The Open Subsurface Data Universe (OSDU) promises a single, open, vendor-neutral home for subsurface and well data — but turning that promise into a working reality inside an operating company is a journey, not a switch you flip. In this presentation, Aker BP shares an honest account of our OSDU adoption so far: the wins worth celebrating, the obstacles we hit, and the work still ahead of us.

We will walk you through where we are today — what we have deployed, which data domains we have onboarded, and how OSDU is starting to change the way our teams find, trust, and use data. We will be open about where we struggled: the effort of data ingestion and mapping, aligning legacy systems and ways of working with OSDU's data model, governance and ownership questions, and the organizational change that technology alone cannot solve.

Looking forward, we will share what is on our roadmap — the capabilities, data types, and use cases we are prioritizing next — and what it will take to get there. Beyond our own four walls, we will reflect on our collaboration with other companies in the OSDU Forum: what works well in working together on a shared platform, what we have learned from others, and where we would like to see the community and the standard improve.

High-quality data products rarely start in the data platform, they start in the operational systems where data is created. Many modern platforms struggle not because of technology, but because of weak upstream data modeling and the lack of of metadata.

Data models and metadata together form the foundation. Models give data its structure and meaning. Metadata gives it context — legal basis, security, quality, ownership, and the full range of properties needed to govern data responsibly. Modeling has its own discipline, but the broader work of metadata across data quality, legal, security, and ethics requires organization through an operational model. "At the Norwegian Tax Administration, we complement the modeling foundation with an operational governance model: data leaders (stewards), legal expertise, and analytical capability are placed close to the domains and their data products, supported by structured collaboration around domain knowledge.

Together, the foundation and the organization turn upstream investment into downstream reuse, automation, and interoperable data products that consumers can actually understand and use.

Key takeaways:

- Information models and metadata together form the foundation for interoperable, well-governed data products

- Modeling discipline gives structure and meaning — semantics are more stable than technology

- Operational governance models matter — data leaders, embedded expertise, and collaboration around domain knowledge

The next competitive advantage in the energy industry will increasingly depend on companies’ ability to collaborate through shared digital infrastructure, common standards and governed data exchange. CoOper8 was established by the industry to provide the digital backbone for this collaboration, delivering shared services that enable trusted information exchange, interoperable workflows and more efficient use of resources across company boundaries.

Drawing on practical examples from equipment information, virtual inventory and project planning, this presentation explores how CoOper8’s industry-wide services are reducing manual work, improving data quality and strengthening operational resilience on the Norwegian Continental Shelf.

Åshild Hanne Larsen is seconded from Equinor into the role as CEO of CoOper8 AS. She is an award-winning technology executive with broad experience as global CIO, VP HR and VP Subsurface Excellence & Digital. She has successfully led corporate-wide IT & digital transformation programs and large-scale organizational change projects, resulting in extensive leadership experience. Åshild holds several board roles and is also widely recognized as a speaker, thought leader and advocate for diversity and inclusion in tech. She holds an MBA from Heriot-Watt University and an MA from Universität Bielefeld.

It wasn’t too long ago when we were working with, or better said: constrained by the adage of: Garbage in, Garbage out. Recently I came across that again, but now in the context of modern day AI: “with all the AI, we still deal with Garbage In: Garbage Out”

We live in an age where economies become circular and a world player like Renewi uses the “Waste No More” in their company strap-line. And with modern AI, that is true for data as well.

In this talk we’ll talk about how, with these days of AI, Data Management has fundamentally changed. How we can actually embrace the data we used to call garbage, but were afraid to throw away “just-in-case” For this purpose we will dive a little bit into the following topics:

• What is data management in this age of generative AI?

• Does the adage of Garbage-in and Garbage-out still hold?

• A little bit of data-architecture to help you out

* A little bit of OSDU Data Standards in the mix as well

• And some cool projects you can download and run for yourself to become the AI enabled data manager

• And finally: how you too can stop worrying and love your data

In this panel, leaders from across the energy, technology, and public sectors will discuss if data quality is no longer the barrier it once was – exploring whether AI has truly solved data quality, or simply scaled it up. Expect strong opinions and different perspectives on trust, governance, and what success looks like in an AI-driven world.