Towards a set of open reference ontologies for 

reasoning and text interoperability across the 

manufacturing domain - an update on the 

Industrial Ontologies Foundry project.

Professor Melinda Hodkiewicz, BHP Fellow for Engineering for Remote Operations, 

NLP-TLP Group at the University of Western Australia

Theme1 Lead, Centre for Transforming Maintenance through Data Science, 

Coordinator, Maintenance Working Group in Industrial Ontologies Foundry, 

TLP Community of Interest Workshop, 2021 Model-Based Enterprise Summit, 

NIST, April 12 - 16, 2021
What and why for ontologies?

https://www.ibm.com/cloud/watson-discovery, http://www.gpt-4.com/ , https://www.oxfordsemantic.tech/

Finding information is no longer a major theoretical challenge

• Intelligent search and text analytics tools (e.g. Watson Discovery),

• Current generation RDF triple stores and semantic reasoning 

engines (e.g. RDFox), 

• Unsupervised pretrained Transformer NLP models (e.g. GPT4)

Given we have these tools....why are ontologies needed for industrial 

engineering applications?

An ontology defines machine-interpretable definitions of shared

concepts, and relations between concepts, using formal explicit

descriptions. 

Ontologies enable reasoning.
Example of value adding use of ontologies 

in engineering design

Example as presented by Berit Gjellan, Vice President – Engineering Manager, 

Aibel, Ontology for Engineering and Procurement, IIOW 2019, Oslo

Piping: 37 000 fittings, 11 000 flanges, 63 000 m piping 

Value ~$US 25 million 

Manual Valves: 3800 items 

Value ~$US 35 million

54 different pipespecs. 

2400 different types of valves available

1700 different design material numbers

3,5M man-hours of construction

Topside, oil 

and gas 

facility

The solution: Semantic Material Master Data The benefits

• Cost reduction of 5% for 

bulk material orders which in 

large projects amounts to 

more than €100 million

• Quality control - a reduction 

of errors in the 

specification of bolt 

lengths from 15% of all 

design drawings to a low 

0.5%.

• Reuse of products/equipment 

and standardization of 

processes

• Basis for future digital twin

The challenge
Industrial Ontology Foundry (IOF) hierarchy

ISO/IEC 21838-2:2020 Information 

technology – Top-level ontologies 

(TLO). Part 2: Basic Formal Ontology 

(BFO)

Common Core Ontology

(CCO)

Information Artefact Ontology

(IAO)
Use of IOF to develop new interoperable ontologies

Ref: Analysis of IOF Ontology architecture (2020), 

S.Kulvatunyou, M.Lee, IOF Meeting.
Maps to

Ontology-based Data Access

(OBDA) help us write better 

queries without knowing the details 

of the underlying data model.

For example, we can query for all 

processes, despite the concept of 

process not existing in our 

relational database.

ONTOP Tool used to create mappings:

Ref: Diego Calvanese, Benjamin Cogrel, Sarah KomlaEbri, Roman Kontchakov, Davide Lanti, Martin Rezk, 

Mariano Rodriguez-Muro, and Guohui Xiao. Ontop: 

Answering SPARQL Queries over Relational Databases. 

In: Semantic Web Journal 8.3 (2017), pp. 471–487.

How ontologies help us to query our data

Relational Database Ontology

Thanks to Caitlin Woods (UWA) for this slide
IOF ontology for industrial maintenance 
Consider end-use when selecting labels (entity types)

– do you want to support reasoning?

Nestor

Item

Problem

Solution

Wikidata

Capital

Author

Image

Child

...1453 other entity 

types

UWA TLP Redcoat 

Phase 2

4000 annotations

HME MWOs

UWA TLP Redcoat 

Phase 1

1000 annotations

Pump MWOs

UWA TLP Redcoat 

Phase 3 (current)

~500 annotations

Pump MWOs

UWA TLP 

Phase 0

Item

Activity

State
Reasoning ...

Natural 

language 

query

Domain-specific and 

Reference Ontologies – all 

constructed with shared, 

open upper ontology

Ontological mapping

Existing 

Corporate

Databases

Figure adapted from Kharlamov, E. et al (2016) Semantic 

access to streaming and static data at Siemens

Asset 

Owner ERP

--------------

Costs, asset 

register & 

history

External 

Remote 

Op. Centre

---------------

Sensor 

data

External 

maintenance 

provider

--------------

Maintenance 

observations 

& work done

Maintainer, 

engineer 

and analyst

Text Mapping
Ontologies – what is the value proposition?

• To enable reasoning

• To share common understanding of the structure of information among 

people and software agents

• To enable reuse of domain knowledge

• To make domain assumptions explicit

In engineering:

• Consistency, quality control and transparency are important

• There are safety and cost consequences to our decisions, and 

• Alignment to International Standards is necessary.

BUT

Ontologies are costly to produce and maintain – hence the need for 

reusable, modular, interoperable ontologies from the Industrial 

Ontology Foundry
More information on the IOF

Website: https://www.industrialontologies.org/

Membership: ~ 200 from industry, government and academia

Mission:

Create a set of core and open reference ontologies that spans the entire 

domain of digital manufacturing. 

Global, digital collaboration process: Slack, GitHub, Google, Confluence, 

regular Working Group meetings

Governance: The IOF will release ontologies under MIT and CC BY 4.0 (or 

similar) licenses. The Open Application Group (OAGi) will manage this 

process.