1. The Industry Ontology Foundry
Barry Smith
National Center for Ontological Research (NCOR) Buffalo, NY
Ontology Summit, NIST
May 15, 2017

2. Slides

3. Early history of ontologies for engineering
A requirement ontology for engineering design J Lin, MS Fox, T Bilgic - Concurrent Engineering, 1996 Ontology as a requirements engineering product KK Breitman, JCS do Prado Leite - Requirements Engineering …, 2003 Ontology-based active requirements engineering framework SW Lee, RA Gandhi - … Engineering Conference, 2005 Revisiting the core ontology and problem in requirements engineering I Jureta, J Mylopoulos… - … Requirements Engineering …, 2008 …

4. Typical reasons for ontology failure
Too many ontologies
Built independently
No common methodology
Short half life
Few definitions (many of them circular, or involving undefined codes)
Few commonly accepted QA standards
Poor training
Poor documentation
Consequence: no real-world examples of industrial use

5. One signal success story: The Gene Ontology (GO, b. 1998)
for consistent tagging of genomics data and literature, now used across all of the life sciences
Uses of ‘ontology’ in PubMed abstracts

6. GO’s three sub-ontologies
is_a
GO’s three sub-ontologies
biological molecular cellular
process function component
part_of
is_a
standard tool in drug discovery …

7. 2004–: extending GO with new ontology modules to provide representations of
cell types
cell parts
protein
population
sequence
metabolism
development
disease
anatomy …

8. RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
Original OBO (Open Biomedical Ontologies) Foundry (b. 2004) (Gene Ontology in yellow)

9. OBO Foundry grows to encompass further domains (2014)
Environments (ENVO)
Populations, Communities (PCO)
Information Artifacts (IAO)
Experiments and Investigations (OBI)

10. OBO Foundry Principles
commitment by developers of all ontology modules to collaborate
Unrestricted open access license
common formal language (OWL, CL)
maintenance in light of scientific advance

11. OBO Foundry Principles
common architecture (BFO, Relation Ontology)
all terms should be singular common nouns
locus of authority, trackers, help desk
all terms have definitions (formal + textual)
orthogonality – one ontology for each domain

12. 8. providing all terms with definitions creates network effects
complex terms in ontologies are defined wherever possible by using simpler terms from existing OBO Foundry ontologies
elevated blood glucose concentration =def
PATO: increased concentration
of CHEBI: glucose
in FMA: blood

13. 9. orthogonality – one ontology for each domain
Create OBO Library
OBO Foundry = subset of OBO Library: Foundry ontologies selected through a process of peer review
Maintain OBO Foundry ontologies as reference ontologies for aggressive reuse using a hub and spokes (and spokes of spokes) strategy

15. Extension Strategy + Modular Organization
top level
mid-level
domain level
Basic Formal Ontology (BFO)
Information Artifact Ontology
(IAO)
Ontology for Biomedical Investigations
(OBI)
Spatial Ontology
(BSPO)
Anatomy Ontology
(FMA*, CARO)
Environment
Ontology
(EnvO)
Infectious Disease Ontology
(IDO*)
Biological Process
Ontology (GO*)
Cell Ontology
(CL)
Cellular
Component
(FMA*, GO*)
Phenotypic Quality
Ontology (PaTO)
Subcellular Anatomy Ontology (SAO)
Sequence Ontology
(SO*)
Molecular Function
(GO*)
Protein Ontology
(PRO*)
* = dedicated NIH funding
Extension Strategy + Modular Organization

16. Hub-and-spokes strategy extended into other domains
NIF Standard
Neuroscience Information Framework
eagle-I
Integrated Semantic Framework / CTSA Connect
cROP / Planteome
Common Reference Ontologies for Plants
UNEP Ontology Framework
United Nations Environment Programme
USGS National Map Ontologies
United States Geological Survey
TRIP Ontologies
Federal Highway Administration (FHWA) Transportation Research Informatics Platform (TRIP)

