Industry Ontologies: Case Studies in Creating and Extending Schema.org for Industry-specific Vocabularies

1. Dr Mirek Sopek
Dr Robert Trypuz, Dominik Kuziński
MakoLab SA

2. • It is impossible to forget that Semantic Web
and „Semantics” as we use it in our track title,
owes much to Sir Tim Berners Lee –
the inventor of Web and the Semantic Web
• Tim received yesterday ACM Turing Award,
nicked named: Nobel of Computing

3. • Schema.org (2011), sponsored by the most important search engines: Google,
Microsoft, Yahoo and Yandex, is a large scale collaborative activity with a mission to
create, maintain, and promote schemas for structured data on the WEB pages and
beyond.
• It contains more than 2000 terms: 753 types, 1207 properties and 220 enumerations.
• Schema.org covers entities, relationships between entities and actions.
• Today, about 15 million sites use Schema.org. Random yet representative crawls (Web
Data Commons) show that about 30% of URLs on the web return some form of triples
from schema.org.
• Many applications from Google (Knowledge Graph), Microsoft (like Cortana), Pinterest,
Yandex and others already use schema.org to power rich experiences.
• Think of schema.org as a global Vocabulary for the web transcending domain and
language barriers.

4. http://bl.ocks.org/danbri/raw/1c121ea8bd2189cf411c/

5. • The Industry Ontologies are the subclass of the DOMAIN ONTOLOGIES.
• They are created to represent concepts that are used in a given industry
• They define valid meanings of concepts that are used in the industry
• The essential character of the Industry Ontologies is pragmatism – they
must be useful, practical and easy to use.
• Some examples of the Industrial Ontologies:
FIBO (Finance), GoodRelations (e-commerce), VVO (Volkswagen Vehicle Ontology), UCO (Used
Cars Ontology), GSPAS Ontology (Ford Ontology for Global Study Process Allocation System),
POPE (Purdue Ontology for Pharmaceutical Engineering) …

6. Case studies:
• Automotive ontology – schema.org “core”  auto.schema.org – “hosted extension” 
PURL.ORG/GAO – “external extension”
• Financial ontology – schema.org “core”  fibo.schema.org – “hosted extension”  fibo.org/voc
- „external extension”

7. Design Decisions
• „The driving factor in the design of
Schema.org was to make it easy for
webmasters to publish their data. In
general, the design decisions place more
of the burden on consumers of the
markup.”
R.V. GUHA, D. DAN BRICKLEY, S. MACBETH – „Schema.org
- Evolution of Structured Data on the Web”
Data Model
• Derived from RDFS (RDF Schema)
• Multiple inheritance hierarchy
• POLYMORPHIC PROPERTIES - Each property
may have one or more types as its domain
and its range („domainincludes” and
„rangeincludes”)

8. Usage models
• Under full control of site/messages/data
publishers
• Data EMBEDDED into page, data
representation or into message markup
(HTML, XML)
• Harvested during standard crawling,
message or data processing
Serializations
• RDFa - CANONICAL
• Microdata (native to HTML5)
• JSON-LD

9. Extension mechanism: sequence of specificity
CORE  HOSTED EXTENSIONS  EXTERNAL EXTENSIONS
CORE – „Core, basic vocabulary for describing the kind of entities the most common web
applications need”*
(Built by schema.org team, extended by proposals from community, managed by a community
process with the leading role of schema.org steering committee.)
HOSTED/REVIEWED EXTENSIONS – Domain specific basic vocabularies. The hosted extensions
are reviewed, versioned and published as part of schema.org itself to ensure consistency with the
core and its flat namespace. (Built by the specific interest groups respecting the community
process, reviewed by the schema.org community and approved by the steering committee).
EXTERNAL EXTENSIONS – More specialized, fully independent domain specific vocabularies.
Built by a third party. May go through a feedback process, yet they are hosted and controlled by
the third party to serve its specific application needs.
* http://schema.org/docs/extension.html

10. Extension mechanism: rules for URIs
CORE http://schema.org/<term> http://schema.org/<term>
HOSTED EXT. http://<ext>.schema.org/<term> http://schema.org/<term>
External EXT. http://<ext.domain>/<term> http://<ext.domain>/<term>
Documentation URI: Canonical URI:
CORE http://schema.org/Car http://schema.org/Car
HOSTED EXT. http://auto.schema.org/Motorcycle http://schema.org/Motorcycle
External EXT. http://fibo.org/voc/BusinessEntity http://fibo.org/voc/BusinessEntity
Examples:
Rules:

