data-mining the semantic web @tcd

Data-mining the Semantic Weband spatially visualising the resultsDAH workshopTrinity College Dublin 27 May 2015

2 of 63@flynam @bilusaurusData-mining the Semantic Web and spatially visualising the resultsDAH workshop

Workshop overview

• Morning session : Data-mining– Open Data– Linked Data– Linked Open Data implementation– Semantic Web and ontologies– Hands-on practical exercises


Workshop overview

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


But first, a very quick survey

• Your occupation– UG student– PG student– Professional academic– Non-academic


A quick survey

• Your age group– Under 16– 16-24– 25-34– 35-44– 45-54– 55 and over


A quick survey

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


A quick survey

• How familiar are you with Open Data?– 1 – Not familiar at all– 2– 3– 4– 5 – Very familiar


A quick survey

• How familiar are you with Linked Data?– 1 – Not familiar at all– 2– 3– 4– 5 – Very familiar


A quick survey

• How familiar are you with the Semantic Web?– 1 – Not familiar at all– 2– 3– 4– 5 – Very familiar


A quick survey

• Have you ever published Open Data?– Yes– No


A quick survey

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


A quick survey

• Please fill in your…– Name– Email address

Don’t worry – I’m not going to pass them on to anyone


From the horse’s mouth

(source: www.ted.com/talks/tim_berners_lee_on_the_next_web)


Open Access

TerminologyOpen Data

Big Data

The web of data

The Semantic WebLinked Data

data mining


Asking questions of digital datasets

Terminology


Open Access

Terminology


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


Linked DataTerminology

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


Big DataTerminology

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


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


The RDF Triple


A Triple Example

‘…the boy’s name is Tom…’

subject

predicate

object


Triple Linking

‘…Tom is short for Thomas…’

subject

predicate

object


Graph data


Serialising RDF

• Turtle

• JSON

• RDF/XML

• N-Triples


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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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> "\u00D0\u00A7\u00D0\u00B5\u00D0\u00BB\u00D0\u00BE\u00D0\u00B2\u00D0\u00B5\u00D0\u00BA-\u00D0\u00BF\u00D0\u00B0\u00D1\u0083\u00D0\u00BA"@ru .


As JSON{"http:\/\/example.org\/green-goblin":{"http:\/\/www.perceive.net\/schemas\/relationship\/enemyOf":[{"type":"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"}],"http:\/\/xmlns.com\/foaf\/0.1\/name":[{"type":"literal","value":"Green Goblin"}]},"http:\/\/example.org\/spiderman":{"http:\/\/www.perceive.net\/schemas\/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"}],"http:\/\/xmlns.com\/foaf\/0.1\/name":[{"type":"literal","value":"Spiderman"},{"type":"literal","value":"\u0427\u0435\u043b\u043e\u0432\u0435\u043a-\u043f\u0430\u0443\u043a","lang":"ru"}]}}


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>


Visualised as a Graph


Triplestoresand

InfrastructureA server farm (source: www.cirrusinsight.com)


Practical: Making RDF

http://www.franklynam.com/blog.aspx?id=85

Q: Create RDF representations of yourself and your relationships


The Semantic Web and Ontologies

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


Ontological Classes and Properties


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


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


Vocabularies


Graph data


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


Querying using SPARQL

SELECT *WHERE {

?s ?p ?o} LIMIT 10


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 ?recipientLatitudeWHERE {

?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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Practical: Universities on DBpedia


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


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> .


SPARQL + FILTER

SELECT * WHERE { ?s rdfs:label ?label .

FILTER langMatches(lang(?label), "en”)}


SPARQL + FILTER

SELECT * WHERE { ?s rdfs:label ?label .

FILTER langMatches(lang(?label), "en") .

FILTER regex(?label, ”bell", "i”)}


SPARQL + FILTER

SELECT * WHERE { ?s dct:dateCreated ?dateCreated .

FILTER (?dateCreated > '1900-01-01'}


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


Practical: Archaeological stratigraphy

Q: Get the stratigraphic relationships between the contexts excavated at Priniatikos Pyrgos

SPARQL endpoint: http://linkedarc.net/sparql


Stratigraphy explained (very briefly…)

Sample stratigraphic sequence (source: www.lparchaeology.com)


The Priniatikos Pyrgos ontology


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


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


Geo-coding the Find Spotswith Google Refine


The Google Maps API

Address String

Geo-coordinates as JSON


Export as CSV


Practical: Getty Concepts

Q: Get all of the Getty URIs that represent concepts related to amphorae

SPARQL endpoint: http://vocab.getty.edu/sparql


Additional Linked Data Resources



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



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



• Would you consider using Linked Open Data resources (using SPARQL or otherwise) in the future?– 1 – Absolutely not – 2– 3– 4– 5 – Definitely



• Is Linked Open Data a feasible platform on which to undertake humanities research?– 1 – Absolutely not– 2– 3– 4– 5 – Definitely



• Any final comments?


Thank you!

Martin Lemay (source: twitter.com/martinlemay)

data-mining the semantic web @tcd

Technology

web of data

bilusaurus data

linked open data services

quick survey

practical exercises

email address dont

age group