17. Examples of ontology suites with top-level ontology hubs
Domain
URL
Open Biomedical Ontologies Foundry
life sciences
VIVO-Integrated Semantic Framework (VIVO-ISF) 
scientific research (persons, works, relations of authorship)
Planteome Ontologies
plant science / genomics
Common Core Ontologies (CCO)
military and related domains
Common IC Ontology
intelligence community
Infectious Disease Ontologies (ISO)
Infectious diseases, vaccines
UNEP SDGIO
UN Sustainable Development Interface Ontology
Industry Ontologies Foundry (IOF)

18. ~ 300 ontologies re-using BFO

20. Industry Ontologies Foundry (IOF) initiative, to create a suite of interoperable high quality ontologies covering the domain of industrial (especially manufacturing) engineering

21. Industry Ontologies Foundry – GOVERNMENT
NIST
Nenad Ivezic
Boonserm Kulvatunyou
KC Morris
Vijay Srinivasan
Ram Sriram
Paul Witherell
Evan Wallace …
Air Force Research Lab
Clare Paul …

22. Potential collaborating partners
2015- AFRL / AFMC
AFRL Air Vehicle Platform Ontology
2017- Jet Propulsion Lab (+DoD, …)
Semantic Technologies for Systems Engineering Working Group (STSEWG)

23. Industry Ontologies Foundry – INDUSTRY
Airbus
Autodesk
Cambridge Semantics
CIMData
CUBRC
Dassault Industries
IBM
Oracle
Samsung
SteveRay.com …

24. Industry Ontologies Foundry – ACADEMIA
Clemson University (Venkat Krovi)
École polytechnique fédérale de Lausanne (Dimitris Kiritsis)
INP-ENIT, University of Toulouse (Hedi Karray)
Loughborough University, UK (Bob Young)
National Center for Ontological Research (Kemper Lewis, Neil Otte Rahul Rai, Ron Rudnicki, Barry Smith)
Penn State (Timothy Simpson)
Texas State (Farhad Ameri)
UMass Amherst (Ian Grosse)
University of Toronto (Michael Grüninger) …

25. Industry Ontologies Foundry Kick-Off NIST, December 8, 2017

26. Second Workshop NIST, April 10-11, 2017 Coordinators: Dimitris Kiritsis (EPFL, Lausanne) and Paul Witherell (NIST)
Monday April 10, 2017
• 1:00-1:30 Overview of IOF to Date
1:30-3:15 Panel 1 – Revisiting BFO – What has worked in the past
• 3:30-5:00 Panel 2 – Industrial Implementations – What has worked in the past
Tuesday April 11, 2017
8:30-11:30 Industry Implementations (continued)
1:00-1:45 Case Studies
• 1:45-3:30 Governance – Discussions led by Chris Will (Dassault Industries) and KC Morris (NIST)

27. IOF goal of orthogonality – one ontology for each domain
First step: Industrial Engineering Ontologies portal *
providing easy access to legacy industry ontology resources
Next step: select candidate IO Foundry ontologies through a process of peer review
*Based on National Center for Biomedical Ontology virtual appliance at:

28. IE

30. IOF testbeds DMDII / CUBRC / CHAMP MatOnto Materials Ontology
Basic Formal Ontology
Product Life Cycle Ontology

31. IOF testbeds DMDII / CUBRC / CHAMP MatOnto Materials Ontology
Basic Formal Ontology
Product Life Cycle Ontology

32. Digital Manufacturing and Design Innovation Institute (DMDII)

33. Model-Based Definition (MBD)
Build on successes of CAD technology CAD focused on shape Extend CAD from shape to behavior, materials, product life cycle, … WHY DOES THIS NOT WORK?

34. As companies mature, they must accommodate technological change and technological diversity among vendors and clients Over time, data comes to be stored in different forms that prevent interoperability.
Here: FilemakerPro, a Window’s folder hierarchy, Oracle, and a paper file drawer. This is a rough approximation of Cobham’s situation.