11. Examples - MICRODATA
div itemscope itemtype="http://schema.org/BankTransfer">
<h1>If you want to donate</h1>
Send <span itemprop="amount" itemscope itemtype="http://schema.org/MonetaryAmount">
<span itemprop="amount">30</span>
<span itemprop="currency" content="USD">$</span>
</span>
via bank transfer to the <span itemprop="beneficiaryBank">European ExampleBank, London</span>
Put "<i itemprop="name">Donate wikimedia.org</i>" in the transfer title.
</div>

12. Examples - RDFa
<div vocab="http://schema.org" typeof="BankTransfer">
<h1>If you want to donate</h1>
Send <span property="amount" typeof="MonetaryAmount">
<span property="amount">30</span>
<span property="currency" content="USD">$</span>
</span>
via bank transfer to the <span property="beneficiaryBank">European ExampleBank,London</span>
Put "<i property=’name’>Donate wikimedia.org</i>" in the transfer title.
</div>

13. Examples – JSON-LD
<script type="application/ld+json">
{"@context": "http://schema.org/",
"@type": "BankTransfer",
"name": "Donate wikimedia.org",
"amount": {
"@type": "MonetaryAmount",
"amount": "30",
"currency": "USD"
},
"beneficiaryBank": "European ExampleBank, London"
}
</script>

15. Automotive Extension
• Extension URI: auto.schema.org
• Designed as the first phase of the GAO project
(Generic Automotive Ontology -
http://automotive-ontology.org)
• First step: extending core vocabulary by a
minimal set of new terms (May 2015)
• Second step: creating auto.schema.org hosted
extension (May 2016)
• Third step: creating POC of the external
extension (March 2017)
Financial extension
• Extension URI: fibo.schema.org
• Inspiration from FIBO project (Financial
Industry Business Ontology – http://fibo.org )
• Going through BOC (Bag-Of-Concept) phase
and using an „Occam Razor” approach.
• First step: extending core vocabulary by a
minimal set of new terms (May 2016)
• Second step: creating fibo.schema.org hosted
extension (published in pending.schema.org
(March 2017))
• Third step: creating POC of the external
extension (March 2017)

16. May 13, 2015
– official introduction
of the Automotive extension
to schema.org
Collaborative project
of Hepp Research GmbH,
MakoLab SA
and many other individuals.

17. … can now be brought to the Web
with the auto.schema.org extension:
See: http://carinsearch.org
for more information

18. • Extension URI:
http://ontologies.makolab.com/gao/
• Based on GAO project (Generic
Automotive Ontology) ontology
• More than 300 classes and 40
properties
• Used to drive SMART search for
an automotive client
• See:
http://ontologies.makolab.com/gao/CarUsageType
http://ontologies.makolab.com/gao/ActiveOrPassiveSafetySystem

19. Extension of the core vocabulary
by a minimal set of new terms
(May 2016)
The hosted extension (published
March 2017) as
pending.schema.org
Collaborative project
of an international group of individuals
lead by MakoLab SA.
Described in: http://schema.org/docs/financial.html

20. The financial extension of schema.org
refers to the most important real world
objects related to banks and financial
institutions:
• A bank and its identification
mechanism
• A financial product
• An offer to the client
• Described in:
http://schema.org/docs/financial.html
Thing CLASSES
Action
TransferAction
MoneyTransfer
Intangible
Service
FinancialProduct
BankAccount
DepositAccount
CurrencyConversionService
InvestmentOrDeposit
BrokerageAccount
DepositAccount
InvestmentFund
LoanOrCredit
CreditCard
MortgageLoan
PaymentCard +
PaymentService
StructuredValue
ExchangeRateSpecification
MonetaryAmount
RepaymentSpecification

21. The financial extension of schema.org
refers to the most important real world
objects related to banks and financial
institutions:
• A bank and its identification
mechanism
• A financial product
• An offer to the client
• Described in:
http://schema.org/docs/financial.html
Thing PROPERTIES
Property
annualPercentageRate
feesAndCommissionsSpecification
interestRate
identifier
leiCode
duration
loanTerm
requiredCollateral
accountMinimumInflow
accountOverdraftLimit
amount
bankAccountType
beneficiaryBank
cashBack
contactlessPayment
currency
currentExchangeRate
domiciledMortgage
downPayment
earlyPrepaymentPenalty
exchangeRate
exchangeRateSpread
floorLimit
gracePeriod
loanMortgageMandateAmount
loanPaymentAmount
loanPaymentFrequency
loanRepaymentForm
loanType
monthlyMinimumRepaymentAmount
numberOfLoanPayments
recourseLoan
renegotiableLoan

