1. Linked Data Mashups: From Query to Visualization Dominic DiFranzo

2. RDF Triple: Subject Predicate Object Use URI for universal naming New York has the postal abbreviation NY "NY".http://purl.org/dc/terms/alternative

3. Linking I found a new dataset and it has the following triple “The Empire State”.http://dbpedia.org/page/New_Yorkhttp://dbpedia.org/ontology/Place/oth erName

4. owl:sameAS.http://www.w3.org/2002/07/owl#sa meAshttp://dbpedia.org/page/New_York

6. What We Have

7. Current Technology Sunlight Foundation’s National Data Catalog, Socrata, Open311 API, and Microsoft’s Open Government Data Initiative, etc Store in some backend, release data through an API.

8. Challenges Only ask what its built to answer No standard - must relearn each time Opaque - no way for consumers to see, reuse or improve the data model Silos of Data - no linking at the data level VeryTop Down

9. What We Want

10. Linked Data decentralized - sources may be spread out and referenced across the Web modular - linked without advance planning or coordination scalable - once store in place, it’s easy to extend advantages hold even when definitions and structure of the data changes over time.

14. Sparql SPARQL is a query language for the Semantic Web.

15. Sparql

16. Long! SELECT ?node ?name WHERE{ ?node ?name.http://xmlns.com/foaf/0.1/givenname ?node.ntax-ns#type> <http://xmlns.com/foaf/0.1/Person } LIMIT 10

17. Prefix PREFIX foaf: http://xmlns.com/foaf/0.1/ PREFIX rdf: 22-rdf- syntax-ns#> SELECT ?node ?name WHE WHERE{ ?node foaf:givenname ?name. ?node rdf:type foaf:Person. } LIMIT 10

18. Shortcuts PREFIX foaf: http://xmlns.com/foaf/0.1/ PREFIX rdf: 22-rdf- syntax-ns#> SELECT ?node ?name WHE WHERE{ ?node foaf:givenname ?name ; rdf:type foaf:Person. } LIMIT 10

19. Graphs

20. Named Graph PREFIX dc: http://purl.org/dc/elements/1.1/ SELECT ?graph ?node ?title WHERE{ GRAPH ?graph{ ?node dc:title ?title. } LIMIT 3

21. Named Graph PREFIX dc: http://purl.org/dc/elements/1.1/ SELECT ?node8 ?desc8 ?node401 ?desc401 WHERE{ GRAPH { ?node401 dc:description ?desc401. } GRAPH { ?node8 dc:description ?desc8. } LIMIT 3

22. Union PREFIX dc: http://purl.org/dc/elements/1.1/ SELECT ?node8 ?desc8 ?node401 ?desc401 WHERE{ { GRAPH { ?node401 dc:description ?desc401. } }UNION{ GRAPH { ?node8 dc:description ?desc8. } LIMIT 3

23. Optional PREFIX foaf: http://xmlns.com/foaf/0.1/ SELECT ?node ?name ?givenname WHERE{ ?node foaf:name ?name. OPTIONAL{ ?node foaf:givenname ?givenname. }

24. Filter PREFIX foaf: http://xmlns.com/foaf/0.1/ SELECT ?node ?name ?givenname WHERE{ ?node foaf:name ?name. ?node foaf:givenname ?givenname. FILTER regex(?name, "Biden"). }

25. SPARQLProxy This is a web service that allows you to query any SPARQL endpoint, and get back the results in any format you want. A RESTful way to query any endpoint in any environment.

26. SPARQLProxy http://logd.tw.rpi.edu/sparqlhttp://logd.tw.rpi.edu/sparql? Paramiters: query: [required] encoded String of SPARQL query query-uri :[required] URI of SPARQL query (use as an alternative to "query" parameter. These two parameters are mutul-exclusive)

27. SPARQLProxy service-uri: [required] URI of SPARQL Endpoint – default is the LOGD endpoint output: output format. ''xml'' - SPARQL/XML (default) : ''exhibit'' - JSON for MIT Exhibit : ''gvds'' - JSON for Google Visualization : ''csv'' - CSV : ''html'' - HTML table : “sparql” - SPARQL JSON

