Exploring FIBO Complexity With Crunchbase

Representing Crunchbase IPOs in FIBO

Vladimir Alexiev


1 Introduction

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The Financial Industry Business Ontology (FIBO) by the Enterprise Data Management Council (EDMC) is a family of ontologies and a reference model for representing data in the financial world using semantic technologies. It is used in fintech Knowledge Graph (KG) projects because it offers a comprehensive and principled approach to representing financial data, and a wide set of predefined models that can be used to implement data harmonization and financial data integration. The 2022Q2 FIBO release consisted of 290 ontologies using 380 prefixes (see [5, 6] for details) that cover topics such as legal entities, contracts, agency, trusts, regulators, securities, loans, derivatives, etc. FIBO's reach and flexible ontological approach allow the integration of a wide variety of financial data, but it comes at the price of more complex representation.

Crunchbase (CB) is a well-known dataset by TechCrunch that includes companies, key people, funding rounds, acquisitions, Initial Public Offerings (IPOs), etc. It has about 2M companies with a good mix of established enterprises (including 47k public companies), mid-range companies and startups. We (Ontotext and other Wikidata contributors) have matched 72k CB companies to Wikidata, see this query.

I explore the representation of Crunchbase data (more specifically IPOs) in FIBO and compare it to the simplest possible semantic representation. I therefore illustrate the complexity of FIBO, and explain its flexibility along the way. I finish with some discussion and conclusions as to when FIBO can bring value to fintech KG projects.

1.1 Open Source Project

This example is available as open source at https://github.com/VladimirAlexiev/crunchbase-fibo and includes the following files:

2 Crunchbase Data

Crunchbase consists of 18 tables (available as CSV and a JSON API) that cover companies, universities, persons, financial transactions, events (conferences and workshops), etc. The gist Crunchbase Challenge describes the complete database, but in this blog post I focus on Initial Public Offerings (IPOs). An IPO is when a company goes public (is listed at a stock exchange and starts trading), which is considered one possible "exit" for its investors and founders.

Crunchbase has a table ipos with the following fields:

field type descr
uuid string Unique identifier, never changes
name string Entity name (often empty for IPOs)
type string Entity type (always "ipo" for IPOs)
permalink string Suffix of cb_url. Despite the name, sometimes changes
cb_url anyURI Full Crunchbase URL of the IPO event
rank integer Crunchbase rank (smaller is "more important")
created_at dateTime When the Crunchbase record was created
updated_at dateTime When the Crunchbase record was updated
org_uuid string Points to the company that was listed
stock_exchange_symbol string Exchange code. Uses internal Crunchbase codes that are ambiguous
stock_symbol string Ticker on the exchange
went_public_on dateTime When the company went public (IPO date)
share_price_usd decimal The share price for the stock at the time of IPO, in US dollars
share_price decimal The share price for the stock at the time of IPO, in local currency
share_price_currency_code string Local currency of share price
valuation_price_usd decimal Valuation of the Organization at IPO, in US dollars
valuation_price decimal Valuation of the Organization at IPO, in local currency
valuation_price_currency_code string Local currency of the valuation
money_raised_usd decimal Total amount raised from the IPO, in US dollars
money_raised decimal Total amount raised from the IPO, in local currency
money_raised_currency_code string Local currency of the total amount raised

There are also organization attributes (org_name, org_cb_url, country_code, state_code, region, city) that are redundant, thus not shown above.

select ?item ?itemLabel ?cb ?mic {
  ?item wdt:P7534 ?mic;             # ISO MIC
     p:P528 [ps:P528 ?cb;           # catalog code
             pq:P972 wd:Q10846831]. # catalog
  service wikibase:label { bd:serviceParam wikibase:language "[AUTO_LANGUAGE],en". }

