1. Introduction to Persistent Identifiers
Summary
Definition of persistent identifiers
Which objects – physical / digital
Proliferation of identifiers
What do identifiers allow us to do
The challenge of real persistence
Social contracts
Present, real examples
Course on persistent identifiers, Madrid (Spain)
Vocabularies and RDF
Kevin Richards
Software Developer
Landcare Research
February 8th, 2012

2. Introduction
This presentation explains how to express your data using standard or common vocabularies
This session is presented by Kevin Richards, Software Developer, at Land Research in New Zealand.

3. Summary
Vocabularies and their expression in RDF
Recommended vocabularies
Introduction to RDF (syntax and semantics)
Tools for working with RDF

4. Recommended Vocabularies
Areas of interest
Taxa, Taxon Concepts
Specimens, Observations, Surveys
Collections
Descriptions (of taxa)
Publications
Geospatial data
Media
People/Agents
Basic metadata

5. Recommended Vocabularies
Taxa, Taxon Concepts
Taxon Name, Taxon Concept, Concept Relationships
TDWG TCS Schema
Taxonomic Databases Working Group, Taxon Concept Schema,
DwC Vocabulary
Darwin Core vocabulary,

6. Recommended Vocabularies
Specimens, Observations, Collection Items
TDWG ABCD Schema
Taxonomic Databases Working Group Access to Biological Collections Data schema,
DwC Vocabulary
Darwin Core vocabulary,

7. Recommended Vocabularies
Natural Collections
Describe a collection, e.g. a herbarium collection
TDWG NCD schema
Taxonomic Databases Working Group Natural Collections Description schema,

8. Recommended Vocabularies
Descriptions
Circumscriptions and protologues for specimens and taxa
TDWG SDD schema
Taxonomic Databases Working Group Structured Descriptive Data schema,
TDWG SPM (Species Profile Model)

9. Recommended Vocabularies
Literature
A bit of a short-coming at present
Can be done to a small degree with Darwin Core ( and other schemas such as RIS
Or linked data ontologies, e.g. Open Citations
Note problem is much bigger than our domain

10. Recommended Vocabularies
Geospatial Data
E.g. locations, coordinates
OGC standards,
Some in DwC

11. Recommended Vocabularies
Media
TDWG Audubon Core

12. Recommended Vocabularies
Other related vocabularies
Generic vocabularies:
People – Friend of a Friend (FOAF),
Metadata - Dublin Core,
Linked Data
GeoNames, DBPedia, TaxonConcept.org, Flickr, Gene Ontology, PubMed

14. Introduction to RDF Resource Description Framework
Resource = thing or piece of data to describe
Based on triples (Subject : Predicate : Object)
Subject X has property value Y
E.g. Specimen CHR1234 has CollectionDate January
Object can be literal or another resource
Has a defined XML representation

15. Introduction to RDF Local identifier: EC 12921 Triples:
E.g.
Local identifier: EC 12921
Triples:
EC is in collection EC
EC has accession number EC 12921
EC collected on 1 August 2001
EC collected by B. Smith …
Possible persistent identifier (URI):

16. RDF formats
Statement - “ has a creator whose value is John Smith”
N3 notation –
: dc:creator “John Smith”.
Xml –
<rdf:Description rdf:about="
<dc:creator>John Smith</dc:creator>
</rdf:Description>

17. rdf:resource Eg <?xml version="1.0"?>
<rdf:RDF xmlns:rdf="
xmlns:dc="
<rdf:Description rdf:about="
<dc:language>en</dc:language>
<dc:creator rdf:resource=" />
</rdf:Description>
</rdf:RDF>

18. Basic RDF rdf:Description – basic description xml node
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="
xmlns:dc="
<rdf:Description rdf:about="
<dc:language>en</dc:language>
</rdf:Description>
</rdf:RDF>
rdf:Description – basic description xml node
Every xml node must be namespaced and the namespace must be resolvable
DublinCore – handy set of basic descriptive elements, such as title, creator, language, etc

