SlideShare a Scribd company logo
1 of 33
Download to read offline
Up and running with Wikidata 
Emw 
New York City Wikidata workshop 
2014-12-14
Wikidata is a free linked database that can be 
read and edited by 
humans and machines.
Wikidata's goals 
● Centralize interwiki links 
● Centralize infoboxes 
● Provide an interface for rich queries 
● Structure the sum of all human knowledge
What you'll learn from this talk 
● How to edit Wikidata 
● How to classify 
● Ideas for small projects 
● Wikidata vocabulary 
● Where to find things 
● Awesome tools
Elements of a Wikidata statement
Example: New York City (Q60)
Items and properties 
● Each item and property has its own page 
● Items 
– Represent subjects: Douglas Adams, Challenger disaster 
– Have identifiers like Q42, Q921090 
– 12,906,291 items 
● Properties 
– Represent attribute names: occupation, has cause 
– Have identifiers like P106, P828 
– 1,329 properties
Statements and claims 
● Claims 
– Claims are “triplets” 
● Formally: subject, predicate, object 
● In Wikidata: item, property, value 
● Example: Douglas Adams, occupation, author 
● Statements 
– A claim is only part of a statement 
– Statements also include: 
● References 
● Ranks
Qualifiers, ranks, references 
●Qualifiers 
– Qualifiers are properties used on claims rather than items 
– “Yonkers population 12,733 at time (P585) 1860” 
●Ranks 
– Preferred, normal, deprecated 
– Useful to mark outdated claims 
●References 
– Source of claim; provenance 
– “... stated in (P248) 1860 United States Census”
More on Wikidata vocabulary 
https://www.wikidata.org/wiki/Wikidata:Glossary
Finding Wikidata items 
Wikipedia articles have a Wikidata item link in the 
left navigation panel.
Finding Wikidata items 
Wikidata search is quick and effective. 
Instant search suggests items that have labels or 
aliases matching your keyword.
Search by label
Search by alias: “flu” -> influenza
Finding properties 
● Is there a property for “number of windows”? 
● What was the ID of that property, again? 
● Search 
– In main site search box, prefix search term with “P:” 
– “P:number of”, “P:occupation” 
– Instant search doesn't work for properties, only items 
● Browse 
– https://www.wikidata.org/wiki/Wikidata:List_of_properties 
^ bookmark this!
Let's edit Wikidata.
Walking through edits for: 
Yonkers, New York 
https://www.wikidata.org/wiki/Q128114
Yonkers TODO 
https://www.wikidata.org/wiki/Q128114 
● population (P1082) claims for historical table in 
https://en.wikipedia.org/wiki/Yonkers,_New_York#Demographics 
● Include references! “1860 United States Census”, etc. 
● To add to item from inbofox: 
– head of government (P6), office held by head of government (P1313) 
– date of foundation or creation (P571) 
– ZIP code (P281)
Area? Population density? 
● Properties with units (km^2, people/km^2, $) 
are not yet possible 
● “Units” datatype in development 
● https://phabricator.wikimedia.org/T65722
Tools 
– Querying: Autolist, by Magnus Manske 
● http://tools.wmflabs.org/autolist/autolist1.html 
– Batch editing: Widar, by Magnus Manske 
● https://tools.wmflabs.org/autolist/ 
– Software framework: Wikidata Toolkit, by Markus Kroetzsch et al. 
● https://www.mediawiki.org/wiki/Wikidata_Toolkit 
● https://github.com/Wikidata/Wikidata-Toolkit
Querying in Wikidata 
List of politicians who died of a heart attack 
Pseudo-query: 
occupation: politician AND cause of death: heart attack 
occupation: P106 
politician: Q82955 
cause of death: P509 
heart attack: Q12152 
Wikidata query in Autolist: 
claim[106:82955] AND claim[509:12152]
http://tools.wmflabs.org/autolist/autolist1.html?q=claim[106:82955]%20AND%20claim[509:12152]
Classification on Wikidata 
● Taxonomy of knowledge 
● Enables powerful inference, novel applications 
● Interesting philosophical, design, and engineering issues
Tree of Porphyry 
User:VoiceOfTheCommons, CC-BY-SA 3.0
Classes and instances 
● Plato is a human is a animal 
● Plato instance of human subclass of animal 
● Instance: concrete object, individual 
● Class: abstract object
Classification on Wikidata 
● instance of (P31) 
– rdf:type in RDF and OWL 
– 11,930,243 usages 
– Most popular Wikidata property 
● subclass of (P279) 
– “all instances of A are also instances of B” 
– rdfs:subClassOf in RDF and OWL 
– 170,571 usages
Examples 
● USS Nimitz instance of Nimitz-class aircraft carrier 
Nimitz-class aircraft carrier subclass of aircraft carrier 
● 2012 Cannes Film Festival instance of Cannes Film Festival 
Cannes Film Festival subclass of film festival 
● an individual charm quark instance of charm quark 
charm quark subclass of quark 
^ Many “leaf nodes” in Wikidata's taxonomic hierarchy are not instances. 
(There are no items about individual quarks on Wikidata!) 
https://www.wikidata.org/wiki/Help:Basic_membership_properties
Bad smells 
Item has many instance of or subclass of claims 
Items typically satisfy a huge number of instance of claims: 
● Fido instance of dog 
● Fido instance of English Pointer 
● Fido instance of faithful animal 
● … 
Solution: use one class for instance of, put other class 
knowledge into normal properties 
● Fido instance of dog 
● Fido breed: English Pointer 
● Fido known for: faithfulness 
● ...
Bad smells 
subclass of claim that is nonsensical when interpreted as “All 
instances of A are also instances of B” 
Example: 
dog subclass of pet 
But not all dogs are pets! 
feral dog subclass of dog true 
feral dog subclass of pet false 
:. dog subclass of pet false 
Solution: put “pet” knowledge about dogs into claim that does not 
apply to all instances of dog. E.g. “dog has role pet”. (Has role 
would not be transitive. Also needed: some/all quantifier.)
Classification on Wikidata 
● Last but not least: part of (P361) 
– Third basic membership property 
– Top-level “part-whole” relation 
● Instance of, subclass of and part of are all transitive 
● Transitive relation: 
A subclass of B 
B subclass of C 
:. A subclass of C 
https://www.wikidata.org/wiki/Help:Basic_membership_properties
Ideas for small projects 
● Add data about towns and cities 
– population (P1082) 
– head of government (P6) 
● Add medical knowledge about historical figures 
– medical condition (P1050) 
– cause of death (P509) 
– manner of death (P1196) 
● Add cultural knowledge about works of art 
– instance of (P31) 
– creator (P170) 
– material used (P186) 
– collection (P195)