For example, here are the first 4 CB IPO records

field example1 example2 example3 example4
uuid 72d30ebd-53ef-2486-6c29-22785c5173ce 3ad2b068-2d97-f646-0b80-1e5f3d7adfc4 a265c6f6-4b96-4079-096a-967a37f3da2b ee426509-826e-5dd0-9309-e79c8f384904
type ipo ipo ipo ipo
permalink microsoft-ipo--72d30ebd the-walt-disney-company-ipo--3ad2b068 divx-ipo--a265c6f6 xo-group-ipo--ee426509
cb_url https://www.crunchbase.com/ipo/microsoft-ipo--72d30ebd https://www.crunchbase.com/ipo/the-walt-disney-company-ipo--3ad2b068 https://www.crunchbase.com/ipo/divx-ipo--a265c6f6 https://www.crunchbase.com/ipo/xo-group-ipo--ee426509
rank 31712 44186 14752 19369
created_at 2008-02-09 05:25:18 2008-02-09 05:40:32 2008-02-25 23:52:11 2008-02-29 00:31:34
updated_at 2018-02-12 23:11:05 2019-02-25 22:31:49 2018-02-12 23:57:54 2018-02-12 23:41:42
org_uuid fd80725f-53fc-7009-9878-aeecf1e9ffbb 756936c0-c335-f0ae-0a3d-fe26bdff5695 73296f0d-85a5-78d5-90b3-86c5f8981ba9 ff8439cf-097c-a88a-9bb9-dd83d23aa14b
stock_exchange_symbol nasdaq nyse nasdaq nyse
stock_symbol MSFT DIS DIVX XOXO
went_public_on 1986-03-13 1978-01-13 2006-10-22 1999-12-02
share_price_usd 16.0
share_price 16.0
share_price_currency_code USD
valuation_price_usd 160000000
valuation_price 160000000
valuation_price_currency_code USD
money_raised_usd 300000000 145000000 35000000
money_raised 300000000 145000000 35000000
money_raised_currency_code USD USD USD

3 Simple Semantic Model of Crunchbase

The simplest possible semantic representation of CB uses one class per table (subsidiary tables like org_descriptions and org_parent are merged to other classes; and org_parents is a direct RDF relation).

I make URLs based on entity type and uuid. I leverage the fact that UUIDs are globally unique (no conflicts between classes) to put Organizations and People under the abstract superclass Agent and in the same URL namespace cb/agent: this is needed since some financial transactions (in particular funding_round) can involve a mix of persons and organizations.

The following diagram shows the complete CB semantic model of 18 entities:

It is generated from a semantic model in Turtle format (cb-model.ttl) using rdfpuml [3] and PlantUML. This model is concatenated from 18 individual per-table models that include source field names in parentheses (also seen on the overall model).

The individual models are used to generate semantic transformations for Ontotext Refine in the form of SPARQL Update queries. The same updates are used for both initial ingest and update, leveraging a global timestamp and using named graphs per each table row (over 10M graphs). See gist Crunchbase Challenge and [1] for more details, including the model source cb-model.ttl and timing (performance) information of the semantic conversions.

Important: Please note that this model covers all of CB, not just CB IPOs. The IPO class (node) is shown with red border.

4 FIBO Model of Crunchbase IPOs

Now I turn to representing IPOs in FIBO by using the ontologies from the FIBO 2024Q1 release (see gist Converting FIBO from RDF to Turtle).

I use the following colors in the diagrams below.

See the next sections for entity diagrams of different kinds of entities (partial models), followed by an overall model diagram, and a binding of the colors to specific RDF classes.

4.1 IPO Agents

First I represent the agents involved in the IPO: Exchange and Issuer. (Perhaps the main agent is the public that invests money into the shares, but they are not individually represented in FIBO).

4.2 Share, Offering, Listing, Ticker

Now I represent the main entities of the IPO event, which in FIBO are:

Please note that PublicOffering includes a number of non-FIBO properties (i.e. CB custom properties):

  cb:uuid       '(uuid)';
  cb:name       '(name)';
  cb:permalink  '(permalink)';
  cb:url        '(cb_url)'^^xsd:anyURI;
  cb:rank       '(rank)'^^xsd:integer;
  cb:createdAt  'fixDate(created_at)'^^xsd:dateTime;
  cb:updatedAt  'fixDate(updated_at)'^^xsd:dateTime.

Truth be told, these are not very semantic:

However, I didn't want to complicate the model even further by placing these fields in yet more FIBO nodes. Furthermore, we'd have to repeat the same event nodes for both Offering and Listing.

