Smart Data for Smart Enterprises: the value of linked-standards-data to enable both internal and external interoperability in our multi-energies'company
Présenté par : Jean-Charles Leclerc
Our information systems are siloed and based on heterogenous labels, which breaks real interoperability, automation or machine learning algorithms use.
We need to exchange information between humans and machines to inter-operate from multiple data domains sources, across various actors, tools, organization branches, internally with our sites and affiliates and externally with our multiple partners.
Following ISO15926 part14 principles, published by PCA this summer, associated with other standards of primary interests such ISO/IEC81346 eg, lessons learnt, and experiences acquired with AFNOR IDMI, IOGP DISC, JIP33 & JIP36 CFIHOS and others working groups, we started in January 2021 to implement a semantic framework to set-up a governance methodology, with rules, common principles, and guidance's to provide tools to sustainably structure our information legacy in a normalized way.
By bridging our data and documents texts to selected and combined standards classes, using W3C standards, respecting the same context, exclusively structured through ISO15926-14 properties to set the relationships between classes, we allow working as a continuum between conceptual, logical, and physical models using trustable labels that recovered their sense.
To govern this common framework, we developed a mapping strategy based on several steps to enforce and endorse progressively our company's reference ontology as a result of our mapping efforts to link our data to standards; this disambiguation or contextualization process loop is a way to formalize our verifiable requirements thru a generic specification enabling data exchange, in a way (or a model or a specification) which is not specific to TotalEnergies.
This approach is an intellectual and cultural breakthrough, beyond our current information management way of working; it implies a change of mindset, supports a progressive participation of the stakeholders for connecting our data and taxonomies to higher level conceptual common nodes. We believe this a one of the keys to debottleneck our fragmented information system.
To support adoption by our organizations, we shall focus attention on pedagogy while each Use Case's resolved mappings are sustainable, means qualified and re-used by third POC or business. Finally, we do believe that a common language across our disciplines and métiers is key, this standard language creates unambiguous understanding among all stakeholders internally and externally. This is a matter of education, federated and shared practices, and adapted tools to support the methodology. It provides user experience customized interfaces by a modular and flexible approach, and the development at scale of domains and UCs knowledge graphs to explore, navigate and use FAIR and safe data.
The relation of this journey in a corporate conducting its digital transition will be illustrated by concrete outcomes of this initiative and will give firsts lessons learnt up to now, as ground of further requirements.
 SMART: Specific, Measurable, Achievable, Realistic, and Timely
 IDMI: Ingénierie des Données et des Modèles pour l'Industrie
 DISC: Digital Information Standards Committee
 CFIHOS: Capital Facilities Hand Over Specification (IOGP JIP36)
 FAIR: Findable, Accessible, Interoperable, Reusable