source: main/trunk/model-sites-dev/eurovision-lod/collect/eurovision/transform/pages/about.xsl@ 35093

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE videocollection [
  <!ENTITY ndash "&#8211;">
  <!ENTITY mdash "&#8212;">
]>
<xsl:stylesheet version="1.0"
    xmlns:xsl="http://www.w3.org/1999/XSL/Transform"
    xmlns:java="http://xml.apache.org/xslt/java"
    xmlns:util="xalan://org.greenstone.gsdl3.util.XSLTUtil"
    xmlns:gslib="http://www.greenstone.org/skinning"
    xmlns:gsf="http://www.greenstone.org/greenstone3/schema/ConfigFormat"   
    extension-element-prefixes="java util"
    exclude-result-prefixes="java util">


  <xsl:template name="coll-description">
    <gsf:style src="sites/{$site_name}/collect/{$collName}/css/eurovision.css"/>    
    <gsf:script src="sites/{$site_name}/collect/{$collName}/js/jquery.show-more.js"/>

    
      <div id="about-desc">
      <h2>Introduction</h2>
      <!--
      <p style="padding-bottom: 10px;">
        The <a href="https://eurovision.tv">Eurovision Song
        Contest</a> is a live-broadcast televised event that
        was first held in 1956 featuring artists singing original songs from
        7 countries.  Since then it has grown into an event involving
        over 40 countries, and streamed all around the world. ...
        
      </p>
      -->
      
      <p style="padding-bottom: 10px;">
        <i style="padding-right:6px;">A help to shore up a post war Europe in 1956 it
        all began, where there were only seven countries and one
        camera man!</i>
      </p>
      <p>
        The <a href="https://eurovision.tv">Eurovision Song
        Contest</a> is a long-running, live-broadcast televised multi-national
        competition with a collaborative mission, not dissimilar
        in spirit to the Olympics.
        The contest has grown significantly from
        that modest start with 7 countries (and one cameraman),
        with over 40 countries competing these days—Australia
        even takes part now, through a specially
        arranged invitation. It's an annual celebration of
        European culture and the highlight of many people's
        year.
      </p>

      <div id="about-show-more">
        <p>     
          At Eurovision there is no division because wherever
          you come from Eurovision is home. The Eurovision song
          contest is widely known as a safe space for LGBTQIA+
          people and a platform for free expression. For example
          trans-woman
          <a href="https://en.wikipedia.org/wiki/Dana_International">Dana International</a>
          won as far back as 1998.
          There have been songs in many different languages over the
          years, although most are in English these days. This
          doesn't matter, however, because music is a language we all
          know how to speak.
        </p>
        <p>     
          In its latest incarnation, after
          all the performances are over, artists wait
          nervously as via live television link-ups the show's hosts visit each
          of the 40+ countries in turn collecting all points cast
          by the country appointed juries.  This includes
          the all important top score that can be cast, 12 points
          (douze points!), a double-increment up from the
          10 points awarded to the song a country ranks second,
          followed by 8, 7, 6 
 1 points awarded.
          With over 20 countries competing in a final, this means
          that not all performers gets points from that country.
          Next comes the &quot;the popular vote&quot;
          where fans, still grouped by country, have
          the votes they cast by phone, SMS or the Eurovision app
          tallied and mapped into the same format of 12 points for 1st
          place, and so on.
          This all culminates in a new winner being crowned, with
          the competition typically being hosted the following year
          in that country. 
        </p>
      </div>
      <gsf:script>
        $('#about-show-more').showMore({
            minheight: 0,
        buttontxtmore:"show more ...",
        buttontxtless:"... show less"
          });
      </gsf:script>

      
      <h2>Features of this Website</h2>

      <p>       
        This (unofficial) website has been developed by a small
        team of dedicated Digital Library researchers who also
        happen to be <i>huge</i> fans of Eurovision.  We wish to
        share our love for the competition, and at the same time
        demonstrate what is possible when—harnessing some of that
        passion!—the techniques of
        <a href="https://en.wikipedia.org/wiki/Linked_data">Linked
        Open Data</a> are applied
        to the Open Source
        <a href="https://www.greenstone.org">Greenstone3</a>
        Digital Library platform.  For the technically interested
        see the
        <a href="{$library_name}/collection/{$collName}/page/about#it-all-started-with">
          <i style="padding-right: 6px;">It All Started with a Little <strike>Sparkle</strike>SPARQL</i></a>
          below for details about how the digital library was formed.
      </p>

