Digital Humanities in a Linked Data World - Semnantic Annotations
Guest Lecture: Linked Open Data for the Humanities and Social Sciences
-
Upload
laura-hollink -
Category
Technology
-
view
149 -
download
0
Transcript of Guest Lecture: Linked Open Data for the Humanities and Social Sciences
Linked Open Data for the Humanities and Social Sciences
Use cases: linking government data to news data in the PoliMedia and Talk of Europe projects
Laura HollinkCentrum Wiskunde & Informatica (CWI)
KU LeuvenGuest lecture November 10, 2016
Linked Open Data in the SSH?
Example question:
How did the debate about the financial crisis in Greece develop?
Searching the proceedings of the European Parliament
"Greece" in the plenary meetings of the European Parliament
Year
Nr.
of m
entio
ns
050
100
150
200
1999 2000 2001 2001 2002 2003 2004 2005 2006 2006 2007 2008 2009 2010 2010 2011 2012 2013
Search volumes of a search engine
Frequency of the query “Greece” on Google
http://www.google.com/trends
Search volumes of a search engine
Frequency of the query “Greece” on Google
http://www.google.com/trends
We need:
✦open access to data ✦to combine sources ✦more complex queries
Linked Open Data in the SSH?
Example question:
Which political debate in the post-war period has attracted most media attention?
“De Indonesische Quaestie"
To answer this question we need to go through all newspaper articles about all political debates…
“De Indonesische Quaestie"
To answer this question we need to go through all newspaper articles about all political debates…
We need:
✦open access to data ✦to combine sources ✦more complex queries
Linked Open Data in the SSH?
Example question:
What are the differences between different media?
Example question:
Has the coverage changed over time?
A method of publishing structured data on the Web in such a way that it can be linked and queried by computers as well as people.
A very brief introduction…
✦open access to data ✦to combine sources ✦more complex queries
Linked Open Data
A method of publishing structured data on the Web in such a way that it can be linked and queried by computers as well as people.
A very brief introduction…
✦open access to data ✦to combine sources ✦more complex queries
Linked Open Data
Thing Type Population Airport
Amsterdam City 1364422 Schiphol
…. … …. …
Structured data
ex:Amsterdam a ex:City . ex:Amsterdam dbo:populationUrban "1330235"^^xsd:integer . ex:Amsterdam dbp:cityServed ex:Schiphol .
Comparable to the data one may find in a database table
Represented as RDF triples
On the WebEverything is identified by URIs (documents, concepts, instances, links)http://example.org/cities#Amsterdam http://example.org/City http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dbpedia.org/ontology/population
On the Web
Triples can be distributed over the Web
Everything is identified by URIs (documents, concepts, instances, links)http://example.org/cities#Amsterdam http://example.org/City http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dbpedia.org/ontology/population
http://example.org/cities#Amsterdam a ex:City.
http://example.org/cities#Amsterdam dbo:populationUrban "1364422"
http://example.org/cities#Amsterdam dbp:cityServed ex:Schiphol
On the Web
Amsterdamhas population
“1364422” City Schiphol
is a has airport
Triples can be distributed over the Web
Everything is identified by URIs (documents, concepts, instances, links)http://example.org/cities#Amsterdam http://example.org/City http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dbpedia.org/ontology/population
http://example.org/cities#Amsterdam a ex:City.
http://example.org/cities#Amsterdam dbo:populationUrban "1364422"
http://example.org/cities#Amsterdam dbp:cityServed ex:Schiphol
Forming a graph
The Web of Data vs. the Web of Documents
Note the differences Web of Data <-> database:• Non-unique naming assumption• Open World assumption• Everyone can say anything about anything
Querying Linked Open Data
• A W3C recommendation for querying RDF graphs called “SPARQL Protocol And RDF Query Language”
• See http://www.w3.org/TR/rdf-sparql-query/ or http://www.w3.org/TR/sparql11-query/
:JamesDean ?what :Giant.
?who :playedIn :Giant.
:JamesDean :playedIn ?what .
:JamesDean :playedIn :Giant .
:Giant
:JamesDean
:playedIn
Data
Query Result
Two example projects of Linked Open Data in SSH: data modelling and linking in the PoliMedia and
Talk of Europe projects
Transcriptions of all 9,294 meetings of the Dutch parliament between 1945-1995, consisting of 1,208,903 speeches.
Roughly 1.8 Million news bulletins between 1937-1984
(We only use 1945-1995)
Archives of hundreds of newspaper with tons of newspaper issues or 10’s of Millions of articles between 1618-1995.