More Related Content

What's hot

FedX - Optimization Techniques for Federated Query Processing on Linked Data
FedX - Optimization Techniques for Federated Query Processing on Linked DataFedX - Optimization Techniques for Federated Query Processing on Linked Data
FedX - Optimization Techniques for Federated Query Processing on Linked Dataaschwarte
 
Semantic Web And Coldfusion
Semantic Web And ColdfusionSemantic Web And Coldfusion
Semantic Web And Coldfusionwilliam_greenly
 
Wikipedia infobox type_prediction_slides_dl4_k_gs
Wikipedia infobox type_prediction_slides_dl4_k_gsWikipedia infobox type_prediction_slides_dl4_k_gs
Wikipedia infobox type_prediction_slides_dl4_k_gsRussa Biswas
 
Web Data Management with RDF
Web Data Management with RDFWeb Data Management with RDF
Web Data Management with RDFM. Tamer Özsu
 
An Introduction to RDF and the Web of Data
An Introduction to RDF and the Web of DataAn Introduction to RDF and the Web of Data
An Introduction to RDF and the Web of DataOlaf Hartig
 
Rich Data? Poor Data? Depends on...
Rich Data? Poor Data? Depends on...Rich Data? Poor Data? Depends on...
Rich Data? Poor Data? Depends on...Lars G. Svensson
 