35. DMDII initiative: Coordinated Holistic Alignment of Manufacturing Processes
create a flexible extensible suite of interoperable generic public-domain ontologies covering the domain of manufacturing engineering
test the utility of these ontologies in the day to day work flows of a local manufacturing enterprise

36. CHAMP Holistic Overview
Ontological Semantic Concept Alignment and Refinement (OSCAR) – extension of KARMA tool from USC:
Integrated Data Management System (IDMS) enhances data generated by the product development process
– data about products, parts, functional capabilities, failure modes, tests, test equipment and locations, failures, root causes, corrective actions ...

37. This makes it hard to answer questions requiring data from different sources of data to be aligned.
Questions such as:
How have changes in the quality of vendor-supplied parts led to product failures over time?
What changes could be made in the production process to save time and money while preserving product quality?
Barry, note you can also say this situation is made worse by employees usually have a limited set of Unix permissions even within particular file systems. This means you might have permissions to see production files on one product, but not on vendors. To navigate permissions, I am also working on a Unix permissions ontology. It’s too early for slides though, unfortunately.

38. are out of reach to small companies.
Companies routinely pay consultants to build custom systems to integrate legacy data.
Such custom systems:
are out of reach to small companies.
represent significant investment for large companies, and even then they do not work (and not only for supply chain reasons)
’legacy data’ here denotes data (often old data) prior to a process of integration.

39. CHAMP will:
analyze the domain of industrial manufacturing across the product lifecycle.
work with industry experts and Cobham Industries to address both locally tailored and canonical forms of data.
produce a series of modular, interoperable ontologies that others may download and tailor for free online.
develop natural language processing, optical character recognition, and other solutions to ingesting legacy data.
produce an ontology browser that simplifies the query process for employees.

40. The Common Core Ontologies
Basic Formal Ontology
The Common Core Ontologies
Quality
Info
Time
Agent
Artifact
Event
Unit
Geospatial

41. Product Life Cycle Ontology
Basic Formal Ontology
The Common Core Ontologies
Quality
Info
Time
Agent
Artifact
Event
Unit
Geospatial
Product Life Cycle Ontology
Machine and Tool Ontology
Materials Ontology
Addictive Manufacturing Ontology
Functionally Graded Materials Ontology
Slacks = Semantic Knowledge Manage System for Laminated Composites developed by Ian Grosse from Umass.
CHEBI
SLACKS
Manufacturing Process Ontology

42. Industrial Organization 1
Particulars
Universals
Act of Manufacturing2
Product 2
has output
agent in
Artifact
is input in
instance of
agent in
Industrial Organization 2
inheres in
Act of Manufacturing1
Product Role
Product 1
has output
inheres in
Act of Testing
prescribes
realized in
Design Specification
Function
has output
instance of
Measurement Data
instance of
Realizable Entity
Information Content Entity
Question: How do the parts supplied by suppliers affect testing outcomes of assembled products?

43. Data Alignment uses OSCAR (a proprietary improvement on KARMA)
Data Alignment uses OSCAR (a proprietary improvement on KARMA). This tool imports OWL and CSV files and allows users to create and export mappings, as well as to generate and export RDF. Here we see from the previous slide the radiographic exam, as well as instances of the act that produced them, the inflation device that participates in them, and the acts. Some of these columns were created by using python to transform or supplement the original columns in the CSV file. There are then some preliminary mappings that appear on top of the columns, displaying column URIs.

44. Information Content Entity
Organization 1
Particulars
Universals
Act of Manufacturing2
Product 2
has output
agent in
Artifact
is input in
instance of
agent in
Organization 2
inheres in
Act of Manufacturing1
Product Role
Product 1
has output
Organization 1 produces Product 1 using Product 2 produced by Organization 2. Query all those parts produced by different organizations at different times and compare them to the test results, here represented by the class ‘measurement data’.
inheres in
Act of Testing
prescribes
realized in
Design Specification
Function
has output
instance of
Measurement Data
instance of
Realizable Entity
Information Content Entity
Question: How do the parts supplied by suppliers affect testing outcomes of assembled products?