28. Example http://logd.tw.rpi.edu/sparql.php?query- option=text&query=PREFIX+conversion%3A+%3C http%3A%2F%2Fpurl.org%2Ftwc%2Fvocab%2Fco nversion%2F%3E%0D%0ASELECT+%3Fg+sum%28 +%3Ftriples+%29+as+%3Festimated_triples%0D% 0AWHERE+{%0D%0A++GRAPH+%3Fg++{%0D%0A +++%3Fg+void%3Asubset+%3Fsubdataset+.%0D %0A+++%3Fsubdataset+conversion%3Anum_tripl es+%3Ftriples+.%0D%0A++}%0D%0A}+%0D%0AG ROUP+BY+%3Fg%0D%0A&service- uri=&output=html&callback=&tqx=&tp=

29. Example // compose query $sparqlproxy_uri = "http://logd.tw.rpi.edu/ws/sparqlproxy.php" $params = array(); $params["query-uri"] = "http://logd.tw.rpi.edu/demo/retrieving-sparql- results/datagov-list-loaded-dataset.sparql"; $params["service-uri"] = "http://services.data.gov/sparql"; $params["output"] = "gvds"; $query= $sparqlproxy_uri."?". http_build_query($params,,'&') ; //specific for Drupal //show query result echo file_get_contents($query);

30. Visualizing The Data Many JavaScript API and Libraries to help make visualizations Trades in eases of use and control/customization. We will focus on the Google Visualization API, very easy to use out-of-the-box but almost impossible to customize outside of what they provide. http://code.google.com/apis/chart/interactive /docs/gallery.html http://code.google.com/apis/chart/interactive /docs/gallery.html

31. Visualization Example Start with a dataset(s) We will look into State Library Agency Survey: Fiscal Year 2006http://logd.tw.rpi.edu/source/data- gov/dataset/353/version/1st-anniversaryhttp://logd.tw.rpi.edu/source/data- gov/dataset/353/version/1st-anniversary and Tax Year 2007 County Income Data http://logd.tw.rpi.edu/source/data- gov/dataset/1356/version/2009-Dec-03

32. Example Lets make a map of "Adjusted Gross Income(AGI) per Capita” a US map where each state is colored according to the average AGI per person living in that state. We obtain a state's AGI data from Dataset 1356 and a state's population data from Dataset 353.

33. Lets make a query http://logd.tw.rpi.edu/demo/building-logd- visualizations/mashup-353-population-1356- agi.sparql http://logd.tw.rpi.edu/demo/building-logd- visualizations/mashup-353-population-1356- agi.sparql

34. <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> AGI per Capita Map AGI per Capita Map Loading Map...

36. // load google visualization packages - STEP 1 google.load('visualization', '1', {'packages': ['geomap']}); // set callback function for drawing visualizations - STEP 2 google.setOnLoadCallback(drawMap);

37. function drawMap() { //Query data - STEP 3 var sparqlproxy = "http://logd.tw.rpi.edu/sparql"; var queryloc = "http://logd.tw.rpi.edu/demo/building-logd- visualizations/mashup-353-population-1356-agi.sparql"; var queryurl = sparqlproxy + "?" + "output=gvds” + “&query-option=uri” + "&query-uri=" + encodeURIComponent(queryloc) ; var query = new google.visualization.Query(queryurl); query.send(handleQueryResponse); }

38. function handleQueryResponse(response){ // Check for query response errors. - STEP 4 if (response.isError()) { alert('Error in query: ' + response.getMessage() + ' ' + esponse.getDetailedMessage()); return; }

39. // read data - STEP 5 var data = response.getDataTable(); // create new data - STEP 6 var newdata = new google.visualization.DataTable(); newdata.addColumn('string', 'State'); newdata.addColumn('number', 'AGI per Capita');

40. // populate each row - STEP 7 var rows = data.getNumberOfRows(); for (var i = 0; i < rows; i++ ) { var state = 'US-' + data.getValue(i, 0); // AGI figure uses thousand-dollar unit var value = Math.round(data.getValue(i, 1)*1000/ data.getValue(i, 2)); newdata.addRow([state, value]); }

41. // configure map options - STEP 8 var options = {}; options['region'] = 'US';// show US map options['dataMode'] = 'regions'; options['width'] = 900; options['height'] = 550;

42. // define geomap instance - STEP 9 var viz = document.getElementById('map_canvas'); new google.visualization.GeoMap(viz).draw(newdata, options ); }//end of handleQueryResponse function //end of JavaScript Tag

43. See Live Version - http://logd.tw.rpi.edu/demo/building-logd- visualizations/agi-per-capita-v2.html