4.3 Financial Factors

The 3 financial factors (share price, market capitalization, money raised) are expressed in 2 currencies each:

Of the 3 factors, Market Capitalization is represented using a more complex pattern:

Please note the URL patterns used by the financial nodes in "national currency" vs in "USD":

<cb/ipo/(uuid)/pricePerShare/(share_price_currency_code)>      vs <cb/ipo/(uuid)/pricePerShare/USD>
<cb/ipo/(uuid)/marketCap/(valuation_price_currency_code)>      vs <cb/ipo/(uuid)/marketCap/USD>
<cb/ipo/(uuid)/marketCapValue/(valuation_price_currency_code)> vs <cb/ipo/(uuid)/marketCapValue/USD>

In an initial version of the mapping, I used a simpler pattern:

<cb/ipo/(uuid)/pricePerShare>                                  vs <cb/ipo/(uuid)/pricePerShareUsd>
<cb/ipo/(uuid)/marketCap>                                      vs <cb/ipo/(uuid)/marketCapUsd>
<cb/ipo/(uuid)/marketCapValue>                                 vs <cb/ipo/(uuid)/marketCapValueUsd>

The difference is subtle but crucial: the current URL pattern effectively merges the financial nodes where the "national currency" is "USD". Since many IPOs are denominated in USD, I can save a significant number of nodes by using URL patterns that incorporate the currency code.

I assume that the monetary fields (eg (money_raised) vs (money_raised_usd)) are identical for US IPOs. If that's true, then the multiple instances of the same statement will be collapsed by the semantic repository on data ingestion, so we won't have duplicate statements in the repository.

4.4 Currencies

Finally, I represent the currencies used for the Financials. This includes USD plus up to 3 national currencies for the 3 financials. (I can't imagine an IPO that would use different national currencies for its 3 financials, but Crunchbase has used separate fields, so I represent separate nodes).

Please note that these nodes are shared between all IPOs, so they are not a large number. And for IPOs that use the same currency for their 3 financials, only 1 pair of nodes will be generated.

FIBO distinguishes betwen currencies and their codes in a particular code set (in this case "CrunchBase currency code set"). But CB uses ISO 4217 standard currency codes, and FIBO already includes such data in the ontology FND/Accounting/ISO4217-CurrencyCodes.rdf, e.g.:

  rdf:type                fibo-fnd-acc-cur:CurrencyIdentifier , owl:NamedIndividual ;
  fibo-fnd-rel-rel:hasTag "USD" ;
  rdfs:label              "USD" ;
  cmns-dsg:denotes        fibo-fnd-acc-4217:USDollar ;
  cmns-id:identifies      fibo-fnd-acc-4217:USDollar ;

  rdf:type                        fibo-fnd-acc-cur:Currency , owl:NamedIndividual ;
  cmns-dsg:hasName                "US Dollar" .
  rdfs:label                      "US Dollar" ;
  fibo-fnd-acc-cur:hasNumericCode "840" ;
  cmns-cxtdsg:isUsedBy            lcc-3166-1:VirginIslandsBritish ...

So why didn't I reuse the FIBO currency nodes and instead made CB currency nodes? The reason is subtle and is described in fibo/issues/1816:

So I decided to play it safe and use the CB currency nodes. The EDM Council has agreed to change the node names a bit to:

fibo-fnd-acc-4217:CurrencyCode-USD, fibo-fnd-acc-4217:Currency-USDollar

And to add a separate coreferencing file that will have sameAs statements for each currency like this:

fibo-fnd-acc-4217:Currency-USDollar owl:sameAs fibo-fnd-acc-4217:Currency-USD

Generated with the following SPARQL query:

construct {
  ?curr owl:sameAs ?currAsCode
} where {
  ?code a fibo-fnd-acc-cur:CurrencyIdentifier; fibo-fnd-rel-rel:hasTag ?c; cmns-id:identifies ?curr.
  bind(iri(concat(str(fibo-fnd-acc-4217:),"Currency-",?c)) as ?currAsCode)

This will effectively add alias URLs for each currency (the two sameAs URLs shown above), so now external data like CB can safely refer to currency nodes like fibo-fnd-acc-4217:Currency-USD.

4.5 Overall FIBO IPOs Model

Finally, I present the overall FIBO IPOs model:

It's a complex graph:

@prefix cb:                <https://ontotext.com/crunchbase/ontology/> .

