Agenda, Intro (15min) Vertiefendes Uebungsprojekt - SQL II. Wichtige Termine. Voraussetzungen

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1 Agenda, Intro (15min) Vertiefendes Uebungsprojekt - SQL II Gerhard Wohlgenannt Ablauf der Lehrveranstaltung Quiz Whd SQL Semantic Web / Linked Data Intro Kurzvorstellung Projekte/Themen Voraussetzungen Wichtige Termine Für das Projekt notwendige Kenntnisse sind 1. Modellierungsmethoden insb. ER-Modellierung 2. SQL (PostgreSQL) 3. eine Programmiersprache (PHP 5.x, Python, Java) 4. (X)HTML 16. Mai 2012: Vorbesprechung, Theorie + Problemstellung 23. Mai 2012: Test, Gruppeneinteilung und Projektvergabe 30. Mai 2012: Präsentationen/Besprechung: Problemdefinition und Use Case Diagramme; ER-Modelle, DB-Design; Projektplanung & Milestones 06. Mai 2012: Implementierung / Präsentation Milestones 13 Juni 2012: Implementierung / Präsentation Milestones 20. Juni 2012: Abschlusspräsentation und Projektübergabe

2 Beurteilungsschema Test 10 % Mitarbeit, Präsentation 25 % Test (unit 2) 65 % Projekt (Usability, Datenbankdesign/Performance, Security) 25 % Projektdokumentation 35 % Ausführung 10 % Endpräsentation Nächste Woche Test über 1. SQL + ER Modellierung Grundkenntnisse 2. Linked Data + Semantic Web Ablauf der Lehrveranstaltung Reminder Software Projekt Definition und Modell Problemdefinition/Use Cases ER-Modell/DB-Design Implementierung Abnahme und Präsentation Benutzerdokumentation Work Reports (wer hat was gemacht) Hauptuni Untersuchung Bitte einer Psychologin Nicht Teil der LV

3 Das Projekt? 1. Themen: am Schluss der LV besprochen SQL basiert, Linked Data & SPARQL, oder Projekt mit RB-Games 2. Gruppen zu 4-5 Personen 3. Ablauf: Agile Entwicklung; wöchentliches reporting über status, Vereinbarung für Zielen für die nächste Woche 4. Jedes Gruppenmitglied muss jeweils Programmieraufgaben übernehmen und darüber jede Woche kurz berichten 5. Infos und links zu manuals etc.: Fragen zum generellen Ablauf? Wiederholung: SQL (30min) SQL Wiederholung: Goals 1. Einstiegsvoraussetzung, beim Test nächste Woche zu können.. :-) 2. Interaktiv, Mitarbeitspunkte zu gewinnen 3. Beispiel: Klassiker Bibliotheksverwaltung 4. jetzt.. Starting from a textual description of the system Data model: ER-Diagram Transform to relations / tables CREATE TABLE SELECT: WHERE, GROUP BY, LIMIT JOINs UPDATE, INSERT, DELETE

4 Linked Data project Linked data section - Agenda 1. Theory section today: Linked data 2. One possible topic for projects 3. Linked Data not mainstream yet, but a lot of research going on 1. Basic Semantic Web technologies: URIs, namespaces, XML, RDF, OWL, Linked data intro 3. SPARQL 4. Linked data mashups Mashups - Motivation Semantic Web introduction Goal: combine and visualize open datasets Example: simple mashup that shows UK gov data + DBpedia etc in geographical context 1. URIs 2. namespaces 3. XML 4. RDF 5. RDFS + OWL

5 Semantic Web introduction - see Linked Data introduction See folien/unit1_sw-nup.pdf Introduction + definitions Principles Generation and consumption Datasets Examples Intro Rationale We are surrounded by data about so many things but very few used for automatic consumption. a term used to describe a recommended best practice for exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF. (Wikipedia) Structure enables sophisticated processing: XML, N3,.. Hyperlinks connect distributed data: typed links, eg. owl:sameas From data islands to a global data space: typed links between data items, not documents Source: Linked data book,

