Data-mining the Semantic Web @TCD

Data-mining the Semantic Web
and spatially visualising the results
DAH workshop
Trinity College Dublin 27 May 2015

1 of 63@flynam @bilusaurus
Data-mining the Semantic Web and spatially visualising the results
DAH workshop
Workshop overview
• Morning session : Data-mining
– Open Data
– Linked Data
– Linked Open Data implementation
– Semantic Web and ontologies
– Hands-on practical exercises

DAH workshop
Workshop overview
• Afternoon session : Data visualisation
– Data visualisation concepts introduction
– Web maps and geo-tagging
– Hands-on practical
– Interpretations
– Hermeneutic circle

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But first, a very quick survey
• Your occupation
– UG student
– PG student
– Professional academic
– Non-academic

DAH workshop
A quick survey
• Your age group
– Under 16
– 16-24
– 25-34
– 35-44
– 45-54
– 55 and over

DAH workshop
A quick survey
• How familiar are you with Open Access?
– 1 - Not familiar at all
– 2
– 3
– 4
– 5 – Very familiar

DAH workshop
A quick survey
• How familiar are you with Open Data?
– 1 – Not familiar at all
– 2
– 3
– 4

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A quick survey
• How familiar are you with Linked Data?
– 2
– 3
– 4

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A quick survey
• How familiar are you with the Semantic Web?
– 2
– 3
– 4

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A quick survey
• Have you ever published Open Data?
– Yes
– No

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A quick survey
• Have you ever consumed Linked Open Data
services?
– Yes
– No

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A quick survey
• Please fill in your…
– Name
– Email address
Don’t worry – I’m not going to pass them on to anyone 

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From the horse’s mouth
(source: www.ted.com/talks/tim_berners_lee_on_the_next_web)

DAH workshop

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Open Access
Terminology
Open Data
Big Data
The web of data
The Semantic Web
Linked Data
data mining

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Asking questions of digital datasets
Terminology

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Open Access
Terminology

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Design by Julie Beck
for the Harvard University Neuroinformatics dept
(source: www.juliebcreative.com/portfolio/open-data-logo/)

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Linked Data
Terminology
The linkages between the major Linked Data datasets (source: lod-cloud.net)

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Big Data
Terminology
Wordle of terms associated with Big Data activity (source: sfdata.startupweekend.org)

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5 Stars of Open Data
put your data online under an open license
make it structured (e.g. as an Excel file)
use non-proprietary formats (e.g. XML and not Excel)
use URIs to identify resources
link your data to external datasets

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The RDF Triple

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A Triple Example
‘…the boy’s name is Tom…’
subject
predicate
object

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Triple Linking
‘…Tom is short for Thomas…’
subject
predicate
object

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Graph data

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Serialising RDF
• Turtle
• JSON
• RDF/XML
• N-Triples

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RDF Turtle
@base <http://example.org/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix rel: <http://www.perceive.net/schemas/relationship/> .
<green-goblin>
rel:enemyOf <spiderman> ;
a foaf:Person ; # in the context of the Marvel universe
foaf:name "Green Goblin" .
<spiderman>
rel:enemyOf <green-goblin> ;
a foaf:Person ;
foaf:name "Spiderman", "Человек-паук"@ru .
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2
3

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As N-Triples
<http://example.org/green-goblin> <http://www.perceive.net/schemas/relationship/enemyOf>
<http://example.org/spiderman> .
<http://example.org/green-goblin> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type>
<http://xmlns.com/foaf/0.1/Person> .
<http://example.org/green-goblin> <http://xmlns.com/foaf/0.1/name> "Green Goblin" .
<http://example.org/spiderman> <http://www.perceive.net/schemas/relationship/enemyOf>
<http://example.org/green-goblin> .
<http://example.org/spiderman> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type>
<http://xmlns.com/foaf/0.1/Person> .
<http://example.org/spiderman> <http://xmlns.com/foaf/0.1/name> "Spiderman" .
<http://example.org/spiderman> <http://xmlns.com/foaf/0.1/name>
"u00D0u00A7u00D0u00B5u00D0u00BBu00D0u00BEu00D0u00B2u00D0u00B5u00D0u0
0BA-u00D0u00BFu00D0u00B0u00D1u0083u00D0u00BA"@ru .

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As JSON
{"http://example.org/green-
goblin":{"http://www.perceive.net/schemas/relationship/enemyOf":[{"ty
pe":"uri","value":"http://example.org/spiderman"}],"http://www.w3.org
/1999/02/22-rdf-syntax-
ns#type":[{"type":"uri","value":"http://xmlns.com/foaf/0.1/Person"}],"ht
tp://xmlns.com/foaf/0.1/name":[{"type":"literal","value":"Green
Goblin"}]},"http://example.org/spiderman":{"http://www.perceive.net/s
chemas/relationship/enemyOf":[{"type":"uri","value":"http://example.org
/green-goblin"}],"http://www.w3.org/1999/02/22-rdf-syntax-
ns#type":[{"type":"uri","value":"http://xmlns.com/foaf/0.1/Person"}],"ht
tp://xmlns.com/foaf/0.1/name":[{"type":"literal","value":"Spiderman"},{
"type":"literal","value":"u0427u0435u043bu043eu0432u0435u043a-
u043fu0430u0443u043a","lang":"ru"}]}}

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As RDF/XML
<?xml version="1.0" encoding="utf-8" ?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:ns0="http://www.perceive.net/schemas/relationship/">
<foaf:Person rdf:about="http://example.org/green-goblin">
<ns0:enemyOf>
<foaf:Person rdf:about="http://example.org/spiderman">
<ns0:enemyOf rdf:resource="http://example.org/green-goblin"/>
<foaf:name>Spiderman</foaf:name>
<foaf:name xml:lang="ru">Человек-паук</foaf:name>
</foaf:Person>
</ns0:enemyOf>
<foaf:name>Green Goblin</foaf:name>
</foaf:Person>
</rdf:RDF>