18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italiani
18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italiani18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italiani
18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italianiDiego Valerio Camarda
 
PyConUK 2016 - Writing English Right
PyConUK 2016  - Writing English RightPyConUK 2016  - Writing English Right
PyConUK 2016 - Writing English RightTatiana Al-Chueyr
 
ALEC (A List of Everything Cool)
ALEC (A List of Everything Cool)ALEC (A List of Everything Cool)
ALEC (A List of Everything Cool)Roderic Page
 
On the Way to a Holding Ontology
On the Way to a Holding OntologyOn the Way to a Holding Ontology
On the Way to a Holding OntologyJakob .
 
Connections that work: Linked Open Data demystified
Connections that work: Linked Open Data demystifiedConnections that work: Linked Open Data demystified
Connections that work: Linked Open Data demystifiedJakob .
 
December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...
December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...
December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...DeVonne Parks, CEM
 
DBpedia Archive using Memento, Triple Pattern Fragments, and HDT
DBpedia Archive using Memento, Triple Pattern Fragments, and HDTDBpedia Archive using Memento, Triple Pattern Fragments, and HDT
DBpedia Archive using Memento, Triple Pattern Fragments, and HDTHerbert Van de Sompel
 
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIsJosef Petrák
 
MLB Teams Logic Puzzle Solution
MLB Teams Logic Puzzle SolutionMLB Teams Logic Puzzle Solution
MLB Teams Logic Puzzle SolutionPhactoidPhil
 

What's hot (18)

FedX - Optimization Techniques for Federated Query Processing on Linked Data
FedX - Optimization Techniques for Federated Query Processing on Linked DataFedX - Optimization Techniques for Federated Query Processing on Linked Data
FedX - Optimization Techniques for Federated Query Processing on Linked Data
 
Semantic Web And Coldfusion
Semantic Web And ColdfusionSemantic Web And Coldfusion
Semantic Web And Coldfusion
 
Wikipedia infobox type_prediction_slides_dl4_k_gs
Wikipedia infobox type_prediction_slides_dl4_k_gsWikipedia infobox type_prediction_slides_dl4_k_gs
Wikipedia infobox type_prediction_slides_dl4_k_gs
 
Web Data Management with RDF
Web Data Management with RDFWeb Data Management with RDF
Web Data Management with RDF
 
An Introduction to RDF and the Web of Data
An Introduction to RDF and the Web of DataAn Introduction to RDF and the Web of Data
An Introduction to RDF and the Web of Data
 
Rich Data? Poor Data? Depends on...
Rich Data? Poor Data? Depends on...Rich Data? Poor Data? Depends on...
Rich Data? Poor Data? Depends on...
 
Keynote session - LOD2014 W3C event
Keynote session - LOD2014 W3C eventKeynote session - LOD2014 W3C event
Keynote session - LOD2014 W3C event
 
18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italiani
18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italiani18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italiani
18 ° Nexa Lunch Seminar - Lo stato dell'arte dei Linked Open Data italiani
 
PyConUK 2016 - Writing English Right
PyConUK 2016  - Writing English RightPyConUK 2016  - Writing English Right
PyConUK 2016 - Writing English Right
 
ALEC (A List of Everything Cool)
ALEC (A List of Everything Cool)ALEC (A List of Everything Cool)
ALEC (A List of Everything Cool)
 
Linked Open Data stuff
Linked Open Data stuffLinked Open Data stuff
Linked Open Data stuff
 
On the Way to a Holding Ontology
On the Way to a Holding OntologyOn the Way to a Holding Ontology
On the Way to a Holding Ontology
 
Clark - Metadata is the Message
Clark - Metadata is the MessageClark - Metadata is the Message
Clark - Metadata is the Message
 
Connections that work: Linked Open Data demystified
Connections that work: Linked Open Data demystifiedConnections that work: Linked Open Data demystified
Connections that work: Linked Open Data demystified
 
December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...
December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...
December 2, 2015: NISO/NFAIS Virtual Conference: Semantic Web: What's New and...
 
