Lessons Learned from a Greenhorn Ontologist

Transcription

1 Lessons Learned from a Greenhorn Ontologist Image credit: 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

2 LD4L

3 My Career Path in 4 Bullets Catalog Librarian ( ) Metadata Librarian for Image Collections ( ) Discovery Metadata Librarian ( ) 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:

4 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)

5 Core Modeling/Ontology Concepts Image Credit:

6 Resource

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

8 RDF Resource-something identified with a URI that you can say things about (has relationships to other resources, label, etc.)

9 Library [RDF] Resource Something named with a URI that a library made available the web for patron/world use.

10 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.

11 URIs Continued

12 What does it all mean? Image credit:

13 Records Image credit:

14 URIs or Headings Image credit:

15 Classes and Individuals Image credit:

16 Classesand Individuals

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

18 RDFS RDF Schema provides a basic datamodeling vocabulary for RDF data. Able to define: Classes and sub-classes Properties and sub-properties Domains and ranges

19 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

20 SKOS Example: skos.rdf

21 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. -

22 OWL Primitive Classes Example from:

23 OWL Defined Classes Example from:

24 Cardinality

25 If it is not said, it may still be true. -Samson Tu(from Protégé Short Course)

26 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>.

27 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>

28 Domains and Ranges <foaf:made> <rdfs:domain> <foaf:agent>. <foaf:made> <rdfs:range> <owl:thing>.

29 Transitive Properties <owl:transitiveproperty rdf:id="subregionof"> <rdfs:domain rdf:resource="#region"/> <rdfs:range rdf:resource="#region"/> </owl:transitiveproperty>

30 Axioms Statements in an ontology defining Relationships between entities Class expressions

31 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>.

32 Best Practices/Process Image Credit:

33 Reuse Image credit:

34 Ontology reuse needs something like Image credit:

35 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

36 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

37 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 and demonstrations will be somewhat tied to available data because detailed information and relationships will not be available for all resources.

38 Pilot: Hip Hop Flyer Metadata to RDF with 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 LinkedBrainzURIs for performers to discover relationships to other entities to discover relationships to other entities

39 MusicBrainz

40 About the Hip Hop Flyers

41 Ontology Decisions Describe the flyer in BIBFRAME, extend where needed Used Getty AAT to create bf:work subclasses 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

42 Ontology Decisions: BIBFRAME for Flyers

43 Ontology Decisions: FOAF for Persons

44 Ontology Decisions: Events and Performers

45 You, me, and the future Image credit:

46 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.

47 Current Ontology Conversations BIBFRAME List (Can be pretty testy, but there are voices of reason participating) Protégé User List (lots of trouble shooting Protégé software, also nice ontology design conversations) Lodlam.net,#lodlam on twitter, LODLAM Google Group

48 The Meaning [of My Life] Triangle

49 Art and Science Image credit:

50 Don t Be Afraid to Ask Questions? Image credit:

51 Thank You.