45. BFO: Generically Dependent continuant BFO:Process BFO: Object
BFO: continuant
BFO: occurrent
Particulars
is a
is a
is a
Universals
BFO: Generically Dependent continuant
BFO:Process
BFO: Object
is a
is a
is a
CCO: Artifact
CCO: Intention Act
is a
instance of
CCO: Information Content Entity
PLC: Product
is a
instance of
CHAMP: Act of Production
instance of
Inflation Device
instance of
participates in
Nominal Measurement Information Content Entity
Information Content Entity Bearer
Act of Lot Acceptance Testing
instance of
inheres in
Here is a diagram showing that an inflation device produced by Cobham was X-rayed during a sample check. The X ray is performed to ensure there are not cracks or bubbles internal to the body of the device. In this instance, the inflation device passed the radiographic exam. [Note: The prefixes included in the universal nodes here include the PLC (product life cycle), CCO (common core ontologies), the CHAMP (formerly referred to as the FLU12 ontology), and of course BFO. ]
participates in
has text value
Act of Radiographic Exam
xsd: “Pass”
has output

46. BFO: continuant
BFO: occurrent
Particulars
is a
is a
is a
Universals
BFO: Generically Dependent continuant
BFO:Process
BFO: Object
Inflation device produced by Cobham passed an X-ray test during a sample check. The X-ray is performed to ensure there are no cracks or bubbles internal to the body of the device.
is a
is a
is a
CCO: Artifact
CCO: Intention Act
is a
instance of
CCO: Information Content Entity
PLC: Product
is a
instance of
CHAMP: Act of Production
instance of
Inflation Device
instance of
participates in
Nominal Measurement Information Content Entity
Information Content Entity Bearer
Act of Lot Acceptance Testing
instance of
inheres in
participates in
has text value
Act of Radiographic Exam
xsd: “Pass”
has output

47. Data Alignment uses OSCAR (a proprietary improvement on KARMA)
Data Alignment uses OSCAR (a proprietary improvement on KARMA). This tool imports OWL and CSV files and allows users to create and export mappings, as well as to generate and export RDF. Here we see from the previous slide the radiographic exam, as well as instances of the act that produced them, the inflation device that participates in them, and the acts. Some of these columns were created by using python to transform or supplement the original columns in the CSV file. There are then some preliminary mappings that appear on top of the columns, displaying column URIs.

48. Data Alignment uses OSCAR (a proprietary improvement on KARMA)
Data Alignment uses OSCAR (a proprietary improvement on KARMA). This tool imports OWL and CSV files and allows users to create and export mappings, as well as to generate and export RDF. Here we see from the previous slide the radiographic exam, as well as instances of the act that produced them, the inflation device that participates in them, and the acts. Some of these columns were created by using python to transform or supplement the original columns in the CSV file. There are then some preliminary mappings that appear on top of the columns, displaying column URIs.

49. Oscar – Tool for Ingesting Legacy Data

50. Return the 25 products having the longest durations of unscheduled maintenance during 2016
To answer this query system might look at the series of RDF statements below
artifact:Product Model X info:prescribes local:SerialNumber_
local:SerialNumber_ ro:participates_in local:Maint_ …
local:Maint_ … ero:occurs_on local:TimeInterval_ :05…
local:TimeInterval_ :05… info:designated_by local:MaintDurationMeasure…
local:MaintDurationMeasure… ero:inheres_in local:MaintDurationHrsToken…
local:MaintDurationHrsToken… has_integer_value n

51. IOF testbeds DMDII / CUBRC / CHAMP MatOnto Materials Ontology
Basic Formal Ontology
Product Life Cycle Ontology

52. MatOnto (background) Materials Genome Initiative
AFRL-managed ontology (‘MatOnto’)
MatOnto software tool:
(~ Protégé for ontology suites)
IOF MatOnto ontology initiative