DBpedia Archive using Memento, Triple Pattern Fragments, and HDT
DBpedia Archive using Memento, Triple Pattern Fragments, and HDTDBpedia Archive using Memento, Triple Pattern Fragments, and HDT
DBpedia Archive using Memento, Triple Pattern Fragments, and HDT
 
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
 
MLB Teams Logic Puzzle Solution
MLB Teams Logic Puzzle SolutionMLB Teams Logic Puzzle Solution
MLB Teams Logic Puzzle Solution
 

Viewers also liked

An Ambitious Wikidata Tutorial
An Ambitious Wikidata TutorialAn Ambitious Wikidata Tutorial
An Ambitious Wikidata Tutorial_Emw
 
Wikidata for libraries and archives
Wikidata for libraries and archivesWikidata for libraries and archives
Wikidata for libraries and archives_Emw
 
Wikidata presentation at SemTechBiz Berlin 2012
Wikidata presentation at SemTechBiz Berlin 2012Wikidata presentation at SemTechBiz Berlin 2012
Wikidata presentation at SemTechBiz Berlin 2012Denny Vrandecic
 
Lecture slides6; Construction contract financial planning
Lecture slides6; Construction contract financial planningLecture slides6; Construction contract financial planning
Lecture slides6; Construction contract financial planningJB Nartey
 
Wikidata and the Semantic Web of Food
Wikidata and the  Semantic Web of FoodWikidata and the  Semantic Web of Food
Wikidata and the Semantic Web of FoodBenjamin Good
 

Viewers also liked (6)

An Ambitious Wikidata Tutorial
An Ambitious Wikidata TutorialAn Ambitious Wikidata Tutorial
An Ambitious Wikidata Tutorial
 
Wikidata for libraries and archives
Wikidata for libraries and archivesWikidata for libraries and archives
Wikidata for libraries and archives
 
Wikidata presentation at SemTechBiz Berlin 2012
Wikidata presentation at SemTechBiz Berlin 2012Wikidata presentation at SemTechBiz Berlin 2012
Wikidata presentation at SemTechBiz Berlin 2012
 
Lecture slides6; Construction contract financial planning
Lecture slides6; Construction contract financial planningLecture slides6; Construction contract financial planning
Lecture slides6; Construction contract financial planning
 
Argument pp 1
Argument pp 1Argument pp 1
Argument pp 1
 
Wikidata and the Semantic Web of Food
Wikidata and the  Semantic Web of FoodWikidata and the  Semantic Web of Food
Wikidata and the Semantic Web of Food
 

Similar to Up and running with Wikidata

20141114 wikidata glam_workshop2
20141114 wikidata glam_workshop220141114 wikidata glam_workshop2
20141114 wikidata glam_workshop2Sebastiaan ter Burg
 
Entity Linking, Link Prediction, and Knowledge Graph Completion
Entity Linking, Link Prediction, and Knowledge Graph CompletionEntity Linking, Link Prediction, and Knowledge Graph Completion
Entity Linking, Link Prediction, and Knowledge Graph CompletionJennifer D'Souza
 
A Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsA Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsDr. Neil Brittliff
 
Understanding the Standards Gap
Understanding the Standards GapUnderstanding the Standards Gap
Understanding the Standards GapDan Brickley
 
Evaluation Initiatives for Entity-oriented Search
Evaluation Initiatives for Entity-oriented SearchEvaluation Initiatives for Entity-oriented Search
Evaluation Initiatives for Entity-oriented Searchkrisztianbalog
 
Csvconf data hacking-with_wikimedia_projects
Csvconf data hacking-with_wikimedia_projectsCsvconf data hacking-with_wikimedia_projects
Csvconf data hacking-with_wikimedia_projectsmattsenate
 
Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...
Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...
Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...Maximilian Klein
 
Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...
Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...
Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...Elwin Huaman
 
Curation and Digital Storytelling
Curation and Digital StorytellingCuration and Digital Storytelling
Curation and Digital StorytellingShawn Day
 
