbacks regarding the data they provide. One of the recurring problems cited in literature is related to the metadata associated with each dataset, which may lead to inadequate descriptions or classifications of datasets, affecting open data usability. As completeness is an important metadata quality metric, in this work, the authors propose an approach based on the alignment of metadata schemes to assess the degree of metadata completeness associated to datasets available in ODPs. To evaluate the proposed approach, they conducted two case studies, leading them to observe that the larger the number of metadata schemes, the lower the completeness of the datasets, although not linear.

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Human exposure is a relevant factor when operating in critical environments and depends on a thorough analysis and consideration towards driving the teams to a safer and more productive environment. Reducing such exposure through digital technologies benefits the whole workforce in their decisions and maneuvers, like simulations, training, and other critical activities that can be executed remotely and prior to the actual activity. This paper presents a case study to demonstrate how augmented and virtual reality can be used to create a high fidelity virtual environment emulating the real industrial facility. This approach enriches the Digital Twin with the association of data and the virtual environment. It leverages on display and interaction capabilities of hardware devices, and intelligence and data querying capabilities of industrial software, empowering the workers with enhanced training capabilities and access to information increasing safety and efficiency. A real application of this technology is presented in this paper through the case study of the PredictMain4.0 project of Repsol Sinopec Brazil (RSB), which aimed at the integration of digital technologies, including augmented reality (AR) and virtual reality (VR). The PredictMain4.0 project was executed using data and data models of PETROBRAS’ P-50, a FPSO (Floating Production Storage and Offloading) operating in Brazil, and illustrates how different AR/VR applications can be developed and used in combination with engineering, operation, and maintenance databases. This includes 3D models, digitalized critical procedures, and the ability to integrate field teams into a single virtual environment, allowing real interaction in a digital setting that is linked to the real world. Considering the digitalized procedures, this paper aims to establish how virtual simulation and training can make teams more confident and prepared to execute the same physical asset procedures. After consulting with stakeholders from many different teams, the PredictMain4.0 project team selected three critical operating modules in the FPSO (Power Generation, Water Injection, and Gas Compression). For each one, considered which situations were relevant, should they occur. These situations led to developing a training and simulation framework, allowing instructors to create different scenarios and use advanced features such as digital measurement, real-time data collection, and collaborative sessions. The case study indicates that the development of such applications can save more than $1 million per year in maintenance costs considering the decrease in downtime and avoiding risks of accident.