53. MatOnto: A suite of ontology modules based on BFO
Existing ontologies in process of being re-engineered to be BFO- conformant:
for Laminated Composites: SLACKS (UMass)
for Functionally Graded Materials: FGMO (NCOR, Milan Polytechnic)
Existing ontologies already BFO-conformant:
for Polymers: CHEBI (EBI)
See:

54. IOF testbeds DMDII / CUBRC / CHAMP MatOnto Materials Ontology
Basic Formal Ontology
Product Life Cycle Ontology

55. Extension Strategy + Modular Organization
top level
mid-level
domain level
Basic Formal Ontology (BFO)
Information Artifact Ontology
(IAO)
Ontology for Biomedical Investigations
(OBI)
Spatial Ontology
(BSPO)
Anatomy Ontology
(FMA*, CARO)
Environment
Ontology
(EnvO)
Infectious Disease Ontology
(IDO*)
Biological Process
Ontology (GO*)
Cell Ontology
(CL)
Cellular
Component
(FMA*, GO*)
Phenotypic Quality
Ontology (PaTO)
Subcellular Anatomy Ontology (SAO)
Sequence Ontology
(SO*)
Molecular Function
(GO*)
Protein Ontology
(PRO*)
* = dedicated NIH funding
Extension Strategy + Modular Organization

56. BFO:continuant continuant independent continuant portion of material
object
fiat object part
object aggregate
object boundary
site
dependent continuant
generically dependent continuant
information artifact
specifically dependent continuant
quality
realizable entity
function
role
disposition
spatial region
0D-region
1D-region
2D-region
3D-region

57. BFO:occurrent occurrent processual entity process fiat process part
process aggregate
process boundary
processual context
spatiotemporal region
scattered spatiotemporal region
connected spatiotemporal region
spatiotemporal instant
spatiotemporal interval
temporal region
scattered temporal region
connected temporal region
temporal instant
temporal interval

58. Basic Formal Ontology
types
Continuant
Occurrent
process
Independent
Continuant
material
entity
Specifically
Dependent
Continuant
attribute
qualities, dispositions, functions depend on specific bearers
instances

59. .... ..... ....... Basic Formal Ontology information entity
Continuant
Occurrent
process
Independent
Continuant
material
entity
Generically
Dependent
Continuant
information
entity
information entity
can be copied from
one bearer to another

60. IOF testbeds DMDII / CUBRC / CHAMP MatOnto Materials Ontology
Basic Formal Ontology
Product Life Cycle Ontology

61. Basic Formal Ontology Information entity can be copied to a
Continuant
Occurrent
process
Independent
Continuant
material
entity
Generically
Dependent
Continuant
information
entity
Information entity
can be copied to a
different bearer

62. Top Level organization of BFO
BFO: Continuant
BFO: Occurrent
Material Entity
Attribute
Information Entity
Process
occupies
occupies
Spatial Region
Temporal Region

63. Material Entity
Information Entity
Process
We focus here on these three BFO:categories
(ignoring ‘Attribute’ for the sake of simplicity)

64. Portion of Material Part/Component Switch Boiler Furnace Tank Factory
Material Entity
Information Entity
Process
Portion of Material
Part/Component
Switch
Boiler
Furnace
Tank
Factory
Access road
Delivery vehicle

65. Material Entity
Information Entity
Process
Product Model (output of CAD system)
Requirement Specification
Process Plan
Production Plan
Part/Component List
Maintenance Plan
Maintenance Report
Maintenance History

66. Material Entity
Information Entity
Process
Design Process
Production Process
Production Plan Generation Process
Product Use Process
Product Maintenance Process
Product Inspection Process
End Of Life Process