      <!--
      <p>
        For those who want to jump right in and access information about, as well as see and hear some of the past performances,
        we suggest you
        start by exploring the assembled information through
        the browsing tabs, such as
        <a href="{$library_name}/collection/{$collName}/browse/CL3">browse by countries</a>
        if you want (for instance) to reminisce about songs your country have entered in the past, or
        <a href="{$library_name}/collection/{$collName}/browse/CL4">browse by years</a> if
        you are curious about who were the countries competing in that inaugural year of 1956.
        Alternatively, use the quick-search box to query the DL collection for a term that you sparks
        interest, such as
        <a href="{$library_name}/collection/{$collName}/search/TextQuery?qs=1&amp;rt=rd&amp;s1.level=Doc&amp;startPage=1&amp;s1.query=love&amp;s1.index=ZZ">love</a>
        and
        <a href="{$library_name}/collection/{$collName}/search/TextQuery?qs=1&amp;rt=rd&amp;s1.level=Doc&amp;startPage=1&amp;s1.query=amore&amp;s1.index=ZZ">amore</a>,
        or maybe something more frivolous such as
        <a href="{$library_name}/collection/{$collName}/search/TextQuery?qs=1&amp;rt=rd&amp;s1.level=Doc&amp;startPage=1&amp;s1.query=la&amp;s1.index=ZZ">la</a>.
        
      </p>
-->

      <p>
        For those who want to jump right in and access information about, as well as see and hear some of the past performances,
        we suggest you
        start by exploring the assembled information through
        the browsing tabs.  For example:
        <ul>
          <li><a href="{$library_name}/collection/{$collName}/browse/CL3">Browse by countries</a>
          if you want (for instance) to reminisce about songs your country have entered in the past; or</li>
          <li><a href="{$library_name}/collection/{$collName}/browse/CL4">Browse by years</a> if
          you are curious about who were the countries competing in that inaugural year of 1956.</li>
        </ul>
      </p>
      <p>
        Alternatively, use the quick-search box to query the DL collection for a term that sparks
        your interest. For example:
        <ul>
          <li>
        <a href="{$library_name}/collection/{$collName}/search/TextQuery?qs=1&amp;rt=rd&amp;s1.level=Doc&amp;startPage=1&amp;s1.query=love&amp;s1.index=ZZ">love</a>
        and
        <a href="{$library_name}/collection/{$collName}/search/TextQuery?qs=1&amp;rt=rd&amp;s1.level=Doc&amp;startPage=1&amp;s1.query=amore&amp;s1.index=ZZ">amore</a>,
        or maybe something more frivolous such as
        <a href="{$library_name}/collection/{$collName}/search/TextQuery?qs=1&amp;rt=rd&amp;s1.level=Doc&amp;startPage=1&amp;s1.query=la&amp;s1.index=ZZ">la</a>.
          </li>
        </ul>       
      </p>


      <h2>Data Analysis and Visualization</h2>
      
      <gsf:script src="ext/jena/sgvizler2/sgvizler2.js"/>

      <gsf:script>
          $(document).ready(    
                function() {
          
          // Exaple triple
          // "s": { "type": "uri" , "value": "http://127.0.0.1:8383/greenstone3/library/collection/eurovision/document/HASH0191e9cc7bfdf14743472257s10" } ,
          // "p": { "type": "uri" , "value": "gsdlextracted:Country" } ,
          // "o": { "type": "literal" , "value": "United Kingdom" }

          sgvizler2.containerDraw('sgvizler2-country-count');                 
        }
          );
      </gsf:script>

      <xsl:variable name="graphURI">https://so-we-must-think.space<xsl:value-of select="$siteURL"/><xsl:value-of select="$library_name"/>/collection/<xsl:value-of select="$collName"/></xsl:variable>    
      <div id="sgvizler2-country-count"
           data-sgvizler-endpoint="//sowemustthink.space/greenstone3-lod3/greenstone/query"
           data-sgvizler-chart="google.visualization.BarChart"
           data-sgvizler-chart-options="title=Number of Songs from each Country|legend.position=none|height=900|chartArea.height=840|fontSize=11"
           data-sgvizler-log="2"
           style="width:900px; height:300px; margin-left: auto; margin-right: auto; overflow-y: scroll; overflow-x: hidden;">
           <xsl:attribute name="data-sgvizler-query">
         PREFIX rdfs: &lt;http://www.w3.org/2000/01/rdf-schema#&gt;
         PREFIX gsdlextracted: &lt;http://greenstone.org/gsdlextracted#&gt;