@prefix cmns-cds:          <https://www.omg.org/spec/Commons/CodesAndCodeSets/> .
@prefix cmns-col:          <https://www.omg.org/spec/Commons/Collections/> .
@prefix cmns-cxtdsg:       <https://www.omg.org/spec/Commons/ContextualDesignators/> .
@prefix cmns-dsg:          <https://www.omg.org/spec/Commons/Designators/> .
@prefix cmns-dt:           <https://www.omg.org/spec/Commons/DatesAndTimes/> .
@prefix cmns-id:           <https://www.omg.org/spec/Commons/Identifiers/> .
@prefix cmns-qtu:          <https://www.omg.org/spec/Commons/QuantitiesAndUnits/> .
@prefix cmns-rlcmp:        <https://www.omg.org/spec/Commons/RolesAndCompositions/> .
@prefix fibo-fbc-fct-mkt:  <https://spec.edmcouncil.org/fibo/ontology/FBC/FunctionalEntities/Markets/> .
@prefix fibo-fbc-fct-ra:   <https://spec.edmcouncil.org/fibo/ontology/FBC/FunctionalEntities/RegistrationAuthorities/> .
@prefix fibo-fbc-fi-fi:    <https://spec.edmcouncil.org/fibo/ontology/FBC/FinancialInstruments/FinancialInstruments/> .
@prefix fibo-fbc-pas-fpas: <https://spec.edmcouncil.org/fibo/ontology/FBC/ProductsAndServices/FinancialProductsAndServices/> .
@prefix fibo-fnd-acc-cur:  <https://spec.edmcouncil.org/fibo/ontology/FND/Accounting/CurrencyAmount/> .
@prefix fibo-fnd-agr-ctr:  <https://spec.edmcouncil.org/fibo/ontology/FND/Agreements/Contracts/> .
@prefix fibo-fnd-arr-id:   <https://spec.edmcouncil.org/fibo/ontology/FND/Arrangements/IdentifiersAndIndices/> .
@prefix fibo-fnd-rel-rel:  <https://spec.edmcouncil.org/fibo/ontology/FND/Relations/Relations/> .
@prefix fibo-ind-mkt-bas:  <https://spec.edmcouncil.org/fibo/ontology/IND/MarketIndices/BasketIndices/> .
@prefix fibo-sec-eq-eq:    <https://spec.edmcouncil.org/fibo/ontology/SEC/Equities/EquityInstruments/> .
@prefix fibo-sec-sec-id:   <https://spec.edmcouncil.org/fibo/ontology/SEC/Securities/SecuritiesIdentification/> .
@prefix fibo-sec-sec-iss:  <https://spec.edmcouncil.org/fibo/ontology/SEC/Securities/SecuritiesIssuance/> .
@prefix fibo-sec-sec-lst:  <https://spec.edmcouncil.org/fibo/ontology/SEC/Securities/SecuritiesListings/> .

What is the reason for this complexity?

4.6 FIBO Changes

I have validated this representation with the EDM Council (see fibo/issues/1808): performed 3 iterations and implemented all suggested additions/corrections.

The initial version of this paper (5-Sep-2023) used FIBO 2022Q2. But there were numerous changes to FIBO since then. This includes:

Elisa Kendall graciously updated the example to use the new ontology terms. For the curious, a detailed diff can be seen on Github. The following namespaces were changed:

@prefix cmns-cds:         <https://www.omg.org/spec/Commons/CodesAndCodeSets/> .
@prefix cmns-col:         <https://www.omg.org/spec/Commons/Collections/> .
@prefix cmns-dsg:         <https://www.omg.org/spec/Commons/Designators/> .
@prefix cmns-dt:          <https://www.omg.org/spec/Commons/DatesAndTimes/> .
@prefix cmns-cxtdsg:      <https://www.omg.org/spec/Commons/ContextualDesignators/> .
@prefix cmns-id:          <https://www.omg.org/spec/Commons/Identifiers/> .
@prefix cmns-qtu:         <https://www.omg.org/spec/Commons/QuantitiesAndUnits/> .
@prefix cmns-rlcmp:       <https://www.omg.org/spec/Commons/RolesAndCompositions/> .
@prefix fibo-fnd-utl-alx: <https://spec.edmcouncil.org/fibo/ontology/FND/Utilities/Analytics/> .
@prefix fibo-fnd-dt-fd:   <https://spec.edmcouncil.org/fibo/ontology/FND/DatesAndTimes/FinancialDates/> .
@prefix lcc-lr:           <https://www.omg.org/spec/LCC/Languages/LanguageRepresentation/> .

4.7 How I Made the Overall Model?

I made the overall model by simply concatenating the Turtle files of the individual models presented in earlier sections. Concatenating any Turtle files produces a valid turtle file, since @prefix and @base can occur anywhere in Turtle. (But don't abuse this feature by redefining prefixes mid-way!)

If you have played with UML XMI files, the simplicity of composing semantic models by simply concatenating them should be refreshing. It mirrors the simplicity of semantic data integration by "simply" converting any kind of data to RDF, using consistent URLs, and "pouring" all data into a semantic repository.