19. RDF Triples are atomic May not have all triples at once e.g.
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="
xmlns:dc="
<rdf:Description rdf:about="
<dc:language>en</dc:language>
</rdf:Description>
</rdf:RDF>
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="
xmlns:dc="
<rdf:Description rdf:about="
<dc:lcreator>John Smith</dc:creator>
</rdf:Description>
</rdf:RDF>

20. Introduction to RDF Possible RDF XML representation (DwC):
<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF …>
<rdf:Description rdf:about="
<rdfs:type rdf:resource="
<dwc:occurrenceID>
<dwc:catalogNumber>EC 12921</dwc:catalogNumber>
<dwc:recordedBy>B. Smith</dwc:recordedBy>
<dwc:eventDate> </dwc:eventDate>
<dwc:locationID rdf:resource=“
<dwc:locality></dwc:locality>
<dwc:country>New Zealand</dwc:country>
<dwc:countryCode>NZL</dwc:countryCode>
</rdf:Description>
<rdf:Description rdf:about="
<rdfs:type rdf:resource="
<dwc:identificationID>
<dwc:dateIdentified> </dwc:dateIdentified>
<dwc:identifiedBy>B. Smith</dwc:identifiedBy>
<dwc:taxonID>urn:lsid:indexfungorum.org:names:494891</dwc:taxonID>
<dwc:scientificName>Amanita alba Lam.</dwc:scientificName>
</rdf:RDF>
Comment on location ID (RDF will be shown elsewhere) and describe locationID / locality – locality is the cached text of the location, for handiness, same with taxon
Comment on countryCode – important to use standards!!

21. Introduction to RDF Online resources very useful TDWG
Google sites for Darwin Core etc
have a look at

22. Introduction to RDF RDF Schema Like XML schema
Not “nested” like XML – i.e. Each nested item must be identifiable itself
More object oriented
Various ontology methodologies
RDFS
OWL
OWL-DS
Reasoning, inference

23. RDF Types Eg example.com employee Jane Smith is of type Person
Define data types
Improves control of input data ranges
Good to show if you have typed your objects well
Eg birthDate of a person
<person:birthDate rdf:dataType= "
Eg example.com employee Jane Smith is of type Person
(n3 notation)
_:jane exterms:mailbox .
_:jane rdf:type exterms:Person .
_:jane exterms:name "Jane Smith" .
_:jane exterms:empID "23748"

24. Inference Person A Rdf triple – A knows B Person B
Inferred triple - A is two steps separated from C
Rdf triple – B knows C
Person C

25. Introduction to RDF SPARQL SPARQL Protocol and RDF Query Language
Similar to SQL and other query languages
Allows querying of RDF triple stores

26. Introduction to RDF Vocabularies and inference
Important to reuse existing vocabularies and ontologies if possible
Important to define linkages with other vocabularies if not re-using
Important to define linkages with other date objects if possible
allows reuse, integration, inference queries

27. Tools Useful tools to work with RDF Protégé Sesame Tabulator
Tool for creating RDF vocabularies, ontologies and documents
Sesame
Web based system for creating RDF triple stores and allowing SPARQL queries
Tabulator
Browser plug-in to display user friendly representations of RDF
More on W3 site,

28. Summary/conclusions Recommended vocabularies Introduction to RDF Tools
Taxa, taxon concepts, observations, literature, natural collections, descriptions, geospatial
TDWG a good resource
Introduction to RDF
uses triples, xml representation, uses (requires) URIs and persistent identifiers, schema language with constructs and inferencing, query language
Tools

29. Introduction to Persistent Identifiers
Summary
Definition of persistent identifiers
Which objects – physical / digital
Proliferation of identifiers
What do identifiers allow us to do
The challenge of real persistence
Social contracts
Present, real examples
Course on persistent identifiers, Madrid (Spain)
Vocabularies and RDF
Kevin Richards
Software Developer
Landcare Research
February 8th, 2012