         SELECT ?country (COUNT(?country) AS ?freqCount)         
         WHERE {
           GRAPH &lt;<xsl:value-of select="$graphURI"/>&gt;  {
               { 
             SELECT DISTINCT ?country ?year WHERE {
                 ?s gsdlextracted:Country ?country.
                 ?s gsdlextracted:Year ?year.
             } ORDER BY ?country ?year
               }
             }
         }
         GROUP BY ?country ORDER BY ASC(?country)
           </xsl:attribute>
           <xsl:text> Loading ...</xsl:text>
      </div>

     
      <p style="padding-top: 10px;">
        All the metadata in the digital library is simultaneously
        published as linked data, meaning it is possible to
        extract and analyze the data contained here in a variety
        of ways.  To aid in such analysis we have
        added in a data visualization layer to the digital
        library.  This is how the bar-graph above has been
        created, which shows how many times each country has
        competed, alphabetically sorted.
      </p>
      <p>
        Through our:
        <ul>
          <li>
        <a href="{$library_name}/collection/{$collName}/page/sgvizler">Visualizer page</a>
          </li>
        </ul>
      </p>
      <p>
        we provide samples you can try out to give you an idea of
        the sorts of visualization that can be produced. More
        importantly, these samples are editable so you are free to
        change them however you wish.  On the visualization page
        you'll find a sample that shows you how often different
        countries have won Eurovision, but perhaps you'd like to
        find out who has lost the most often?  We also provide a
        sample dataflow visualization of jury voting patterns over
        the last decade, which makes for interesting viewing!
        Adjust the values used to discover how this compares
        with other time periods.
      </p>

      <div id="viz-show-more" style="margin-bottom: 10px;">

        <p>
          In addition to the visualizer, through the:
          <ul>
        <li>
          <a href="{$library_name}/collection/{$collName}/page/sparql">Data Analysis page</a>
        </li>
          </ul>
          you will find a set of samples you can test-drive to give you an idea of the
          sorts of raw data analysis that can be done.  The syntax used is called
          <a href="https://en.wikipedia.org/wiki/SPARQL" target="_blank">SPARQL</a> (pronounced &quot;sparkle&quot;).  If you are unfamiliar
          with this syntax, there are a variety of tutorials available online where you can learn about query language, such as
          the one done by <a href="https://jena.apache.org/tutorials/sparql.html" target="_blank">Apache Jena</a>, an Open Source
          initiative that provides a variety of Semantic Web and Linked Data tools.
          As before, these samples are editable so you are free to
          change them however you wish to adjust the analysis undertaken, or once you're mastered the
          query syntax, develop completely original forms of
          analysis.
      </p>

      
      <p>
        We suggest starting with viewing <a href="{$library_name}/collection/{$collName}/page/sgvizler">sample visualizations</a> to see what's possible,
        and making minor edits to that to adjust what is visualized.
        Then, if you want to start visualizing the data in a more substantially different way
        or else export the data for more detailed analysis under your own control,
        switch to the <a href="{$library_name}/collection/{$collName}/page/sparql">SPARQL-based data analysis</a> page to ensure the underlying
        data retrieved is as you intended.  Then take the newly developed SPARQL query back to the visualizer page, and through the
        additional text-input fields provided there, develop the visualization.

      </p>

      </div>

      <gsf:script>
        $('#viz-show-more').showMore({
            minheight: 0,
        buttontxtmore:"show more ...",
        buttontxtless:"... show less"
          });
      </gsf:script>

<!--
      <p>       
        If you'd like to dig into the data behind this Digital Library collection, this can be done directly
        using the <a href="{$library_name}/collection/{$collName}/page/sparql">SPARQL Query interface</a>.
        This is a good place to go to see what sort of data is being stored, and we provide some sample
        queries to get you going.  But if you like to see the data presented more visually, we suggest
        you try out the <a href="{$library_name}/collection/{$collName}/page/sgvizler">SGVizler page</a>,
        which takes things to the next level, using pie-charts, histograms and other forms of
        visualization to present the data.      
      </p>