(We only use 1945-1995)
Step 1: Translate the Dutch parliamentary debates to the standard structured web format RDF
nl.proc.sgd.d.194519460000002
nl.proc.sgd.d.194519460000002.1
PartOfDebateDebate
http://resolver.politicalmashup.nl/nl.proc.sgd.d.194519460000002
http://statengeneraaldigitaal.nl/
http://resolver.kb.nl/resolve?urn=sgd:mpeg21:19451946:0000002:pdf
nl.proc.sgd.d.19720000002
Handelingen Verenigde Vergadering...
Dutch
1945-11-20rdf:type
dc:id
dc:source
dc:source
dc:publisher
dc:language
dc:date
hasPart
rdf:type
nl.proc.sgd.d.194519460000002.1.1hasPart
DebateContext
rdf:type
nl.proc.sgd.d.194519460000002.1.2
Speech
rdf:type
hasPart
nl.proc.sgd.d.194519460000002.1.3
hasSubsequentSpeech
"Mijnheer de Voorzitter, de Commissie van …"
hasSpokenText
sem:hasActorSpeaker_0006
4
Party_kvp
hasParty
hasSpeaker
member_of _parliament
"De voorzitter opent de vergadering…"
hasText
http://resolver.kb.nl/resolve?urn=ddd:011198136:mpeg21:a0525:ocr
coveredIn
Party
KVP
Katholieke Volkspartijrdf:type
hasAcronym
hasFullName
Joannes Antonius James
Bargefoaf:firstName
foaf:lastName
Bargerdfs:label
http://resolver.politicalmashup.nl/nl.m.00064
dc:source
Politician
rdf:typehasRole
nl.proc.sgd.d.194519460000002.2
hasSubsequentPartOfDebate
Step 2: Discovering links between politics and news
Detect topics in
speeches
Create queries
Search newspaper
archive
Topics
Named Entities
Name of speaker
Detect Named
Entities in speeches
Candidate articles
Queries
Rank candidate
articles
Links between speeches
and articles
Debates
Date of debate
Step 2: Discovering links between politics and news
Detect topics in
speeches
Create queries
Search newspaper
archive
Topics
Named Entities
Name of speaker
Detect Named
Entities in speeches
Candidate articles
Queries
Rank candidate
articles
Links between speeches
and articles
Debates
Date of debate
Intuition 1: The name of the speaker should appear in the article and the article should be published within a week of the debate
Step 2: Discovering links between politics and news
Detect topics in
speeches
Create queries
Search newspaper
archive
Topics
Named Entities
Name of speaker
Detect Named
Entities in speeches
Candidate articles
Queries
Rank candidate
articles
Links between speeches
and articles
Debates
Date of debate
Intuition 1: The name of the speaker should appear in the article and the article should be published within a week of the debate
Intuition 2: the more the article and the speech overlap in terms of topics and named entities, the more they are related.
Representation of links
architecten
architects
Link 001
skos:exactMatch
handmatigL. Hollink
concept1
concept2
link type
link methodeauteur
architecten architectsskos:exactMatch
Representation of links
architecten
architects
Link 001
skos:exactMatch
handmatigL. Hollink
concept1
concept2
link type
link methodeauteur
architecten architectsskos:exactMatch
• This is an example of the“design pattern” referred to as n-ary relations or relations as classes.
• It allows us to save provenance information about the statements we create.
Evaluation of Links
Recall that we aim to use the links to answer a research question.
Can we still do that if there are errors in the links?
How many errors are acceptable?
We need to know the quality!
Evaluation of Links
How would you determine the quality of the links?
Recall that we aim to use the links to answer a research question.
Can we still do that if there are errors in the links?
How many errors are acceptable?
We need to know the quality!
Evaluation of Links
How would you determine the quality of the links?
1. Manually rating (a sample of) mappings
• relatively cheap and easy to interpret
• only precision, no recall
Recall that we aim to use the links to answer a research question.
Can we still do that if there are errors in the links?
How many errors are acceptable?
We need to know the quality!
Evaluation of Links
How would you determine the quality of the links?
1. Manually rating (a sample of) mappings
• relatively cheap and easy to interpret
• only precision, no recall
2. Comparison to manually found links
• precision and recall
• more expensive! (but: crowd sourcing?)
Recall that we aim to use the links to answer a research question.
Can we still do that if there are errors in the links?
How many errors are acceptable?
We need to know the quality!
