A Single Source of Truth Leaves No Asset Data Behind

Odbok Contributors: Don Sands (Synengco), Steve Miller (Odbok), Mark Freund (Diriger), Jeff Lloyd (Precoda)Author: Greg L Towne (Diriger)

When you combine the expertise, experiences, industry leadership, methodologies, technologies, and systems of the members of a collaborative ecosystem like Odbok, you get the synergy of a rigorous and interoperable Asset Unified Namespace (UNS) that leaves no Asset Management Data behind and hence, provides a Single Source of Truth; be it consistent data or documentation and the methodology to achieve it.


Your problem-solving capability is optimised, enhanced, and then extendable via solutions that are innovative, consistent, and user-actionable from the ground (physical devices) up to multi-enterprise views, decisions, and actions. It is just what you would expect when establishing a modern Industry 4.0 environment that needs more than just a reporting and graphics solution; it is a methodology that delivers a Single Source of Truth.


Let’s look at some of the problems we already know about



Systems and Processes

Critical decisions and actions are occurring in an environment of:

Summary Metaphor

In essence, the current systems and methodologies are akin to a Thermometer; a device that only tells the User the current temperature – whereas what industry really needs is a Thermostat; a device with actionable characteristics in terms of temperature range, durability, vibration resistance, chemical resistance, and application compatibility – so that it can automatically do things in relation to its set point and expected capability.


Current Industry 3.0 attempts at integration are continuing to fail as current technology and approaches are based on linear, discrete, and complex methodologies that continue to create more and more technical debt and sub-optimal outcomes when compared to newer Industry 4.0 capabilities.

These Current state issues are further exacerbated by existing technologies, resources, skills, system atrophy, and implementation methodologies that serve as band-aids and regularly fail. We can illustrate this in the diagram below, where the ‘current state’ is shown within the ISA-95 Levels and is aligned with the standard DIKW Pyramid. 

The significant barriers to success magnify the transitions between ERP, MES and DCS, mainly due to a poor data foundation, linear integration methods and lack of interoperable capabilities. These sub-optimal outcomes result in the Information not being transformed into Knowledge, and Knowledge is not transformed into Insights and Actions.


The atrophy impacts on systems, business misalignment, and interoperability can be the equivalent of a cumulative tax on your organisation from the bottom to the top, with some cumulative estimates being as high as ~70%.


Existing and predictable business expectations and goals have amplified the needs to: 


Our approach is influenced by leveraging several megatrends impacting most asset-intensive operations:

These megatrends drive towards increased use of digital technologies to support better insights, faster decisions, and sustainability within increasingly complex environments and constraints.

Hence, Asset Management needs to accommodate:

The quality of the data used by the digital tools and the humans is the key to making digital machines better decision-makers. A key element of our solution is the design and governance around quality data and structures to amplify the collaboration and its benefits between digital devices and humans to facilitate “Explainable” Artificial Intelligence.


We believe digital solutions should be sticky due to the value they create rather than being sticky due to being locked into a particular vendor’s digital ecosystem. As a result, subscribing to an open standard, vendor-neutral digital ecosystem allows for low-cost solution switching and portability. 

The framework adopted needs to provide for future-proofing of digital technologies as the digital services and components are abstracted away from the digital tools, thus deriving several benefits:

We subscribe to ISO18101 and the OIIE (Open Industrial Interoperable Ecosystem) that form part of the standard to ensure the Interoperable Digital Ecosystem is fully vendor-neutral with open ISO standards as the basis of vendor neutrality.


OIIE - Mimosa - Open Industrial Interoperability Ecosystem 

CCOM - Mimosa


Continuing from the above, a joint effort (working group) is also a work in progress between Texas A&MU and Adelaide’s UniSA on an Asset Data Interoperability Framework (ADIF), which focuses on six main problem areas.

We align with these same focus points and do not underestimate the importance and influence of such alignment in the solutions we have crafted and the direction we will take downstream


We are putting forward several best-of-breed solutions that can interoperate with each other and your existing enterprise systems in a vendor-neutral Enterprise-level UNS (Unified Namespace).  Our methodologies and experience in delivering such solutions allows us to adapt to the customer’s requirements as they progress, without impediment, through multiple levels within an organisational structure.  We do this by packaging the capability of a conceptual UNS, as depicted below.