-->

      <h2 id="it-all-started-with">It All Started with a Little <strike>Sparkle</strike>SPARQL</h2>
      

      <p>
        In terms of how this collection was developed using the
        Greenstone3 Digital Library (DL) architecture, we are
        being a touch irreverent to say <i>it all started with a
        little SPARQL</i>.
        It is certainly true to say that, operationally, the DL
        was created using SPARQL query that draws down JSON
        records from
        <a href="https://dbpedia.org" target="_blank">DBPedia</a>       
        about all the different entrants in the Eurovision.  This
        is then ingested into Greenstone using its document- and
        metadata-processing pipeline: expand through the <i>show
        more ...</i> button below to see the actual query.
        But in truth, our starting point of the SPARQL query is
        only possible due to the Herculean efforts of the
        contributors to the Wikipedia pages about
        the Eurovision Song Contest, and following on from
        that the endeavors of the DBPedia project to
        transform a substantial portion of that information
        into machine-readable linked data.
      </p>

      <p>
        Continuing the technical development of the DL,
        to the DBpedia extracted content, we then added in voting metadata—again
        using the Greenstone document- and metadata- processing
        pipeline—this time in the form of CSV-based spreadsheet derived from the
        <a href="https://www.kaggle.com/datagraver/eurovision-song-contest-scores-19752019" target="_blank">Kaggle Eurovision Voting dataset 1975-2019</a>.
      </p>
      

      <div id="dl-tech-show-more">
        <p>
          Here's the SPARQL query that retrieves, for every year
          Eurovision has been held, the countries that took part.
          At under 20 lines of code, we think it's pretty awesome!
          The information retrieved includes the country, year,
          title of the song, and name of the entrant (the
          act/artist), amongst other things.  All useful core
          information to seed the digital library collection.  As
          the 2020 Eurovision event did not run due to the
          Covid-19 Pandemic, and (at the time of writing the 2021
          is yet to occur), we have opted to filter the matches
          returned to be prior to 2020.
        </p>
<!--
#    bind( REPLACE(str(?country_in_year), ".*(\\d{4})", "$1") AS ?year).

PREFIX rdfs: &lt;http://www.w3.org/2000/01/rdf-schema#&gt;
xsd:
skos:
prov:

dbc:
dbp:

dct:
-->     
        <pre style="background-color: #fff; color: #000; padding: 12px; margin-right: 6px;">
SELECT ?countries_in_esc_by_year ?country_in_year (?year AS ?Year) (?country AS ?Country) ?entrant (?entrant_label AS ?Creator) ?song (?song_label AS ?Title) (?was_derived_from AS ?WikipediaURL)
WHERE {
    ?countries_in_esc_by_year skos:broader dbc:Countries_in_the_Eurovision_Song_Contest_by_year.

    ?country_in_year dct:subject ?countries_in_esc_by_year.
    ?country_in_year dbp:year ?year.
    FILTER ( xsd:integer(?year) &lt; 2020).

    ?country_in_year dbp:country ?country.

    ?country_in_year dbp:entrant ?entrant.
    ?entrant rdfs:label ?entrant_label
      FILTER (lang(?entrant_label) = 'en').

    ?country_in_year dbp:song ?song.
    ?song rdfs:label ?song_label
      FILTER (lang(?song_label) = 'en').

    OPTIONAL {
      ?song prov:wasDerivedFrom ?was_derived_from
    }
}
ORDER BY DESC(?countries_in_esc_by_year)
        </pre>