2014 10-11 Wikidata talk London WMF UK
2014 10-11 Wikidata talk London WMF UK2014 10-11 Wikidata talk London WMF UK
2014 10-11 Wikidata talk London WMF UKMagnus Manske
 
Web Driven Revolution For Library Data
Web Driven Revolution For Library DataWeb Driven Revolution For Library Data
Web Driven Revolution For Library DataRichard Wallis
 
VALA Tech Camp 2017: Intro to Wikidata & SPARQL
VALA Tech Camp 2017: Intro to Wikidata & SPARQLVALA Tech Camp 2017: Intro to Wikidata & SPARQL
VALA Tech Camp 2017: Intro to Wikidata & SPARQLJane Frazier
 
2014-02-27 Wikidata talk Cambridge
2014-02-27 Wikidata talk Cambridge2014-02-27 Wikidata talk Cambridge
2014-02-27 Wikidata talk CambridgeMagnus Manske
 
Digital Narratives for Transylvania DH
Digital Narratives for Transylvania DHDigital Narratives for Transylvania DH
Digital Narratives for Transylvania DHShawn Day
 
Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...
Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...
Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...Olivier Grisel
 
Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...
Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...
Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...Onando Mulang'
 
Wikipedia and Civic Engagement
Wikipedia and Civic EngagementWikipedia and Civic Engagement
Wikipedia and Civic EngagementAndrew Lih
 
Creating Narrative with Digital Objects
Creating Narrative with Digital ObjectsCreating Narrative with Digital Objects
Creating Narrative with Digital ObjectsShawn Day
 
Entity Retrieval (SIGIR 2013 tutorial)
Entity Retrieval (SIGIR 2013 tutorial)Entity Retrieval (SIGIR 2013 tutorial)
Entity Retrieval (SIGIR 2013 tutorial)krisztianbalog
 

Similar to Up and running with Wikidata (19)

20141114 wikidata glam_workshop2
20141114 wikidata glam_workshop220141114 wikidata glam_workshop2
20141114 wikidata glam_workshop2
 
Entity Linking, Link Prediction, and Knowledge Graph Completion
Entity Linking, Link Prediction, and Knowledge Graph CompletionEntity Linking, Link Prediction, and Knowledge Graph Completion
Entity Linking, Link Prediction, and Knowledge Graph Completion
 
A Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsA Little SPARQL in your Analytics
A Little SPARQL in your Analytics
 
Understanding the Standards Gap
Understanding the Standards GapUnderstanding the Standards Gap
Understanding the Standards Gap
 
Evaluation Initiatives for Entity-oriented Search
Evaluation Initiatives for Entity-oriented SearchEvaluation Initiatives for Entity-oriented Search
Evaluation Initiatives for Entity-oriented Search
 
Csvconf data hacking-with_wikimedia_projects
Csvconf data hacking-with_wikimedia_projectsCsvconf data hacking-with_wikimedia_projects
Csvconf data hacking-with_wikimedia_projects
 
Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...
Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...
Häskell und Grepl: Data Hacking Wikimedia Projects Exampled With Open Access ...
 
Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...
Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...
Quipu: Quechua Knowledge Graph [Pilot: Building virtual assistants based on Q...
 
Curation and Digital Storytelling
Curation and Digital StorytellingCuration and Digital Storytelling
Curation and Digital Storytelling
 
2014 10-11 Wikidata talk London WMF UK
2014 10-11 Wikidata talk London WMF UK2014 10-11 Wikidata talk London WMF UK
2014 10-11 Wikidata talk London WMF UK
 
Web Driven Revolution For Library Data
Web Driven Revolution For Library DataWeb Driven Revolution For Library Data
Web Driven Revolution For Library Data
 
VALA Tech Camp 2017: Intro to Wikidata & SPARQL
VALA Tech Camp 2017: Intro to Wikidata & SPARQLVALA Tech Camp 2017: Intro to Wikidata & SPARQL
VALA Tech Camp 2017: Intro to Wikidata & SPARQL
 
2014-02-27 Wikidata talk Cambridge
2014-02-27 Wikidata talk Cambridge2014-02-27 Wikidata talk Cambridge
2014-02-27 Wikidata talk Cambridge
 
Digital Narratives for Transylvania DH
Digital Narratives for Transylvania DHDigital Narratives for Transylvania DH
Digital Narratives for Transylvania DH
 
Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...
Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...
Universal Topic Classification - Named Entity Disambiguation (IKS Workshop Pa...
 
Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...
Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...
Arjun@WISE-2020 : Encoding Knowledge Graph Context in an Attentive Neural Net...
 
Wikipedia and Civic Engagement
Wikipedia and Civic EngagementWikipedia and Civic Engagement
Wikipedia and Civic Engagement
 
Creating Narrative with Digital Objects
Creating Narrative with Digital ObjectsCreating Narrative with Digital Objects
Creating Narrative with Digital Objects
 
Entity Retrieval (SIGIR 2013 tutorial)
Entity Retrieval (SIGIR 2013 tutorial)Entity Retrieval (SIGIR 2013 tutorial)
Entity Retrieval (SIGIR 2013 tutorial)
 

Recently uploaded

VidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptxVidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptxolyaivanovalion
 
BPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptx
BPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptxBPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptx
BPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptxMohammedJunaid861692
 
Data-Analysis for Chicago Crime Data 2023
Data-Analysis for Chicago Crime Data  2023Data-Analysis for Chicago Crime Data  2023
Data-Analysis for Chicago Crime Data 2023ymrp368
 
Call Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girl
Call Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girlCall Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girl
Call Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girlkumarajju5765
 
Edukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFxEdukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFxolyaivanovalion
 
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...shivangimorya083
 
Week-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionWeek-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionfulawalesam
 
Mature dropshipping via API with DroFx.pptx
Mature dropshipping via API with DroFx.pptxMature dropshipping via API with DroFx.pptx
Mature dropshipping via API with DroFx.pptxolyaivanovalion
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfMarinCaroMartnezBerg
 
{Pooja: 9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...
{Pooja:  9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...{Pooja:  9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...
{Pooja: 9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...Pooja Nehwal
 
Invezz.com - Grow your wealth with trading signals
Invezz.com - Grow your wealth with trading signalsInvezz.com - Grow your wealth with trading signals
Invezz.com - Grow your wealth with trading signalsInvezz1
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxolyaivanovalion
 
BabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptxBabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptxolyaivanovalion
 
Capstone Project on IBM Data Analytics Program
Capstone Project on IBM Data Analytics ProgramCapstone Project on IBM Data Analytics Program
Capstone Project on IBM Data Analytics ProgramMoniSankarHazra
 
Zuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptxZuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptxolyaivanovalion
 
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Delhi Call girls
 
100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptxAnupama Kate
 
Log Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptxLog Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptxJohnnyPlasten
 

Recently uploaded (20)

VidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptxVidaXL dropshipping via API with DroFx.pptx
VidaXL dropshipping via API with DroFx.pptx
 
BPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptx
BPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptxBPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptx
BPAC WITH UFSBI GENERAL PRESENTATION 18_05_2017-1.pptx
 
Data-Analysis for Chicago Crime Data 2023
Data-Analysis for Chicago Crime Data  2023Data-Analysis for Chicago Crime Data  2023
Data-Analysis for Chicago Crime Data 2023
 
Call Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girl
Call Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girlCall Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girl
Call Girls 🫤 Dwarka ➡️ 9711199171 ➡️ Delhi 🫦 Two shot with one girl
 
Edukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFxEdukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFx
 
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
 
Week-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interactionWeek-01-2.ppt BBB human Computer interaction
Week-01-2.ppt BBB human Computer interaction
 
Mature dropshipping via API with DroFx.pptx
Mature dropshipping via API with DroFx.pptxMature dropshipping via API with DroFx.pptx
Mature dropshipping via API with DroFx.pptx
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdf
 
{Pooja: 9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...
{Pooja:  9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...{Pooja:  9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...
{Pooja: 9892124323 } Call Girl in Mumbai | Jas Kaur Rate 4500 Free Hotel Del...
 