Evaluation of links in PoliMedia
How good are the links?
• We ask 2 raters to manually score pairs of newspaper articles and speeches.
• a pilot study showed that we needed more than a 2 point scale.
• inter-rater agreement: 0.5 -> acceptable, but not high.
• Score: 80%
Evaluation of links in PoliMedia
Score Setting 1 Setting 2 Setting 3
I don’t know 0,14 0,15 0,08
0 - unrelated 0,38 0,23 0,12
1- related 0,29 0,36 0,36
2- explicit mention of the debate 0,19 0,26 0,44
1+2 0,48 0,62 0,8
How good are the links?
• We ask 2 raters to manually score pairs of newspaper articles and speeches.
• a pilot study showed that we needed more than a 2 point scale.
• inter-rater agreement: 0.5 -> acceptable, but not high.
• Score: 80%
Evaluation of links in PoliMedia
Score Setting 1 Setting 2 Setting 3
I don’t know 0,14 0,15 0,08
0 - unrelated 0,38 0,23 0,12
1- related 0,29 0,36 0,36
2- explicit mention of the debate 0,19 0,26 0,44
1+2 0,48 0,62 0,8
How many links did we miss?
• We ask the raters to manually search the archives of the National Library for related articles.
• Score: 62%
How good are the links?
• We ask 2 raters to manually score pairs of newspaper articles and speeches.
• a pilot study showed that we needed more than a 2 point scale.
• inter-rater agreement: 0.5 -> acceptable, but not high.
• Score: 80%
Results
• An open data set of Dutch parliamentary debates,
• with almost 3 Million links between 450.000 speeches and 1.5 Million news paper articles and radio bulletins at the National Library.
• accessible though a Web demonstrator and through a Sparql Enpoint
Online database: SPARQL endpoint
• A service to query a knowledge base using the SPARQL query language.
“All speeches with more than 60 associated news items.”
The European Parliament as Linked Open Data
Laura Hollink Centrum Wiskunde & Informatica, Amsterdam Astrid van Aggelen VU University Amsterdam Martijn Kleppe Erasmus University Rotterdam Henri Beunders Erasmus University Rotterdam Jill Briggeman Erasmus University Rotterdam Max Kemman University of Luxembourg
Talk of Europe goals
• To publish the entire plenary debates of the European Parliament as Linked Open Data
• To improve access to the data• To enable large scale analysis across time spans.‣ To residents of the European Union access to the proceedings
of the European parliament is a formal right.
14M RDF statements about the 30K speeches in 23 languages by 3K speakers in 1K session days that were held in the EU parliament between 1999 and 2014
Step 1: Translate the European parliamentary debates to Linked Open Data
Modelling debates as events, not documents
• `
lpv:number
lpv:month
lpv:year
rdf:type
lp:eu/plenary/SessionDay/2013-11-20
lp:eu/plenary/2013-11-20/AgendaItem_6
lp:eu/plenary/2013-11-20/Speech_103
lp:eu/plenary/Session/2013-11
"2013-11-20"^xsd:date
"11"^xsd:gMonth
"2013"^xsd:gYear
lp:eu/plenary/2013-11-20/AgendaItem_7
lp:eu/plenary/2013-11-20/Speech_104
lpv:hasSubsequent
lpv:hasSubsequent
dc:date
dc:date
dc:date
103^xsd:integer
6^xsd:integer lpv:number
dc:hasPart dc:isPartOf
dc:hasPart dc:isPartOf
dc:isPartOfdc:hasPart
lpv:eu/plenary/Speech
lpv:eu/plenary/AgendaItem
lpv:eu/plenary/SessionDay
lpv:eu/plenary/Sessionrdf:type
rdf:type
rdf:type
PREFIX lpv: <http://purl.org/linkedpolitics/vocabulary/> PREFIX lp: <http://purl.org/linkedpolitics/> PREFIX dc: <http://purl.org/dc/elements/1.1/> PREFIX foaf: <http://xmlns.com/foaf/0.1/>
How to relate a speech the party of the speaker?
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUParty/SomeParty
lpv:hasParty
How to relate a speech the party of the speaker?
Why is this not a good solution?
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUParty/SomeParty
lpv:hasParty
How to relate a speech the party of the speaker?
Why is this not a good solution?
1. A person might be a member of more than one party (at different times)
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUParty/SomeParty
lpv:hasParty
How to relate a speech the party of the speaker?
Why is this not a good solution?
1. A person might be a member of more than one party (at different times)
2. Since there is no link between a speech and a party, queries for all speeches spoken by the members of a certain party become very complicated.