        <p>
          You can try this query out yourself if you like.  Select the entirety of the SPARQL query
          in the above text box, and press <i>Control-C</i> to place it in your Copy-buffer.
          Next visit the DBPedia SPARQL Endpoint given below, and in the main text box of the page
          that appears, press <i>Control-V</i>
          to paste in your SPARQL query. Finally, click on the <i>Execute Query</i> button
          to initiate the search.
          <ul>
          <li>
            <a href="https://dbpedia.org/sparql/" target="_blank">DBpedia's SPARQL endpoint</a>
          </li>
          </ul>
        </p>
        <p>
          Through the SPARQL Endpoint you can change the output format that is used to, for example, JSON or Turtle.
          For convenience, if you are just interested in seeing what the outcome of running the query is, displayed as a web page:
          <ul>
        <li>
          <a href="https://dbpedia.org/sparql?default-graph-uri=http%3A%2F%2Fdbpedia.org&amp;query=SELECT+%3Fcountries_in_esc_by_year+%3Fcountry_in_year+%3Fyear+as+%3FYear+%3Fcountry+as+%3FCountry+%3Fentrant+%3Fentrant_label+as+%3FCreator+%3Fsong+%3Fsong_label+as+%3FTitle+%3Fwas_derived_from+as+%3FWikipediaURL%0D%0AWHERE+%7B%0D%0A++++%3Fcountries_in_esc_by_year+skos%3Abroader+dbc%3ACountries_in_the_Eurovision_Song_Contest_by_year.%0D%0A%0D%0A++++%3Fcountry_in_year+dct%3Asubject+%3Fcountries_in_esc_by_year.%0D%0A++++bind%28+REPLACE%28str%28%3Fcountry_in_year%29%2C+%22.*%28%5C%5Cd%7B4%7D%29%22%2C+%22%241%22%29+as+%3Fyear%29.%0D%0A++++FILTER+%28+xsd%3Ainteger%28%3Fyear%29+%3C+2020%29.%0D%0A%0D%0A++++%3Fcountry_in_year+dbp%3Acountry+%3Fcountry.%0D%0A%0D%0A++++%3Fcountry_in_year+dbp%3Aentrant+%3Fentrant.%0D%0A++++%3Fentrant+rdfs%3Alabel+%3Fentrant_label%0D%0A++++++FILTER+%28lang%28%3Fentrant_label%29+%3D+%27en%27%29.%0D%0A%0D%0A++++%3Fcountry_in_year+dbp%3Asong+%3Fsong.%0D%0A++++%3Fsong+rdfs%3Alabel+%3Fsong_label%0D%0A++++++FILTER+%28lang%28%3Fsong_label%29+%3D+%27en%27%29.%0D%0A%0D%0A++++OPTIONAL+%7B%0D%0A++++++%3Fsong+prov%3AwasDerivedFrom+%3Fwas_derived_from%0D%0A++++%7D%0D%0A%7D%0D%0AORDER+BY+DESC%28%3Fcountries_in_esc_by_year%29&amp;format=text%2Fhtml&amp;timeout=30000&amp;signal_void=on&amp;signal_unconnected=on" target="_blank">Click here to run the query directly</a>
        </li>
          </ul>
        </p>

        <h2>Triplestore Errata</h2>

        <p>
          The above SPARQL query is a good starting point to
          extract all the Eurovision entries over the years,
          however a more careful study of the returned results
          revealed a few complications that needed to be
          addressed. One issue stems from the fact that in its
          inaugural year, countries were allowed to send two
          entries each.  For 1956, for every URI representing a
          country in that year there are two title and two
          entrants represented.  As initially expressed, the
          SPARQL query does not cater for this circumstance and
          results in 2 x 2 = 4 combinations of artist and title
          per song.
        </p>
        <p>
          The way to address this is to include an additional
          constraint that ensures that the URI representing
          <i>?song</i> includes the relationship <i>dbp:artist</i>
          for <i>?entrant</i>, effectively locking in to the
          artist that performed that particular song.  Studying
          the result of this change, however, showed up a more
          wide-reaching problem which was that not all the
          <i>?country_year</i> URI entries expressed relationships
          to songs and artists that were themselves URI: sometimes
          they were represented as a string literal, meaning the
          added constraint would fail, and reject entirely the
          details about a country's entry in that
          year. Compounding this, we also saw that some of the
          processing work by DBPedia to turn the manually curated
          information in Wikipedia into machine-readable form
          erroneously handled the formation of some of the song
          titles and artists.
        </p>
        <p>
          Given that the erroneous entries were strings (even
          integer numbers at times!) and not URI gave us a way in
          to see how wide-spread the problem was.  Using adapted
          versions of the the main SPARQL query we had formulated,
          we were able to produce lists of the affected entries.
          The lists are available here through the following
          links:
          <ul>
        <li>
          <a target="_blank" href="sites/{$site_name}/collect/{$collName}/prepare/problem-lod-lists/dbpedia-problem-songs.html">Problem Songs (titles are literals not URIs/IRIs)</a>
        </li>
        <li>
          <a target="_blank" href="sites/{$site_name}/collect/{$collName}/prepare/problem-lod-lists/dbpedia-problem-entrants.html">Problem Entrants (artists are literals not URIs/IRIs)</a>
        </li>
          </ul>
        </p>