Invezz.com - Grow your wealth with trading signals
Invezz.com - Grow your wealth with trading signalsInvezz.com - Grow your wealth with trading signals
Invezz.com - Grow your wealth with trading signals
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptx
 
BabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptxBabyOno dropshipping via API with DroFx.pptx
BabyOno dropshipping via API with DroFx.pptx
 
Capstone Project on IBM Data Analytics Program
Capstone Project on IBM Data Analytics ProgramCapstone Project on IBM Data Analytics Program
Capstone Project on IBM Data Analytics Program
 
Delhi 99530 vip 56974 Genuine Escort Service Call Girls in Kishangarh
Delhi 99530 vip 56974 Genuine Escort Service Call Girls in  KishangarhDelhi 99530 vip 56974 Genuine Escort Service Call Girls in  Kishangarh
Delhi 99530 vip 56974 Genuine Escort Service Call Girls in Kishangarh
 
Abortion pills in Doha Qatar (+966572737505 ! Get Cytotec
Abortion pills in Doha Qatar (+966572737505 ! Get CytotecAbortion pills in Doha Qatar (+966572737505 ! Get Cytotec
Abortion pills in Doha Qatar (+966572737505 ! Get Cytotec
 
Zuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptxZuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptx
 
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
 
100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx
 
Log Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptxLog Analysis using OSSEC sasoasasasas.pptx
Log Analysis using OSSEC sasoasasasas.pptx
 

