lessons learned from a greenhorn ontologistdownloads.alcts.ala.org/mw_ac/ac15_linked_data... ·...

Lessons Learned from a Greenhorn Ontologist

Steven Folsom, Metadata Strategist and Standards Advocate, Cornell University LibraryBeyond the Looking Glass: Real World Linked Data

ALCTS Preconference, ALA Annual Conference, Friday, June 26, 2015

Image credit: https://emmatrinidad.wordpress.com/2014/04/24/yoko-ono/

My Career Path in 4 Bullets

• Catalog Librarian (2005-2006)

• Metadata Librarian for Image Collections (2006-2012)

• Discovery Metadata Librarian (2012-2015)– June 2014 to present- Representative on the LD4L

project, learning from/contributing to ontology discussions and metadata to RDF transformations.

• Metadata Strategist and Standards Advocate (This past Tuesday – present)

Steven Folsom, Metadata Strategist and Standards Advocate, Cornell University Library Beyond the Looking Glass: Real World Linked Data ALCTS Preconference, ALA Annual Conference, Friday, June 26, 2015

Talk Outline

• Modeling/Ontology Concepts– Terms/Vocabulary

– Modeling Languages/Light introduction to OWL

• Modeling Best Practices/Process

• LD4L Example of Applying Some of These Concepts

• Going forward (Skills Required and other Training Opportunities)


Core Modeling/Ontology Concepts


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Resource


Library Resource- something in a library collection meant for patron use


RDF Resource- something identified with a URI that you can say things about (has relationships

to other resources, label, etc.)


http://dbpedia.org/resource/Joseph_Kosuth

Library [RDF] ResourceSomething named with a URI that a library made available the web

for patron/world use.


In linked data a URI identifies the thing/the entity/the RDF

resource.

The thing can have labels and relationships to other things,

but none of these traits *identify* the thing.


URIs Continued


What does it all mean?


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Records



URIs or Headings



Classes and Individuals




Introduction to Modeling Languages[RDFS, SKOS, and OWL… but mostly OWL]

RDFS

RDF Schema provides a basic data-modeling vocabulary for RDF data. Able to define:

• Classes and sub-Classes

• Properties and sub-Properties

– Domains and ranges


SKOS

A vocabulary, built with OWL and RDFS to model concepts

• Supports the building of thesauri, classification schemes, subject heading systems and taxonomies

• A focus on labels, preferred, alternate, and hidden

• Allows for broader/narrower relationships and associative relationships


SKOS

Example:

http://id.loc.gov/authorities/subjects/sh85029624.skos.rdf


OWL

“designed to represent rich and complex knowledge about things, groups of things, and relations between things… can be exploited by computer programs, e.g., to verify the consistency of that knowledge or to make implicit knowledge explicit.”

- http://www.w3.org/OWL/


OWL Primitive Classes

Example from: http://protegewiki.stanford.edu/wiki/ProtegeOWL_API_Advanced_Class_Definitions


OWL Defined Classes

Example from: http://protegewiki.stanford.edu/wiki/ProtegeOWL_API_Advanced_Class_Definitions


Cardinality


“If it is not said, it may still be true.”

-Samson Tu (from Protégé Short Course)


Disjoint Classes

In OWL you can also say two types of things are not the same through disjoint classes.

<foaf:Person> <owl:disjointWith> <foaf:Project> .


Property Types

• Object Properties relate two instances of two classes, e.g.<foaf:Agent> <foaf:made> <owl:Thing> .

• Data Properties relate instances of classes with RDFS Literals and XML Schema datatypes<foaf:Person> <foaf:name> “Joseph Kosuth” .

• Annotation Properties <owl:versionInfo>

<rdfs:label>

<rdfs:comment>

<rdfs:seeAlso>

<rdfs:isDefinedBy>


Domains and Ranges

<foaf:made> <rdfs:domain> <foaf:Agent> .

<foaf:made> <rdfs:range> <owl:Thing> .


Transitive Properties

<owl:TransitiveProperty rdf:ID="subRegionOf"> <rdfs:domain rdf:resource="#Region"/> <rdfs:range rdf:resource="#Region"/>

</owl:TransitiveProperty>


Axioms

Statements in an ontology defining

• Relationships between entities

• Class expressions


Entailments/Inferences

Logic or axioms that are true based on assertions, e.g. If X and Y are true, then Z.

<Cat> <subClassOf> <Mammal> .

<DomesticCat><subClassOf><Cat> .

Entails

<DomesticCat> <subClassOf><Mammal> .


Best Practices/Process


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Reuse


Image credit: https://en.wikipedia.org/wiki/Tower_of_Babel

Ontology reuse needs something like…


Image credit: http://www.dlib.indiana.edu/~jenlrile/metadatamap/

Naming Classes and Properties

• Classes begin with a capital letter and are always singular, e.g. foaf:Person

• Properties begin with a lowercase letter, foaf:made

• Data type properties are nouns/noun phrases, e.g. bf:barcode

• Object properties are verbs/verb phrases, e.g. dc:hasPart

• Use camelCase if a term has more than one word, e.g. skos:ConceptScheme


Consider Reuse When Defining Domain and Range

• Being overly stringent with domains and ranges inhibits their use in perfectly appropriate ways

• In a “Anyone can say anything about anything” world, it’s not wrong to use a property in an unintended way, it just means that we’ll get unintended inferences


Applying some of these concepts in LD4L Use Case 4

Making use of complex graph relationships via queries or patterns (rather than direct connections)… to allow discovery that would not be possible without the semantics of different relationships between items and types of items included in the graph. User stories anddemonstrations will be somewhat tied to available data because detailed information and relationships will not be available for all resources.


Pilot: Hip Hop Flyer Metadata to RDFwith links to MusicBrainz/LinkedBrainz Data

Goals

• Model non-MARC metadata from Cornell Hip Hop Flyer Collection to RDF– Test BIBFRAME for describing the flyers– Test the use of other ontologies for describing other

entities, e.g. events, venues (more on this in a moment)

• Use of LinkedBrainz URIs for performers to discover relationships to other entities to discover relationships to other entities…


MusicBrainz

About the Hip Hop Flyers


Ontology Decisions

• Describe the flyer in BIBFRAME, extend where needed• Used Getty AAT to create bf:Work sub-

classes• Describe events and related entities using

MusicOntology, Event Ontology and Schema.org

• Use foaf:Person’s to reflect RWO persons, with bf:Person as an associated authority


Ontology Decisions: BIBFRAME for Flyers


Ontology Decisions: FOAF for Persons


Ontology Decisions: Events and Performers


You, me, and the future


Image credit: http://www.moma.org/collection/object.php?object_id=81074

Training Opportunities

• Zepheira’s BIBFRAME training (the WHY)

• Library Juice (the HOW and library context)

– Especially the Ontologies and Linked Data Course

• Protégé Short Course- In depth training in OWL and ontology design through the Protégé ontology creation tool.


Current Ontology Conversations

• BIBFRAME List (Can be pretty testy, but there are voices of reasonparticipating)

• Protégé User List (lots of trouble shooting Protégé software, also nice ontology design conversations)

• Lodlam.net,#lodlam on twitter, LODLAM Google Group


The Meaning [of My Life] Triangle


Art and Science


Image credit:http://www.moma.org/learn/moma_learning/joseph-kosuth-one-and-three-chairs-1965

Don’t Be Afraid to Ask Questions?


Image credit: http://www.maciejratajski.com/work/what-is-art

Thank You.


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