        <p>
          The generation of these lists also provided the key to
          the approach we used to compensate for the complications
          these issues introduced.  Skipping ahead slightly to the
          formation of the Digital Library collection with
          Greenstone3, we make use of this software architecture's
          Triplestore Extension, which means that in addition to
          the main DL and Open Archive Initiative (OAI) server
          endpoints, there is also a triplestore backend.  While
          the triplestore extension was designed to provide SPARQL
          access to the metadata and document content of the DL
          collections, its existence means we can include in it a
          graph that represents the necessary errata information
          we need to &quot;course correct&quot; the SPARQL query
          to perform how it is intended.
        </p>
        
        <p>
          This does admittedly complicate the expression of the
          query, but the additions are manageable.  The expanded
          query makes use of SPARQL's federated search feature:
          the query starts as before with the retrieval of triples
          from the DBPedia endpoint; based on resolved values of
          entities such as <i>?country_year</i> and <i>?song</i>,
          it then optionally retrieves matching items from the DL
          SPARQL endpoint.  The final step is to use a conditional
          clause (if-statement) to test to see if the DBpedia
          version of the song is a literal, and if it is and if
          there is a bound value for the DL retrieved one, then it
          selects that one in preference.
        </p>

        <p>
          The DBpedia SPARQL endpoint doesn't allow for federated
          queries, and so we initiate the SPARQL queries through
          the DLs SPARQL endpoint, using SERVICE blocks to specify
          the parts of the query that are run on the DBpedia endpoint.
          <ul>
        <li>
          <a href="{$library_name}/collection/{$collName}/page/sparql">DL's (local) SPARQL endpoint</a>
        </li>
          </ul>
        </p>
        
        <h3>Adding in Voting Metadata</h3>

        <p>
          To fulfill our vision of developing this DL collection
          as a rich resource through which people can explore the
          phenomenon we went looking for voting data that was
          available in a machine-readable format.
          We found data compiled through a manual curation process
          about how countries have voted going back to 1975 is available through the
          <a href="https://www.kaggle.com/datagraver/eurovision-song-contest-scores-19752019">Kaggle website as an Excel spreadsheet</a>.
        </p>
        <p>
          To incorporate this as metadata into the DL, we wrote
          some Python code to transform the data into the internal
          serialized metadata format used by Greenstone.  Prior to
          this project, the only serialized form for this was XML,
          which is processed by the MetadataXML plugin.  As it was
          more convenient to generate JSON from our Python code,
          we took the step of adding in a new plugin to
          Greenstone3: MetadataJSON.
        </p>

        <h3>Page Scraping</h3>

        <p>
              Despite our best intentions work soley with
              machine-readable data—primarily as you have seen in the
              form of Linked Open Data, but also utilizing a
              spreadsheet of voting data—to form the Eurovision DL,
          in looking to expand the metadata in the DL to cover
          details concerning the draw position of acts, and their
          overall placing, we have resorted to page-scraping
          content from Wikipedia itself.  This was because such
          information was not part of the entity extraction
          process that occurs when Wikipedia is mapped to DBpedia.
        </p>

        <p>
          A review of Wikipedia article pages about the event in
          any given year showed these pages to be especially well
          curated, and included a table in each that listed the
          information we sought.  While there was some variation
          in how this table was expressed in HTML, with a
          considerably portion of the heavy lifting being done by
          the Python library BeautifulSoup4, it was not too
          complex a task to develop a program that extracted this
          information and turned it into the newly developed
          Greenstone JSON metadata format.
        </p>
          
        <h3>Patching in Missing Data</h3>

        
        <p>
          Another difficulty we have encountered is that
          not every country who had an entry in Eurovision
          in a given year has its own standalone article page.
          This leads to missing entries in the category
          page for the contest in a given year, which is
          problematic to us, because it is this category
          information that we draw upon in our SPARQL query
          to populate the DL with all the acts.
        </p>
        <p>
          The information about all the countries competing
          in a given year does, however, appear in the
          article page for the contest in that year.  In fact
          it's in the same table we targetted to extract out
          draw position and placement.  We therefore
          wrote a further page-scraping program to compare
          the countries in that table with the countries
          listed on the category page for the contest in
          that year.  For any entries we find in the
          table, but not in the Category page, we
          produce a metadata record for the DL
          with basic information about the entry:
          country, year, song title, artist,
          draw-position, placement, and (where available)
          their total score.
        </p>
        <p>
          Comparable with the problem titles and artist/entrants,
          we have formulated a SPARQL query that enumerates
          these missing category entrants:
          <!--
          We took the opportunity to add in further fields: Performing Position, Placement, Voting Total, thumbnail flag image.