67. Material Entity
Information Entity
Process

68. Process
Information Entity
Material Entity

69. time
Process
Information Entity
Material Entity

70. Top Level organization of BFO
BFO: Continuant
BFO: Occurrent
Material Entity
Attribute
Information Entity
Process
occupies
occupies
Spatial Region
Temporal Region
For some processes we have also process boundaries (beginning of process, end of process) at determinate Temporal Intervals. For some processes beginnings or endings may be indeterminate

71. BFO: Process Planned Process Product Life Cycle (PLC) Process
Information Entity
Material Entity

72. BFO: Process Planned Process Product Life Cycle (PLC) Process
Part of
Part of
Part of
Part of
Part of
Part of
End of Life Process
Design
Process
Production Plan
Generation Process
Production
Process
Mainten-ance Process
Inter-
sperses
Use
Process
Follows
Follows
Follows
Follows
Information Entity
Material Entity

73. Parthood Structure of PLC
Product Life Cycle (PLC)
Part of
Part of
Part of
Part of
Part of
Part of
End of Life Process
Design
Process
Production Plan
Generation Process
Production
Process
Mainten-ance Process
Inter-
sperses
Use
Process
Follows
Follows
Follows
Follows

74. Is-a (Subtype-of) Structure of the PLC
BFO: Process
Is_a
Product Life Cycle (PLC)
Is-a
Is-a
Is-a
Is-a
Is-a
Is-a
End of Life Process
Design
Process
Production Plan
Generation Process
Production
Process
Mainten-ance Process
Follows
Inter-
sperses
Use
Process
Follows
Follows
Follows
The PLC is a process

75. Is-a (Subtype-of) Structure of the PLC
BFO: Process
Is_a
Product Life Cycle (PLC)
Is-a
Is-a
Is-a
Is-a
Is-a
Is-a
End of Life Process
Design
Process
Production Plan
Generation Process
Production
Process
Mainten-ance Process
Follows
Inter-
sperses
Use
Process
Follows
Follows
Follows
But the successive parts of the PLC are also processes

76. Disposal and Recycling
BFO: Process
Process
Planned Process
Process
Product Life Cycle (PLC)
Part of
Part of
Part of
Part of
Part of
Part of
End of Life Process
Design
Process
Production Plan
Generation Process
Production
Process
Mainten-ance Process
Use
Process
Follows
Follows
Follows
Inter-
sperses
Follows
Generic perspective from the manufacturing industry
Requirement
Planning
Concept Development
Product
Definition
Product Development
Product Introduction
Product
Support
Disposal and Recycling

77. BFO: Process Planned Process Product Life Cycle (PLC) Design Process
Part of
Part of
Part of
Part of
Design
Process
Production Plan
Generation Process
Production
Process
Maintenance Process
Follows
Follows
Follows
Has output
Guides
Information Entity
Production Plan

78. BFO: Process Product Planned Process Product Life Cycle (PLC) Design
Part of
Part of
Part of
Part of
Design
Process
Production Plan
Generation Process
Production
Process
Maintenance Process
Follows
Follows
Follows
Has output
Guided-by
Information Entity
Production Plan
Has-output
Material Entity
Product

79. Maintenance Plan Maintenance Process Generation Process
Guided-by
Has output
Maintenance Plan

80. BFO: Process Planned Process Product Life Cycle (PLC) Design Process
Part of
Part of
Part of
Part of
Design
Process
Production Plan
Generation Process
Production
Process
Maintenance Process
Follows
Follows
Follows
Maintenance Plan
Generation Process
Guided-by
Has output
Has output
Information Entity
Guided-by
Production Plan
Maintenance Plan

81. BFO: Process Planned Process Product Life Cycle (PLC) Design Process
Part of
Part of
Part of
Part of
Design
Process
Production Plan
Generation Process
Production
Process
Maintenance Process
Follows
Follows
Follows
Maintenance Plan
Generation Process
Guided-by
Guided-by
Has output
Has output
Production Plan
Maintenance Plan
Maintenance Report
In what sense is the maintenance process ‘Guided-by’ the maintenance plan? To deal with this we need to introduce the dimension of inspection and decision to maintain (similarly we need to add the dimension of market research and decision to produce, prior to the design and production plan generation processes)