22. A bank
Deposit Account
Payment card
The basic models of the
financial objects

23. • Extension URI:
http://fibo.org/voc/
• Based on FIBO project
(Financial Industry Business
Ontology) ontology –
Business Entities
• Used in the POC for SEO,
analytics and search.

24. • Flat namespace (moderate requirement)
• schema.org views (showing super- and sub- types for a given type, showing
properties that can be used)
• References to schema.org for common types and properties
• URI stability and persistence
• Good taxonomy
• Good and comprehensive labels
• Not many restrictions, e.g. property polymorphism not required
Many ontologies can qualify for the transformation !!!

25. The Web Structured Data Revolution
Knowledge Graphs, Rich Snippets,
Conversational Search, Info Boxes, Knowledge Panels,
Semantic Search, Answer Boxes, RankBrain,
Semantic SEO, Rich Cards, Enhanced Analytics
and more …

27. I. DATA analytics for Websites using schema.org
II. Intelligent/Smart search based on schema.org markup
III. Enterprise taxonomies & vocabularies
• Work for both Intra-, Extra- and Inter-net portals
• Does not need Google to cooperate 
• Not limited to „core” or „hosted extensions”
• Works with all serializations, but the easiest is JSON-LD.
• Minimal skills required to create relevant markup

29. Markup in
website’s code
• Schema.org
or external
extension
Google Tag
Manager*
• Additional
setup
Google
Analytics**
• Additional
Dimensions
and Metrics
How does it work?
* Other Tag Managers possible
** Other analytics platforms possible

30. Proof-Of-Concept:
Auto
Model 1
- Name
- Brand
Version1
Model,
fuelConsumption,
fuelType,
numberOfDoors, Color
Version 2
Version 3
Model 2
- Name
- Brand
Version 1
Version 2
Version 3
Model 3
- Name
- brand
Version 1
Version 2
Version 3

31. http://wisem.makolab.pl/ga/car1a.html

36. • Mark your product data
with schema.org markup
• Run the smart Search Crawler
for an Enterprise Website
• Check for schema.org
markup (Microdata or JSON-LD)
• When markup found, create
property map and assign values
• Display enhanced search results

37. Corporate product page + microdata
http://nusil.com/product/r-2370_rtv-silicone-rubber-foam

38. Crawler
Indexer
(Lucene)
Microdata
found
Semantic
Data
WebSite

39. The real values taken from existing data found
by crawler within the marked website pages

42. • External extensions to schema.org
are ideal for exposing enterprise
taxonomies
• OWL ontologies can be “projected”
onto external schema.org format
• No loss of ontology expressivity
• The best example: “GS1 Web
Vocabulary” http://gs1.org/voc/
• GAO, FIBO external extension POCs
“A well-constructed enterprise taxonomy is central to multiple
business functions, including Business Intelligence, Content Strategy a
nd Management, Digital Asset Management, Knowledge Management,
and User Experience.” Strategic Content (http://strategiccontent.com)

44. • Schema.org is an extensible framework to build (convert) industrial ontologies
• Extremely easy to use
• It’s principal use is to enable Structured Data Revolution
• It can also be used for an enterprise’s own needs:
• Enhancing enterprise data quality and meaning by delivering easy to use
vocabulary/taxonomy solution
• Enabling data analytics
• Enabling smart search
• External extensions to schema.org can be used to express most of the industrial
ontologies (easy to match requirements)
• Bridges the gap between enterprise data formats and public web data

45. Robert Trypuz
MakoLab SA
Rzgowska 30
93-172 Łódź
Poland
robert.trypuz@makolab.com
Dominik Kuziński
MakoLab SA
Rzgowska 30
93-172 Łódź
Poland
dominik.kuzinski@makolab.com
MakoLab USA Inc.
20 West University Ave.,
Gainesville, FL 32601
USA
+1 551 226 5488
MakoLab SA
Demokratyczna 46
93-430 Lodz
Poland
+48 600 814 537
Dr Mirek Sopek
sopek@makolab.com