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Visualised as a Graph

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Triplestores
and
Infrastructure
A server farm (source: www.cirrusinsight.com)

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Practical: Making RDF
http://www.franklynam.com/blog.aspx?id=85
Q: Create RDF representations of yourself and
your relationships

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The Semantic Web and Ontologies
The stages of the Web (source: urenio.org)

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Ontological Classes and Properties

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The British Museum data mapping onto the CIDOC CRM
(source: confluence.ontotext.com/display/ResearchSpace/BM+Mapping)

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The CIDOC CRM basic entity types and their relationships
(source: www.cidoc-crm.org/)

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Vocabularies

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Graph data

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Minna Sundberg (source: www.sssscomic.com/comic.php?page=196)

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Querying using SPARQL
SELECT *
WHERE {
?s ?p ?o
} LIMIT 10

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More complex SPARQL
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX letters1916: <http://letters1916.linkedarc.net/ontology/>
PREFIX letters1916data: <http://letters1916.linkedarc.net/data/>
PREFIX schema: <http://schema.org/>
SELECT DISTINCT ?letter ?letterName ?recipientPostalAddressName ?recipientLongitude ?recipientLatitude
WHERE {
?letter rdf:type letters1916:Letter ;
schema:name ?letterName ;
letters1916:recipientLocation ?recipientPostalAddress .
?recipientPostalAddress schema:addressRegion ?recipientPostalAddressRegion ;
FILTER regex(?recipientPostalAddressRegion, 'Galway', 'i')
?recipientPostalAddress schema:name ?recipientPostalAddressName .
?recipientPlace schema:address ?recipientPostalAddress ;
schema:geo ?recipientGeoCoordinates .
?recipientGeoCoordinates schema:longitude ?recipientLongitude ;
schema:latitude ?recipientLatitude
}
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2
3

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Practical: Universities on DBpedia
Q: Get a list of all of the universities that DBpedia
knows about

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SKOS
@prefix dct: <http://purl.org/dc/terms/> .
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix cc: <http://creativecommons.org/ns#> .
<http://linkedarc.net/vocabs/vessel-jar> a skos:Concept ;
cc:license <http://creativecommons.org/licenses/by/3.0> ;
cc:attributionURL <http://linkedarc.net> ;
cc:attributionName "linkedarc.net" ;
skos:inScheme <http://linkedarc.net/vocabs> ;
skos:prefLabel “Jar" ;
skos:scopeNote ”A jar concept. Pottery. This isn’t a great scope note." ;
dct:publisher <http://linkedarc.net> ;
dct:identifier <http://linkedarc.net/vocabs/vessel-jar> ;
dct:issued "2015-02-23"^^xsd:date ;
skos:exactMatch <http://purl.org/heritagedata/schemes/mda_obj/concepts/97609> .

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SPARQL + FILTER
SELECT * WHERE {
?s rdfs:label ?label .
FILTER langMatches(lang(?label), "en”)
}

DAH workshop
SPARQL + FILTER
SELECT * WHERE {
?s rdfs:label ?label .
FILTER langMatches(lang(?label), "en") .
FILTER regex(?label, ”bell", "i”)
}

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SPARQL + FILTER
SELECT * WHERE {
?s dct:dateCreated ?dateCreated .
FILTER (?dateCreated > '1900-01-01'
}

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Practical: British Museum Sarcophagi
Q: Get the find spots of all of the sarcophagi in
the British Museum collection
SPARQL endpoint: http://collection.britishmuseum.org/sparql

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Practical: Archaeological stratigraphy
Q: Get the stratigraphic relationships between
the contexts excavated at Priniatikos Pyrgos
SPARQL endpoint: http://linkedarc.net/sparql

DAH workshop
Stratigraphy explained (very briefly…)
Sample stratigraphic sequence (source: www.lparchaeology.com)

DAH workshop
The Priniatikos Pyrgos ontology

DAH workshop
Practical: Archaeological stratigraphy
Q: Get the stratigraphic relationships between
the contexts excavated at Priniatikos Pyrgos
SPARQL endpoint: http://linkedarc.net/sparql
Hint: you will need to traverse 2 levels of the ontology’s
hierarchy to get at the stratigraphy data

DAH workshop
Practical: Nomisma and Ancient Coins
Q: Get the geo-coordinates of all of the coin
hoards stored in the Nomisma triplestore
SPARQL endpoint: http://nomisma.org/sparql

DAH workshop
Geo-coding the Find Spots
with Google Refine

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The Google Maps API
Address String
Geo-coordinates as JSON

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Export as CSV

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Practical: Getty Concepts
Q: Get all of the Getty URIs that represent
concepts related to amphorae
SPARQL endpoint: http://vocab.getty.edu/sparql

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Additional Linked Data Resources

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One final quick survey
• Please arrange the practicals in terms of how
easy they were to complete (1 for hardest and
5 for easiest)?
– Making your FOAF profile
– DBpedia universities
– British Museum sarcophagi hunting
– Getty vocabularies
– Nomisma coin hoards

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• Would you consider publishing Linked Open
Data in the future?
– 1 – Absolutely not
– 2
– 3
– 4
– 5 – Definitely

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• Would you consider using Linked Open Data
resources (using SPARQL or otherwise) in the
future?
– 2
– 3
– 4

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• Is Linked Open Data a feasible platform on
which to undertake humanities research?
– 2
– 3
– 4

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• Any final comments?

DAH workshop
Thank you!
Martin Lemay (source: twitter.com/martinlemay)

Data-mining the Semantic Web @TCD

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