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUParty/SomeParty
lpv:hasParty
How to relate a speech to the party of the speaker?
"20111126"^ xsd:date
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelpv:political
Function
lpv:institution
lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
How to relate a speech to the party of the speaker?
"20111126"^ xsd:date
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelpv:political
Function
lpv:institution
lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
"20111126"^ xsd:datelp:political-Function101
lpv:end"20111126"^ xsd:date
lpv:beginning
"20071114"^xsd:date
lpv:PoliticalFunction
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023
lp:politicalFunction
lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelp:Role/member
lp:EUParty/NI
lpv:rolelpv:political
Function
lpv:institutionlpv:institution rdf:type
lpv:speaker
rdf:type
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
How to relate a speech to the party of the speaker?
"20111126"^ xsd:date
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelpv:political
Function
lpv:institution
lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
"20111126"^ xsd:datelp:political-Function101
lpv:end"20111126"^ xsd:date
lpv:beginning
"20071114"^xsd:date
lpv:PoliticalFunction
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023
lp:politicalFunction
lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelp:Role/member
lp:EUParty/NI
lpv:rolelpv:political
Function
lpv:institutionlpv:institution rdf:type
lpv:speaker
rdf:type
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
"20111126"^ xsd:datelp:political-Function101
lpv:end"20111126"^ xsd:date
lpv:beginning
"20071114"^xsd:date
lpv:PoliticalFunction
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023
lp:politicalFunction
lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelp:Role/member
lp:EUParty/NI
lpv:rolelpv:political
Function
lpv:institutionlpv:institution rdf:type
lpv:spokenAs
lpv:speaker
lpv:spokenAs
rdf:type
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
How to relate a speech to the party of the speaker?
"20111126"^ xsd:date
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelpv:political
Function
lpv:institution
lpv:speaker
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
"20111126"^ xsd:datelp:political-Function101
lpv:end"20111126"^ xsd:date
lpv:beginning
"20071114"^xsd:date
lpv:PoliticalFunction
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023
lp:politicalFunction
lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelp:Role/member
lp:EUParty/NI
lpv:rolelpv:political
Function
lpv:institutionlpv:institution rdf:type
lpv:speaker
rdf:type
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
"20111126"^ xsd:datelp:political-Function101
lpv:end"20111126"^ xsd:date
lpv:beginning
"20071114"^xsd:date
lpv:PoliticalFunction
"20090716"^ xsd:date
lp:political-Function102
lpv:beginning
lpv:end
lp:EUmember_1023
lp:politicalFunction
lp:eu/plenary/2009-10-21/Speech_140>
lpv:role
lp:EUCommittee/Committee_on_Legal_Affairs
lp:Role/substitutelp:Role/member
lp:EUParty/NI
lpv:rolelpv:political
Function
lpv:institutionlpv:institution rdf:type
lpv:spokenAs
lpv:speaker
lpv:spokenAs
rdf:type
lp:EUmember_1023lp:eu/plenary/2009-10-21/Speech_140>lpv:speaker
lp:EUparty_NI
lpv:party
Note: this is another example of the design pattern called n-ary relations or relations as classes.
Linking Members of Parliament to Wikipedia / DBpedia
• String matching is the most important feature in the linking process.
• “nearly all [alignment systems] use a string similarity metric” [12]
• stopping and stemming is not helpful! Nor is using WordNet synonyms. [12]
[12] Cheatham, M., & Hitzler, P. String similarity metrics for ontology alignment. ISWC 2013.
http://www.dbpedia.org/page/Judith_Sargentini
Example query 1: speeches that contain a certain keyword
Query: all speeches that contain the phrase “open data”
…. So let us go for open data, let us go for utilisation of all the instruments available to that end! …..
…. but there too governments are encouraging the use of open data to increase transparency, accountability and citizen participation ….
…. We already have many open data projects in the Member States and local authorities…..
