In the wave of digital transformation, the value of data lies not only in storage but in understanding. The OiO Data Governance Framework breaks away from traditional table-centric IT governance and pioneers a new paradigm based on Business Ontology.
We do not merely clean data — we define the business.
Through our proprietary Five-Dimensional Business Coordinate Model(Object Domain, Business Domain, Work Domain, Process Domain, Discipline Domain), complex oil & gas operations are decomposed into standardized Minimum Business Units (MBUs).
This unified business description model gives every piece of data clear business semantics — enabling not only human experts to understand it, but also empowering AI models to accurately read, reason, and apply it.
As a result, enterprise-wide data integration and deep convergence can be achieved under a single semantic framework.
We have established a holistic data standard system that is compatible with international OSDU standards and further extended to meet real-world operational needs, ensuring high-quality data from the source:
1. Standardized Business Definitions
Replace obscure database fields with MBUs as the atomic unit of data management. Each data item is directly linked to a specific business activity, realizing the concept of “Data as Business.”
2. Holistic Metadata Framework
Build a comprehensive metadata system covering business attributes, technical attributes, governance attributes, and knowledge graph relationships (KG). Data is no longer isolated — it becomes interconnected knowledge entities.
3. Business-Oriented Data Quality Rules
A built-in library of 32 categories of quality rules (covering completeness, accuracy, consistency, timeliness, etc.) transforms business logic into machine-executable validation standards, ensuring 100% trustworthy data ingestion.
OiO provides an end-to-end standardized governance pipeline, transforming raw data into intelligent assets:
1. Business Modeling
Using the OiO-MME engine, business processes are structured into MBUs and required resources (IPOMSQ), forming a unified semantic backbone.
2. Source Ingestion
Standardized collection templates are generated from the model. Data is captured at the source (e.g., drilling sites, wellhead production, research activities) via JuraEco edge gateways or JuraDataHub — preventing “dirty data” from entering the lake.
3. Intelligent Governance
Data ingestion automatically triggers quality scanning. Rule engines cleanse data while establishing lineage and business relationships.
4. Knowledge Graph Construction
Structured data and unstructured documents are transformed into KG1 instance-level knowledge graphs, creating machine-understandable knowledge assets.
5. Data Asset Serving
Unified APIs enable upper-layer applications such as intelligent search (JuraSearch) and AI-powered Q&A (JuraSeek), realizing a “data finds people” paradigm.
1.Machine-Readable Outcomes
Traditional governance produces database tables — OiO produces knowledge graphs.
All data is ontology-mapped, allowing AI models to directly understand scenarios such as“oil production of Well X at Time Y” along with its business context — without manual interpretation.This forms the foundation for autonomous AI agents.
2. Unified Semantic Model
Eliminates cross-departmental “language barriers.” Exploration, drilling, and production data are all positioned within the same five-dimensional coordinate system, enabling true data interoperability and breaking down silos.
3. Full Lifecycle Management of Business Objects
Core objects such as wells, reservoirs, and equipment are managed across their entire lifecycle — from planning and design to operation and abandonment — providing a complete data asset perspective.
OiO Data Governance brings data back to its business essence —
and injects AI intelligence into the oil & gas industry.
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