I have used some rdfpuml (PlantUML) layout instructions in the models to improve the look of the overall model. These specify the direction and length of a few arrows, and set colored circles for the classes (called "UML stereotype").

cmns-cxtdsg:appliesTo                  puml:arrow puml:up.
cmns-id:identifies                     puml:arrow puml:up.
cmns-qtu:hasArgument                   puml:arrow puml:up.
cmns-rlcmp:isPlayedBy                  puml:arrow puml:up.
fibo-fbc-fi-fi:isDenominatedIn         puml:arrow puml:down-4.
fibo-fnd-acc-cur:isPriceFor            puml:arrow puml:up.
fibo-fnd-rel-rel:isIssuedBy            puml:arrow puml:up.

cmns-cds:CodeSet                       puml:stereotype "(C,lightgreen)".
cmns-id:IdentificationScheme           puml:stereotype "(S,lightgreen)". # also cmns-cds:CodeSet
cmns-id:Identifier                     puml:stereotype "(I,lightgreen)".
fibo-fbc-fct-mkt:Exchange              puml:stereotype "(X,lightblue)".  # also fibo-fbc-fct-ra:RegistrationAuthority
fibo-fbc-fi-fi:Issuer                  puml:stereotype "(I,lightblue)".  # also fibo-fbc-pas-fpas:Offeror
fibo-fnd-acc-cur:Currency              puml:stereotype "(C,green)".
fibo-fnd-acc-cur:CurrencyIdentifier    puml:stereotype "(I,green)".
fibo-fnd-acc-cur:MonetaryAmount        puml:stereotype "(A,red)".
fibo-fnd-acc-cur:MonetaryPrice         puml:stereotype "(P,red)".
fibo-ind-mkt-bas:MarketCapitalization  puml:stereotype "(C,red)".
fibo-sec-eq-eq:PricePerShare           puml:stereotype "(P,red)".
fibo-sec-sec-id:TickerSymbol           puml:stereotype "(T,lightgreen)".
fibo-sec-sec-iss:PublicOffering        puml:stereotype "(O,yellow)".
fibo-sec-sec-lst:ListedSecurity        puml:stereotype "(S,yellow)".     # also fibo-sec-eq-eq:Share
fibo-sec-sec-lst:Listing               puml:stereotype "(L,yellow)".

4.8 Generating Semantic Transformation

Although the FIBO IPO model is considerably more complex than the CB IPO model, we can use the rdf2sparql script (part of the RDF by Example open source project) to generate a semantic transformation automatically [1].

ipos-fibo.ru is an OntoRefine SPARQL UPDATE transformation (240 lines) generated from the FIBO IPO model that has the following parts:

delete {graph ?cb_ipos_uuid_URL {?_s_ ?_p_ ?_o_}}
where {
  service <rdf-mapper:ontorefine:PROJECT_ID> {
    bind(?c_uuid as ?uuid)
    bind(iri(concat("cb/ipos/",?uuid)) as ?cb_ipos_uuid_URL)
    bind(?c_updated_at as ?updated_at)
  <cb> cb:updatedAt ?UPDATED_AT_DT 
  bind(replace(str(?UPDATED_AT_DT),'T',' ') as ?UPDATED_AT) filter(?updated_at > ?UPDATED_AT)
  graph ?cb_ipos_uuid_URL {?_s_ ?_p_ ?_o_}};

CrunchBase has about 18 tables and each row has uuid and updated_at timestamp. This allows us to process the whole dump and daily updates using the same generated set of scripts, by storing each row of each table in a separate named graph (about 14M graps). We clear only graphs that have been updated since the last ingest. The service <rdf-mapper:ontorefine:PROJECT_ID> pattern is executed against an OntoRefine virtual SPARQL endpoint, whereas cb:updatedAt fetches a global timestamp recorded in the real RDF repository. See rdf2sparql: Global Filtering for details.