          An unintended side-affect of this is that we have also been able to expand
          -->

          
          <ul>
        <li>
          <a href="sites/{$site_name}/collect/{$collName}/prepare/problem-lod-lists/dbpedia-problem-category-in-year.html">Problem Category pages (some countries not listed in a given year despite competing)</a>
        </li>
          </ul>
        </p>
        
          
      </div>
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      <div>
        <h2>The Gory Details</h2>
<!--
          <p>         
        The resulting SPARQL query result set (JSON format
        selected for output) is then ingested into a Greenstone
        DL collection, and used in a variety of ways.  For now
        an (admittedly cryptic) list of technical steps that
        were developed and/or deployed to provide the
        functionality encountered in interacting with this site.
        
        <ul>
          <li>New SPARQL plugin for <i>download_from.pl</i> developed, used in GLI to enter the above query</li>
          <li>New SPARQL <i>Document Processing</i> plugin developed</li>
          <li>Greenstone3 Apache Jena Triple Store Extension activated</li>
          <li>SGVizler used to display Google Visualizations such as the pie-chart above.</li>
          <li>Metadata in document view enhanced through Greenstone Format Statements micro-data</li>
          <li>Custom <i>interface</i> developed</li>
        </ul>
          </p>
-->     
          <p>
        Viewing the
        <a download="collectionConfig.xml"
               href="sites/{$site_name}/collect/{$collName}/etc/collectionConfig.xml">collection
        configuration file</a> provides a good insight into how
        all of these technical aspects are brought together.
          </p>
          
          <p>
        Full disclosure as to how the collection all ticks is
        provided through our Subversion repository.  Topping up
        our
        <a href="https//trac.greenstone.org/browser/main/trunk/greenstone3">Greenstone3
        code base</a> we have:
        
        <ul>
          <li>The site: <a href="https://trac.greenstone.org/browser/main/trunk/model-sites-dev/eurovision-lod">eurovision-lod</a></li>
          <li>The interface: <a href="https://trac.greenstone.org/browser/main/trunk/model-interfaces-dev/eurovision-lod">eurovision-lod</a></li>
          <li>The triplestore extension: <a href="https://trac.greenstone.org/browser/gs2-extensions/apache-jena/trunk/src">apache-jena</a></li>
        </ul>
            
          </p>

      </div>
      
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          <p>
        In terms of how this collection was developed using the
        Greenstone DL architecture, the starting point is the
        formulation of a SPARQL query to retrieve from DBpedia
        entries about all the entrants in the contest over the
        years:
          
          </p>
          
        </div>
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          Linked Open Data
        </div>

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          <h2>Eurovision LOD SPARQL Endpoints</h2>
          <p>
        The source data can be access vis the DBpedia SPARQL endpoint.  The ingested,
        data (with correction) is available through the collection's local
        SPARQL endpoint:
        <ul>
          <li>
            <a href="https://dbpedia.org/sparql/">DBpedia's SPARQL endpoint</a>
          </li>
          <li>
            <a href="{$library_name}/collection/{$collName}/page/sparql">DL's (local) SPARQL endpoint</a>
          </li>
        </ul>
          </p>
          
          <h2>Eurovision LOD Errata</h2>
        </div>
      </div>
      
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          Voting Data
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          <p>
        The Voting data used in this collection is sourced from the Kaggle, which in turn
        is derived from work available through Data Graver:
        <ul>
          <li><a href="https://www.kaggle.com/datagraver/eurovision-song-contest-scores-19752019">Kaggle Eurovision Voting dataset 1975-2019</a></li>
          <li><a href="https://data.world/datagraver/eurovision-song-contest-scores-1975-2019">Data Graver</a></li>
          <li><a href="https://docs.google.com/spreadsheets/d/1veXpiF54hQGP4OVuf1xjowumIe8HUOhI/edit#gid=528591420">Google Spreadsheet (internal use only)</a></li>
          
        </ul>
          </p>
        </div>    
      </div>

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