A Non-Technical, Example-Driven Introduction to Linked Data
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Transcript of A Non-Technical, Example-Driven Introduction to Linked Data
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
HOW LINKED DATA AND SEMANTIC WEB
TECHNOLOGIES FOSTER THE
PUBLICATION, RETRIEVAL, REUSE, AND
INTEGRATION OF DATA
A NON-TECHNICAL, EXAMPLE-DRIVEN INTRODUCTION
Krzysztof Janowicz, Grant McKenzie, and Yingjie HuSTKO Lab
University of California, Santa Barbara, USA
UCSB Library, April 2014
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
WHAT IS LINKED DATA?
LINKING DATA AS NEXT-GENERATION INFRASTRUCTURE
Data SilosWeb servicesDatabasesWeb pages
hinder ad-hoc combinationenforce data modelslimit re-usability
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
FROM DOCUMENTS TO DATA
FROM LINKED DOCUMENTS TO LINKED DATA
Use Uniform Resource Identifiers (URI) to identify entities, link them to otherentities, encode information about these entities using themachine-understandable RDF, and make them available on the Web.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
FROM DOCUMENTS TO DATA
BERNERS-LEE’S LINKED DATA PRINCIPLES AND STARS
Four Rules for Linked DataUse URIs as names for things
Use HTTP URIs so that people can look up those names.
When someone looks up a URI, provide useful information, using the standards(RDF*, SPARQL)
Include links to other URIs. so that they can discover more things.
Is your Linked Open Data 5 Star?? Available on the web (whatever format) but with an open licence, to be Open Data
?? Available as machine-readable structured data (e.g. excel instead of imagescan of a table)
? ? ? as (2) plus non-proprietary format (e.g. CSV instead of excel)
? ? ?? All the above plus, Use open standards from W3C (RDF and SPARQL) toidentify things, so that people can point at your stuff
? ? ? ? ? All the above, plus: Link your data to other people’s data to providecontext
See http://www.w3.org/DesignIssues/LinkedData.html
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
EXPLORING LINKED DATA
EXPLORING LINKED DATA RELATED TO SANTA BARBARA
Follow-your-nose: Explore information related to Santa Barbara usingLinked Data (DBpedia).
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
EXPLORING LINKED DATA
FINDING RELATIONS BETWEEN PLACES
Finding Relations between places (via people, events, objects,...).
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
EXPLORING LINKED DATA
REASONATOR:BROWSE WIKIDATA
’Wikidata is afree knowledgebase that can beread and editedby humans andmachines alike.’
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
EXPLORING LINKED DATA
SEARCHING THE WEB OF DOCUMENTS
This is still how most (Web) search works today. 20 million results, no hit.AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
EXPLORING LINKED DATA
SEARCHING THE WEB OF (LINKED) DATA
Populated places have a population, are located, occupy a certain area,...AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
EXPLORING LINKED DATA
GOOGLE’S KNOWLEDGE GRAPH
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
EXPLORING LINKED DATA
GOOGLE’S KNOWLEDGE GRAPH
Google’s Web search is changing towards query answering.AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
QUERYING AND INTEGRATION OF LINKED DATA
THE GLOBAL GRAPH OF LINKED DATA
The examples before involved only one data set, but there is much more...AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
QUERYING AND INTEGRATION OF LINKED DATA
THE GLOBAL GRAPH OF LINKED DATA
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
QUERYING AND INTEGRATION OF LINKED DATA
INTEGRATION AND QUERY FEDERATION
Integration by searching equivalent classes or/and same featuresin data sets. This requires ontology matching and alignment.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
ONTOLOGIES IN COMPUTER/INFORMATION SCIENCE
ONTOLOGIES IN COMPUTER/INFORMATION SCIENCE
An ontology is an explicit specification of a conceptualization used
to achieve a shared understanding of a particular domain of interest. (adopted from Gruber (1993))
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
ENTITIES, CONCEPTS AND CATEGORIES
ENTITIES, CONCEPTS AND CATEGORIES
An entity is an individual (real world) object.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
ENTITIES, CONCEPTS AND CATEGORIES
ENTITIES, CONCEPTS AND CATEGORIES
A concept/class is a (mental) template used for grouping entities.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
ENTITIES, CONCEPTS AND CATEGORIES
ENTITIES, CONCEPTS AND CATEGORIES
A category is the set of entities grouped using a particular concept.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
SUBSUMPTION AND SIMILARITY
SUBSUMPTION
Concepts can be organized within hierarchical structures.[this subClassOf relation is transitive]
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
SUBSUMPTION AND SIMILARITY
SIMILARITY
Some concepts (and entities) are more similar than others.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
ONTOLOGY LANGUAGES
UNDER THE HOOD OF A MAP LEGEND ONTOLOGY
NC = {LegendItem,Symbol ,Label ,FeatureType} (1)NR = {consistsOf , isLabelFor , isLabelOf ,SymbolizedBy} (2)
> v ¬∃N.> (3)
LegendItem v ∃consistsOf .Symbol t ∃consistsOf .LegendItem (4)
Label v ∃SymbolizedBy .Symbol u ∀SymbolizedBy .Symbol (5)> v≤ 1isLabelFor.> (6)> v≤ 1isLabelOf.> (7)
> v≤ 1SymbolizedBy.> (8)Label v ∃isLabelFor .FeatureType (9)
Label u Symbol v ⊥ (also for Symbol, Label, FeatureType, LegendItem) (10)SymbolizedBy− ◦ isLabelFor v depictedBy− (11)
¬∃consistsOf− v Legend (12). . . (13)
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
SEMANTIC INTEROPERABILITY
WHY NOT JUST STANDARDIZE MEANING? (CITY OR TOWN?)