Example 2: speeches that contain a certain keyword by date
"Slovenia" in the plenary meetings of the European Parliament
Year
Nr.
of m
entio
ns
020
4060
80100
1999 2000 2001 2003 2004 2005 2006 2007 2008 2010 2011 2012 2013
Example 2: speeches that contain a certain keyword by date
"Slovenia" in the plenary meetings of the European Parliament
Year
Nr.
of m
entio
ns
020
4060
80100
1999 2000 2001 2003 2004 2005 2006 2007 2008 2010 2011 2012 2013
Example 2: speeches that contain a certain keyword by date
Mentions of 'human rights'
dates
Frequency
0200
400
600
800
1999 2000 2001 2003 2004 2005 2006 2007 2009 2010 2011 2012 2013
Example 3: speeches that contain a certain keyword by country
AT BE BG CY CZ DE DK EE ES FI FR GB GR HR HU IE IT LT LU LV MT NL PL PT RO SE SI SK
Mentions of 'human rights' by country
01000
2000
3000
4000
5000
6000
7000
Example 4: the number of speeches per EU country
SELECT ?c (COUNT(?c) as ?count)
WHERE {
?x rdf:type <http://purl.org/linkedpolitics/vocabulary/eu/plenary/Speech>.
?x <http://purl.org/linkedpolitics/vocabulary#speaker> ?p.
?p <http://purl.org/linkedpolitics/vocabulary#countryOfRepresentation> ?c
} GROUP BY ?c LIMIT 50
Example 5: include data external sourceQuery: MEPs that were born outside Europe.
Members of Parliament
(DBpedia contains info on birthplace, birth date, schools, careers, residence, family, etc. )
Example 5: include data external sourceQuery: MEPs that were born outside Europe.
Members of Parliament
(DBpedia contains info on birthplace, birth date, schools, careers, residence, family, etc. )
Intermezzo: one-question Quiz Reasoning on the Web of Data
Question: What can we conclude from this graph?A. Stihler is a member of exactly 3 partiesB. Stihler is a member of at least 3 partiesC. Stihler is a member of at most 3 partiesD. None of the aboveE. All of the aboveF. Other, namely ….
http://purl.org/linkedpolitics/EUmember_4545 "Catherine Stihler"foaf:name
http://purl.org/linkedpolitics/EUParty/PES http://dbpedia.org/resource/Party_of_European_Socialists
http://dbpedia.org/resource/Progressive_Alliance_of_Socialists_and_Democrats
:memberOf:memberOf
:memberOf
Results
• An open data set of EU parliamentary debates,
• with links to other sources on the Web of Data
• accessible though a through a Sparql Enpoint
Reflection: to what extent can we now answer these questions?
How did the debate about the financial crisis in Greece develop?
Which political event has attracted most media attention?
What are the differences between different media?
Has the coverage changed over time?
Reflection: to what extent can we now answer these questions?
How did the debate about the financial crisis in Greece develop?
Which political event has attracted most media attention?
What are the differences between different media?
Has the coverage changed over time?
We can, but:• what is the influence of the selection of newspapers
available at the National Library?• what was the quality of the digitisation process (OCR)?• How good is our linking approach (based on
automatically detected entities and topics)?• How much can we trust the quality of external sources?
➡ How to handle these uncertainties is one of our research questions. We call this Tool Criticism
Research directions at CWI
Transparent, reproducible analysis of large volumes of connected, heterogenous, multimodal data. 1. How do we automatically link heterogeneous datasets?
2. How do we interpret links between datasets of different quality and certainty?
3. How do we handle the fact that knowledge evolves?
4. How do we design interfaces that allow scholars to study the datasets
• including the links between them?
• while assessing the reliability of the findings?
Research directions at CWI
Transparent, reproducible analysis of large volumes of connected, heterogenous, multimodal data. 1. How do we automatically link heterogeneous datasets?
2. How do we interpret links between datasets of different quality and certainty?
3. How do we handle the fact that knowledge evolves?
4. How do we design interfaces that allow scholars to study the datasets
• including the links between them?
• while assessing the reliability of the findings?
Data Science - Big Data - Web of Data
PoliMedia demo: http://polimedia.nl/ PoliMedia project video: https://youtu.be/u24oRCj7xrQ
Talk of Europe project: http://talkofeurope.eu/ Talk of Europe data: purl.org/linkedpolitics Talk of Europe project video: https://youtu.be/GxA53gkCe0o
My website: http://homepages.cwi.nl/~hollink/
A. van Aggelen, L. Hollink, M. Kemman, M. Kleppe & H. Beunders. The debates of the European Parliament as Linked Open Data. Semantic Web Journal. In press, 2016.
M. Kleppe, L. Hollink, J. Oomen, M. Kenman, D. Juric, J. Blom, H. Beunders. PoliMedia - Improving the Analyses of Radio & Newspaper coverage of Political Debates. First prize winner of the LinkedUp Veni Competition, presented at the Open Knowledge Conference (OKCon), Geneva, September 2013..
I’d be happy to answer any questions!