Up and running with Wikidata

  • 1. Up and running with Wikidata Emw New York City Wikidata workshop 2014-12-14
  • 2. Wikidata is a free linked database that can be read and edited by humans and machines.
  • 3. Wikidata's goals ● Centralize interwiki links ● Centralize infoboxes ● Provide an interface for rich queries ● Structure the sum of all human knowledge
  • 4. What you'll learn from this talk ● How to edit Wikidata ● How to classify ● Ideas for small projects ● Wikidata vocabulary ● Where to find things ● Awesome tools
  • 5. Elements of a Wikidata statement
  • 6. Example: New York City (Q60)
  • 7. Items and properties ● Each item and property has its own page ● Items – Represent subjects: Douglas Adams, Challenger disaster – Have identifiers like Q42, Q921090 – 12,906,291 items ● Properties – Represent attribute names: occupation, has cause – Have identifiers like P106, P828 – 1,329 properties
  • 8. Statements and claims ● Claims – Claims are “triplets” ● Formally: subject, predicate, object ● In Wikidata: item, property, value ● Example: Douglas Adams, occupation, author ● Statements – A claim is only part of a statement – Statements also include: ● References ● Ranks
  • 9. Qualifiers, ranks, references ●Qualifiers – Qualifiers are properties used on claims rather than items – “Yonkers population 12,733 at time (P585) 1860” ●Ranks – Preferred, normal, deprecated – Useful to mark outdated claims ●References – Source of claim; provenance – “... stated in (P248) 1860 United States Census”
  • 10. More on Wikidata vocabulary https://www.wikidata.org/wiki/Wikidata:Glossary
  • 11. Finding Wikidata items Wikipedia articles have a Wikidata item link in the left navigation panel.
  • 12.
  • 13. Finding Wikidata items Wikidata search is quick and effective. Instant search suggests items that have labels or aliases matching your keyword.
  • 15. Search by alias: “flu” -> influenza
  • 16. Finding properties ● Is there a property for “number of windows”? ● What was the ID of that property, again? ● Search – In main site search box, prefix search term with “P:” – “P:number of”, “P:occupation” – Instant search doesn't work for properties, only items ● Browse – https://www.wikidata.org/wiki/Wikidata:List_of_properties ^ bookmark this!
  • 18. Walking through edits for: Yonkers, New York https://www.wikidata.org/wiki/Q128114
  • 19. Yonkers TODO https://www.wikidata.org/wiki/Q128114 ● population (P1082) claims for historical table in https://en.wikipedia.org/wiki/Yonkers,_New_York#Demographics ● Include references! “1860 United States Census”, etc. ● To add to item from inbofox: – head of government (P6), office held by head of government (P1313) – date of foundation or creation (P571) – ZIP code (P281)
  • 20. Area? Population density? ● Properties with units (km^2, people/km^2, $) are not yet possible ● “Units” datatype in development ● https://phabricator.wikimedia.org/T65722
  • 21. Tools – Querying: Autolist, by Magnus Manske ● http://tools.wmflabs.org/autolist/autolist1.html – Batch editing: Widar, by Magnus Manske ● https://tools.wmflabs.org/autolist/ – Software framework: Wikidata Toolkit, by Markus Kroetzsch et al. ● https://www.mediawiki.org/wiki/Wikidata_Toolkit ● https://github.com/Wikidata/Wikidata-Toolkit
  • 22. Querying in Wikidata List of politicians who died of a heart attack Pseudo-query: occupation: politician AND cause of death: heart attack occupation: P106 politician: Q82955 cause of death: P509 heart attack: Q12152 Wikidata query in Autolist: claim[106:82955] AND claim[509:12152]
  • 24. Classification on Wikidata ● Taxonomy of knowledge ● Enables powerful inference, novel applications ● Interesting philosophical, design, and engineering issues
  • 25.
  • 26. Tree of Porphyry User:VoiceOfTheCommons, CC-BY-SA 3.0
  • 27. Classes and instances ● Plato is a human is a animal ● Plato instance of human subclass of animal ● Instance: concrete object, individual ● Class: abstract object
  • 28. Classification on Wikidata ● instance of (P31) – rdf:type in RDF and OWL – 11,930,243 usages – Most popular Wikidata property ● subclass of (P279) – “all instances of A are also instances of B” – rdfs:subClassOf in RDF and OWL – 170,571 usages
  • 29. Examples ● USS Nimitz instance of Nimitz-class aircraft carrier Nimitz-class aircraft carrier subclass of aircraft carrier ● 2012 Cannes Film Festival instance of Cannes Film Festival Cannes Film Festival subclass of film festival ● an individual charm quark instance of charm quark charm quark subclass of quark ^ Many “leaf nodes” in Wikidata's taxonomic hierarchy are not instances. (There are no items about individual quarks on Wikidata!) https://www.wikidata.org/wiki/Help:Basic_membership_properties
  • 30. Bad smells Item has many instance of or subclass of claims Items typically satisfy a huge number of instance of claims: ● Fido instance of dog ● Fido instance of English Pointer ● Fido instance of faithful animal ● … Solution: use one class for instance of, put other class knowledge into normal properties ● Fido instance of dog ● Fido breed: English Pointer ● Fido known for: faithfulness ● ...
  • 31. Bad smells subclass of claim that is nonsensical when interpreted as “All instances of A are also instances of B” Example: dog subclass of pet But not all dogs are pets! feral dog subclass of dog true feral dog subclass of pet false :. dog subclass of pet false Solution: put “pet” knowledge about dogs into claim that does not apply to all instances of dog. E.g. “dog has role pet”. (Has role would not be transitive. Also needed: some/all quantifier.)
  • 32. Classification on Wikidata ● Last but not least: part of (P361) – Third basic membership property – Top-level “part-whole” relation ● Instance of, subclass of and part of are all transitive ● Transitive relation: A subclass of B B subclass of C :. A subclass of C https://www.wikidata.org/wiki/Help:Basic_membership_properties
  • 33. Ideas for small projects ● Add data about towns and cities – population (P1082) – head of government (P6) ● Add medical knowledge about historical figures – medical condition (P1050) – cause of death (P509) – manner of death (P1196) ● Add cultural knowledge about works of art – instance of (P31) – creator (P170) – material used (P186) – collection (P195)