Binds come in several varieties:

bind(REPLACE(?created_at,' ','T') as ?created_at_FIXDATE)
bind(strdt(?created_at_FIXDATE,xsd:dateTime) as ?created_at_FIXDATE_xsd_dateTime)
bind(iri(concat("cb/ipo/",?uuid,"/pricePerShare/USD")) as ?cb_ipo_uuid_pricePerShare_USD_URL)

Here are some of the binds. Hopefully you can appreciate how a simple declarative model is used to generate a complex (even cryptic) transformation:

    bind(REPLACE(?created_at,' ','T') as ?created_at_FIXDATE)
    bind(strdt(?created_at_FIXDATE,xsd:dateTime) as ?created_at_FIXDATE_xsd_dateTime)
    bind(REPLACE(?updated_at,' ','T') as ?updated_at_FIXDATE)
    bind(strdt(?updated_at_FIXDATE,xsd:dateTime) as ?updated_at_FIXDATE_xsd_dateTime)
    bind(iri(concat("cb/ipo/",?uuid,"/listing")) as ?cb_ipo_uuid_listing_URL)
    bind(iri(concat("cb/currency/",?share_price_currency_code)) as ?cb_currency_share_price_currency_code_URL)
    bind(iri(concat("cb/ipo/",?uuid,"/ticker")) as ?cb_ipo_uuid_ticker_URL)
    bind(iri(concat("cb/currency/",?valuation_price_currency_code)) as ?cb_currency_valuation_price_currency_code_URL)
    bind(iri(concat("cb/currency/",?money_raised_currency_code)) as ?cb_currency_money_raised_currency_code_URL)
    bind(strdt(?money_raised,xsd:decimal) as ?money_raised_xsd_decimal)
    bind(strdt(?money_raised_usd,xsd:decimal) as ?money_raised_usd_xsd_decimal)
    bind(iri(concat("cb/ipo/",?uuid,"/marketCap/",?valuation_price_currency_code)) as ?cb_ipo_uuid_marketCap_valuation_price_currency_code_URL)
    bind(iri(concat("cb/ipo/",?uuid,"/marketCapValue/",?valuation_price_currency_code)) as ?cb_ipo_uuid_marketCapValue_valuation_price_currency_code_URL)
    bind(iri(concat("cb/ipo/",?uuid,"/pricePerShare/",?share_price_currency_code)) as ?cb_ipo_uuid_pricePerShare_share_price_currency_code_URL)
    bind(iri(concat("cb/ipo/",?uuid,"/marketCap/USD")) as ?cb_ipo_uuid_marketCap_USD_URL)
    bind(iri(concat("cb/ipo/",?uuid,"/marketCapValue/USD")) as ?cb_ipo_uuid_marketCapValue_USD_URL)
    bind(iri(concat("cb/ipo/",?uuid,"/pricePerShare/USD")) as ?cb_ipo_uuid_pricePerShare_USD_URL)

5 Conclusion

FIBO is good for capturing real-world complexity and integrating data from numerous sources, e.g.

However, that flexibility comes at the price of higher complexity. Compare:

Should you use FIBO in fintech applications?

Such calls rest ultimately with the Semantic Data Architect, who should evaluate the tradeoffs of different representations.

Finally, I close with a couple of quips regarding FIBO:

5.1 Acknowledgements

5.2 References

Alexiev, V. 2023. Generation of Declarative Transformations from Semantic Models. European Data Conference on Reference Data and Semantics (ENDORSE 2023) (Mar. 2023).
Alexiev, V. 2012. Implementing CIDOC CRM Search Based on Fundamental Relations and OWLIM Rules. Workshop on Semantic Digital Archives (SDA 2012), part of International Conference on Theory and Practice of Digital Libraries (TPDL 2012) (Paphos, Cyprus, Sep. 2012).
Alexiev, V. 2016. RDF by Example: rdfpuml for True RDF Diagrams, rdf2rml for R2RML Generation. Semantic Web in Libraries (SWIB) (Bonn, Germany, Nov. 2016).
Alexiev, V., Manov, D., Parvanova, J. and Petrov, S. 2013. Large-scale Reasoning with a Complex Cultural Heritage Ontology (CIDOC CRM). Workshop practical experiences with CIDOC CRM and its extensions (CRMEX 2013) at TPDL 2013 (Valetta, Malta, Sep. 2013).
Allemang, D., Garbacz, P., Grądzki, P., Kendall, E. and Trypuz, R. 2021. An Infrastructure for Collaborative Ontology Development: Lessons Learned from Developing the Financial Industry Business Ontology (FIBO). Formal Ontology in Information Systems: Proceedings of the Twelfth International Conference (FOIS 2021). F. Neuhaus and B. Brodaric, eds. IOS Press.
Garbacz, P. and Kendall, E.F. 2022. Reasoning in the FIBO ontology - a challenge. 2nd Semantic Reasoning Evaluation Challenge and 3rd SeMantic Answer Type, Relation and Entity Prediction Tasks Challenge (SemREC/SMART@ISWC) (2022).