82. BFO: Process Product Planned Process Product Life Cycle (PLC) Design
Part of
Part of
Part of
Part of
Design
Process
Production Plan
Generation Process
Production
Process
Maintenance Process
Follows
Follows
Follows
Has output
Guided-by
Information Entity
Production Plan
Has-output
Material Entity
Product

83. BFO: Process Product Planned Process Product Life Cycle (PLC) Design
Part of
Part of
Part of
Part of
Design
Process
Production Plan
Generation Process
Production
Process
Maintenance Process
Follows
Follows
Follows
Maintenance Plan
Generation Process
Guided-by
Guided-by
Has output*
Has output
Production Plan
Maintenance Plan
Maintenance Report
Has output*
Product
*Two different senses of ‘Has output’? or two different senses of ‘Product’?

85. Technical Manual BFO: Process Planned Process Product Life Cycle (PLC)
Part of
Part of
Part of
Production Plan
Generation Process
Production
Process
Maintenance Process
Follows
Follows
Maintenance Plan
Generation Process
Has output
Guided-by
Has output
Maintenance Report
Guided-by
Production Plan
Maintenance Plan
Maintenance History
Technical Manual

86. Material Entity Raw Material Waste Material Product Has-input
Transformed-into
Product
Has-input
We need to deal with the fact that the end-of-life process normally occurs not merely after some process of use, but after long sequence of processes of use or after a long time period has elapsed

87. Process Material Entity Product Life Cycle (PLC) Information Entity
BFO: Process
Planned Process
Product Life Cycle (PLC)
Process
Part of
Part of
Part of
Part of
Part of
Part of
Design
process
Production Plan
Generation Process
Production
Process
Possession, Storage
Use
Process
End of Life Process
Follows
Follows
Follows
Follows
Follows
Maintenance Plan Generation Process
Part of
Guides
Maintenance
Process
Has output
Is input for
Is input for
Has output
Guides
Is input for
Has output
Requirements Specification
Product Model (Drawing, …)
Production Plan
Maintenance Plan
Guides
Has output
Has output
Maintenance Report
Information Entity
Technical
Documentation
User Documentation
Is input for
Has output
Is input for
Has output
Portion of Raw Material
Portion of Waste Material
Product
Material Entity
Human being (Designer, Manager, Machinist, Maintenance Engineer, User, … )
Factory (Machine, Bulding, …)
Utility Supply System (Energy, Water, Data … )

88. Structure of the Current Ontologies
Basic Formal Ontology
Materials Ontology
The Common Core Ontologies
Machine Ontology
Product Life Cycle (PLC)
Production Plan
Generation Process
Design
Process
Follows
Mainten-ance Process
Use
End of Life Process
Part of
Inter-
sperses
Production
Tool Ontology
Facility Ontology
Product Ontologies
We are leveraging these ontologies, all of which are presently under development. Slacks = Semantic Knowledge Manage System for Laminated Composites developed by Ian Grosse from UMass

89. Slides http://ncor.buffalo.edu/IOF/Ontolog.pptx With thanks to
Dimitris Kiritsis
Neil Otte
Ron Rudnicki

90. Coda: On the Choice of BFO as Top Level Ontology

91. BFO DOLCE SUMO ISO High Fleet Onto- Step
Research CYC
ISO
15926
High
Fleet
Onto-
Step
Small   
Open
Top Level

92. BFO
DOLCE
SUMO
Small  
Open
Top Level 
Documentation
User
Technical
External community review / support
Users
Domain ontology developers

93. BFO DOLCE SUMO ISO High Fleet Onto- Step
Research CYC
ISO
15926
High
Fleet
Onto-
Step
Small   
Open
Top Level
Documentation
User
Technical
External com-munity review / support
Users
Domain onto-logy developers
Axiomatization
OWL
Common Logic
Natural language
definitions
WordNet mapping
Stable
Explicit license