The Digital Twins Working Group are divided into three sub teams addressing various items identified in the white paper. These sub-teams are focused on exploring these topics and generating content and thought-leadership pieces as a result of the work done.
Group 1: Standards for data models
Today, there are existing established standards for data models that are already in place. The current focus is on extending the scope and deploying established data models. These standards are essential, they allow the collection of data and creation of data models to operate at various levels of scale. What is required is a standardized way of creating interoperable systems data. The output should be secure, reliable, and efficient ways of sharing data at an industry-wide scale.
Group 2: Standards for data management and integration
Standardization in the realm of data management and integration aims to bring two related fields together: data science and information management. To map knowledge between these two fields, it is especially important to focus on semantic precision i.e. the data must be integrated on a common basis to retain its true meaning. Standards that allow the integration of data with a focus on semantic precision facilitate the creation of a robust, transparent, and sustainable system of data – a resilient ecosystem of digital twins.
Group 3: Data security and privacy
By providing a neutral forum for discussing relevant topics, bSI is relevant for parties who wish to work together and have the means and sense of duty to resolve open questions related to data security and privacy. Bridging gaps of knowledge and allowing data to flow effortlessly between projects, lifecycle phases, levels of scale, tools – this innovation will naturally lead to questions around the hosting of data, data ownership and privacy. As the enabler for the industry and ultimately as an enabler of enablers.