The new way of working implies new roles and requires new competencies. The following roles are relevant to discuss:
- The Subject Matter Expert (SME). SMEs are experts on discipline engineering. For example, a process engineer who develops the design of the main processing system, or an electrical engineer who develops the design of the electrical supply and distribution.
- The System Engineer is an expert on system integration. For example, a System Engineer is responsible for coherent integration of system designs from, e.g., different disciplines, different phases of the project lifecycle and different parties in the value chain.
- The Data Engineer is an expert on the flow of data between IT systems and applications. For example, a Data Engineer manages the export of data from a model authoring application into an engineering register system.
- The Knowledge Engineer is an expert on semantic technology. For example, a Knowledge Engineer manages the validation and integrity verification of the model of a design.
Engineering and design is a process of making a series of decisions founded on subject matter expertise and governed by requirements and limitations. This is the domain of SMEs and System Engineers, but the new way of working allows a significant shift in focus away from formatting of information, and towards creating information. It is less constrained by document formats and instead allows a much more flexible and incremental way of creating a design. This will have an impact on how the work is optimally allocated into different roles.
The SME role is by definition holding expertise on a defined subject, usually a single discipline, but the new way of working will reward an approach of also working across disciplines that are interlinked and interdependent, thus reducing time-consuming coordination effort. As systems thinking is a fundamental part, the System Engineer role may have a stronger impact, in particular when integrating segments of models into a whole, and when managing how systems interact.
While conventionally the Data Engineer has had more focus on batch transfer of data between systems, this role will need to strengthen the focus on publishing and sharing of model data, and on leveraging semantic technologies. A significant value of modelling is that it allows use of advanced semantic technologies and mechanisms for machine-based validation and verification. The role of the Knowledge Engineer is instrumental for achieving this.
Figure 10 illustrates how the different roles work together to enable modelling of parts of the Facility Asset that then are integrated into a complete model where semantic technology is utilized to verify and validate the integrity of the model.
The SME is modelling information that today is available only in fragments, as documents ❶.
The documents may refer to standards, possibly exploiting reference data, such as names of shared properties and classes, and initiatives to digitally enrich documentation format such as DEXPI (2)❷. When modelling, the SME creates the building blocks of the model from definitions held in a common industry library, a Reference Data Library ❸, enabling the re-use of well-proven design patterns (e.g., type of pump configuration). The building blocks are put together into a model in accordance with the IMF rules and structures that build on the IEC/ISO81346 O&G standard  ❹.
IMF does not require all to work on one, single model, something which often is implied when referring to data-centric or model-centric ways of working. Instead, the modelling can be done as many smaller IMF Models, here shown as puzzle pieces, that the System Engineer later can bring together as a complete puzzle ❺. IMF Models can be translated ❻ to enable the Knowledge Engineers to exploit verification techniques such as automated reasoning ❼.