At a minimum, a UNS should comprise seamless capabilities as follows ….


The Odbok Industry 4.0 Interoperable Ecosystem

This model outlines our Odbok Ecosystem for a federated UNS solution supported by a System-of-Systems interoperable environment and Governance Methodology.  The first step in IT/OT Convergence

Our Unified Namespace provides

Odbok Collaborative Ecosystem

Governance, Methodology and Standards [ODBOK]

Within an interoperable digital ecosystem, the quality of data and alignment of data structures is paramount between all the digital service providers. While each vendor has its data structures and ways of ensuring the quality of the data used, a methodology to support all vendors and solutions reduces the effort required and improves the quality of a combined solution. It also provides for the addition of new vendors into the ecosystem with minimal rework.  

Systems-of-Systems Interoperability [Diriger]

The interoperability capability provided by DirigerHUB makes the solution as seamless and scalable as possible, plus allows for flexible transition approaches aligned to the internal capability within the customer organisation. Additional system-of-systems capabilities and data sources can be added as required.

Diriger also provides Industry standard Asset Master Data Management (Asset MDM), Management of Change (MOC), and API Management (OIIE, OPC, MQTT, etc) for verification and validation (V&V) of data consistency across all application levels.

Plant Optimisation, Simulation, Performance [Synengco]

Sentient System is a decision support and real-time optimisation platform for asset-intensive operations. It uses a self-learning digital twin of a process to provide for model-based decisions. The key to the technology is to automatically maintain alignment between the physical plant and the digital representation of the plant.

Taxonomies, Ontologies, and Standards [Precoda]

A significant key to the success of the Unified Namespace is the agreement, deployment and synthesisation of salient industry standards, appropriate taxonomies and ontologies. Our Off-The-Shelf standards library provides the capability for building synergy between various systems and the desired operating philosophy.



The Odbok Methodology is a Systems and Data Lifecycle methodology, and it will be refined specifically for the customer to encapsulate their objectives and constraints. The Odbok methodology is designed to be implemented in either a greenfield or a brownfield situation, enabling the customer to determine the pace at which remediation and alignment occur. It orchestrates project and maintenance changes across all systems to maintain the integrity of business objectives, compliance, and operations data.

Govern: Develop and maintain your system and site agnostic references e.g. Attributes, measures, UoM, classifications, functional locations, standards, formulas and aggregations.

Design: Develop and maintain your system and site agnostic template catalogues e.g. Asset templates, Hierarchy templates and composite templates.

Build: Develop and maintain your site and system-specific implementations and changes as change packages.

Deploy: Orchestrate the deployment of your changes in concert with the other associated works being done.

Monitor: Monitor the changes that are deployed or implemented directly.  Capture data from the system for input into the quality and health statistics.


The summary below provides an indication of the capabilities that the Enterprise UNS solution can provide in all varying situations.

Business Functions, Decision Drivers and Asset Life-cycle Management  

Models and Terminology  

APM, Modelling and Simulation (Digital Twin)  

Monitors the fundamental changes in performance and asset consumption, continuously calibrates the digital twin by sophisticated machine learning and uses this self-calibrated digital simulation to provide….

Once optimised in the digital world, execute the changes to the real-plant and ensure the actual change aligns with the expected improvement.

Governance Methodology  

Designed and established to assist companies to align, integrate and industrialise the data within their systems in readiness for Digital Transformation and Industry 4.0 Automation initiatives.

A Framework for ….

Refer to the separate section on the Methodology Overview above.




Autonomous / Interoperable computing capability

Data Consistency  

 Data Governance Management  

Methodology includes…..


Various Categorised Object Libraries.…

User Interface and Experience  


Data Storage  

Secure Data Fabric  

Standards and Frameworks  

Current Standards …..

Note: This insight is written by Diriger Pty Ltd on behalf of the contributors from the Odbok Collaborative Ecosystem – visit Odbok.cloud or Diriger.io for more information.