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
SEMANTIC INTEROPERABILITY
WHY NOT JUST STANDARDIZE MEANING? (CITY OR TOWN?)
California:City ≡ Town
Utah:Town ≡< (population,1000)
Pennsylvania:Town ≡ {Bloomsburg}
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
SEMANTIC INTEROPERABILITY
SEMANTIC INTEROPERABILITY – MEANINGFUL LINKS
Unfortunately, our data sources useexactly the same terminology (e.g.,connection) to talk about totally differentand contradicting facts (e.g., separation)
While we can still syntactically integrateand reuse information, the results may bemisleading or even meaningless
We need heterogeneity preserving semantic interoperability methods
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
SEMANTIC INTEROPERABILITY
SEMANTIC INTEROPERABILITY – MEANINGFUL LINKS
Unfortunately, our data sources useexactly the same terminology (e.g.,connection) to talk about totally differentand contradicting facts (e.g., separation)
While we can still syntactically integrateand reuse information, the results may bemisleading or even meaningless
We need heterogeneity preserving semantic interoperability methods
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND VOCABULARIES
ONTOLOGIES TO MAKE YOUR DATA MORE USABLE
Five Stars of Linked Data Vocabulary Use© Linked Data without any vocabulary.
? There is dereferencable human-readable information about the usedvocabulary.
?? The information is available as machine-readable explicitaxiomatization of the vocabulary.
? ? ? The vocabulary is linked to other vocabularies
? ? ?? Metadata about the vocabulary is available (in a dereferencableand machine-readable form).
? ? ? ? ? The vocabulary is linked to by other vocabularies.
See http://semantic-web-journal.net/content/
five-stars-linked-data-vocabulary-use
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND MAPS
A TINY ONTOLOGY FOR ESRI’S ARCGIS ONLINE
This fragment of the ontology developed for ArcGIS Online definesthe relations (e.g., isOwnerOf) between items (e.g., map services),users, and user groups.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND MAPS
WHICH BASEMAP IS MOST POPULAR (BASED ON VIEWS)?
SELECT DISTINCT ?baseMap ?numViewsWHERE { ?baseMap arcgis:isBaseMapOf ?item .
?baseMap arcgis:numViews ?numViews }ORDER BY DESC(?numViews) LIMIT 10
Listing 1: SPARQL query for most popular maps based on views.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND MAPS
WHICH BASEMAP IS MOST POPULAR (BASED ON USAGE)?
SELECT ?baseMap (count(distinct ?item) as ?usedTimes)WHERE { ?baseMap arcgis:isBaseMapOf ?item }GROUP BY ?baseMapORDER BY DESC(?usedTimes) LIMIT 10
Listing 2: SPARQL query for most popular maps based on usage.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND MAPS
LINKED DATA PORTAL FOR ARCGIS ONLINE (DEMO)
Semantics-enabled and Linked Data-driven similarity search interface for ArcGIS Online.
http://stko-exp.geog.ucsb.edu/linkedarcgis/
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND GAZETTEERS
USCB’S ALEXANDRIA DIGITAL LIBRARY GAZETTEER (2006)
Interface of the original Alexandria Digital Library Gazetteer.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND GAZETTEERS
ONTOLOGY-POWERED, LINKED DATA-DRIVEN ADL GAZETTEER (DEMO)
5 Million places merged from multiple authoritative data sources. Containsmultiple alternative (e.g., historic) names, provenance information, 1200geographic feature classes, polygon data, GeoSPARQL endpoint, etc.[Still a lot of work to be done].
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND GAZETTEERS
WHY NOT JUST USE GEONAMES?
A SPARQL query for people living near the Gulf of Guinea will return about 7billion! See http://stko.geog.ucsb.edu/location_linked_data for more examples.
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND SCIENTOMETRICS
DEKDIV: EXPLORING BIBLIOGRAPHIC LINKED DATA (DEMO)
System: http://stko-exp.geog.ucsb.edu/lak/; paper: http://bit.ly/1dW2NER
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU
LINKED DATA ONTOLOGIES APPLICATIONS (AT STKO)
LINKED DATA AND SCIENTOMETRICS
SEMANTIC WEB JOURNAL: LINKED SCIENTOMETRICS
System: http://semantic-web-journal.com/SWJPortal/;
paper: http://bit.ly/1ilwbRU
AN EXAMPLE-DRIVEN INTRODUCTION TO LINKED DATA JANOWICZ, MCKENZIE, AND HU