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Trust and efficiency based on proven methodologies

DNV´s digital recommended practices provide guidance for organizations and industries on all stages of the digitalization journey. They are guidelines and best practices for procurement, development, and operation of AI and other digital solutions. 

Our recommended practices have been established based on decades of experience, research, and expert knowledge. They are developed in close cooperation with the industry and validated through a global hearing process prior to publication.

Get free access to the AI-enabled systems assurance (DNV-RP-0671) document in its entirety, with our Rules and Standards Explorer subscription. You can also access previews of other RPs via this subscription, or you can trial the Rules and Standards Explorer+ subscription for 14 days.

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Get access to our full catalogue of RPs, including all the RPs mentioned below, with our Rules and Standards Explorer+ subscription. 

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Existing Rules and Standards Explorer+ customers can get direct access to the documents here.

AI-enabled systems assurance (DNV-RP-0671)

This recommended practice describes a framework for assuring AI-enabled systems. It provides guidance on how to assure that AI-enabled systems are trustworthy and managed responsibly throughout their entire life cycle.

The recommended practice is part of the UK Centre of Data Ethics and Innovation portfolio of AI assurance techniques supporting the development of trustworthy AI. 

Digital twin assurance (DNV-RP-A204)

This recommended practice provides guidance on how to develop and assure a digital twin. The RP describes how to develop a trustworthy digital twin that provides business value through defining both work processes and technical requirements based on the criticality of the application.

Cyber security assurance

DNV combines specialist knowledge of your industry with deep engineering expertise and security best practice to secure your projects and operations, which includes publishing a range of standards and recommended practices supporting cyber security in the energy sector and maritime. DNV has four recommended practices dedicated to cyber security, including one tailored for oil and gas and one for electricity infrastructure and distribution.

Data quality assurance (DNV-RP-0497)

This recommended practice provides a systematic approach and framework for the assessment of data quality management. The assessment methodology is valuable input for organizations on how to establish best practices for achieving satisfactory data quality and considers both data quality and management capabilities.

Simulation models assurance (DNV-RP-0513)

This recommended practice defines and introduces assurance activities to establish trust in simulation models. That is needed as a fundamental prerequisite to ensure safety and establish trust in digital assets where simulation models are applied.

Machine learning applications (DNV-RP-0665)

This recommended practice delineates a set of assurance activities and requirements vital for instilling trust in machine learning applications. This ensures that these applications are not only aligned with their intended purposes but also operate within acceptable risk.

Sensor systems assurance (DNV-RP-0317) 

This recommended practice describes a methodology to assess or assure that a data collection and transmission infrastructure ensures good sensor data quality with an acceptable risk of use.

Data driven applications (DNV-RP-0510)

This recommended pracice will be updated in the beginning of 2024 and will outline assurance activities and requirements to establish trust in data-driven applications, particularly those incorporating classical AI.  This comprehensive guideline is designed to be universally applicable across a wide spectrum of data-driven applications.

Asset information modelling framework (DNV-RP-0670)

DNV is developing a new recommended practice which allows for the creation of a formal description of a digital asset using common industry Reference Data Libraries (RDL) and standards. It provides guidelines for structuring a machine-readable asset information model as a basis for data-centric and scalable implementations throughout the lifecycle of the energy sector. The recommended practice will be launched early in 2024.

Register your interest in receiving our upcoming RP on Asset Information Modelling Framework (DNV-RP-0670).

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