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content of the model to provide flow and check consistency.
This interactive tool must be supplemented with tools that allow data to be entered into the DDB in bulk, using tabular data. OTTR provides some of this functionality, but this needs to be lifted up into interactive tools. Mappings need to be developed towards common process simulators and engineering design databases. We need to both read design variables from the DDB and write calculated results back to the DDB. Here we need to work together with the industry so that our models and vendor’s models converge over time to an actual or de-facto standard. We are cautiously optimistic about the possibilities of this being successful. We see that many influential vendors are interested in exposing their data using semantic schemas and open formats.
We should aim for work practices where a DDB harvests data from engineering tools without intervention from the engineer. The proof-of-concept has also helped us to
develop a more systematic approach to defining the digital design basis. Time and organizational constraints meant that this first effort was more inductive than deductive. The modelling was driven by the data we had to represent, and we then drew systematic conclusions from the solutions developed.
The lessons from this project have been taken up in further, ambitious initiatives by each of the partners. We are contri- buting to the revisions of READI IMF and RDS for Oil & Gas. This work aims to address the tooling challenges above in the context of several on-going field development projects. It is also developing a formal systematization of modelling and use of data in engineering projects. The results of this work have also been taken into the development of the forthcoming Part 14 of the ISO15926 standard. We hope that these initiatives together will provide elements for establishing a practical, scalable framework for sharing information in the process engineering sector.
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