6 (Linked Data) Principles 1. Use URIs as names! 2. Use HTTP URIs, so that people can look up those names. 3. Dereferenceable: When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL). 4. Include links to other URIs, so that they can discover more things. Datasets I There is a big number of data sets available on the Web of Data now I Cross-domain data sets (such as DBpedia) vs. domain data sets eg. geographic, about media,... Publishing I Exposing + Sharing: Publishing datasets on the Web + making them accessible (using on open license) I Connecting: Interlinking between the datasets I data, information, knowledge: data (instances), knowledge ( ontologies etc.) Linked Open Data Cloud The LOD cloud, by Richard Cyganiak and Anja Jentzsch

7 Cross-domain datasets Geographic datasets DBpedia ( Structured version of Wikipedia. A DBpedia ontology for the vocabulary million things : 416,000 persons, 526,000 places (including 360,000 populated places), 106,000 music albums, 60,000 films, 17,500 video games, 169,000 organizations,... eg: Freebase ( an editable, openly-licensed database populated through user contributions and data imports from sources such as Wikipedia and Geonames. Freebase provides RDF descriptions of items in the database, which are linked to items in DBpedia with incoming and outgoing links. (Source: Linked data book) Geonames ( geographical database covers all countries and contains over eight million placenames Interlinked with DBpedia serves as a hub for other data sets that have some geographical component. Linked data version of the CIA world factbook, at incl. SPARQL endpoints, Media and Entertainment datasets SPARQL introduction Many parts of the BBC Website are fed from Linked Data. New York Times has published a significant proportion of its internal subject headings as Linked Data, interlinking these topics with DBpedia, Freebase and Geonames. Data sets about People, Organization, Topics,... are available, which power Linked MBD: Linked Data about films, actors, etc. for Linked Data in the domain of music. 1. Introduction 2. Slides for the SPARQL section are found here folien/unit1_sw-nup.pdf 3. Exercises...

8 Mashups - Overview What are mashups? 1. What are Mashups? What are LD Mashups? 2. Examples 3. Example with code Wikipedia: a mashup is a Web page or application that uses and combines data, presentation or functionality from two or more sources to create new services. Main characteristics: combination, visualization, and aggregation. Make existing data more useful What are LD mashups? Approaches to LD Mashups Query and mix data from linked data sources into an application. Add some kind of visualization. Tools: eg. python-rdflib to query and store graphs, and to do SPARQL queries on them. 1. Crawl data into local triple store, query local store LDspider for crawling, SPARQL/Update for saving SPARQL to access triple store 2. Directly access data sources (endpoints) with SPARQL Might get too slow if many datasets, but ok for experiments. Needs endpoints available. Data always up-to-date 3. Intermed: Collect data into a graph in memory and query it, eg. with RDFlib Slow, easy to set up. Use for prototyping...

9 Tools Crawling: LDSpider, SPARQL queries, download datasets Storing: None (just consume), local RDF graph, triple store Querying: SPARQL Visualization:?? depends on data: your turn.. Common tasks 1. Accessing the Web of Data: Crawling (follow links), LD search engines, SPARQL endpoints 2. Vocabulary Mapping: Different Linked Data sources may use different RDF vocabularies to represent the same type of information. Linked Data applications which discover data that is represented using terms that are unknown to the application may therefore search the Web for mappings and apply the discovered mappings to translate data to their local schemata. 3. Identity Resolution: Different Linked Data sources use different URIs to identify the same entity, for instance, a person or a place. Data sources may provide owl:sameas links pointing at data about the same real-world entity provided by other data sources. 4. Provenance Tracking: If cached locally, track where you got the data from. 5. Data Quality Assessment: Open nature of the web, be suspicious about quality. 6. Using the Data in the Application Context: Display data to the user. Eventually aggregate or mine the data, etc. sameas.org Examples is a good place for identity resolution. Example: 2Fdbpedia.org%2Fresource%2FMike_Tyson&x=13&y=21 The BBC website uses Linked Data / Semantic Web technologies for its website, eg. A mashup showing how to visualize LD info on a Geo map how:

10 Examples (2) A python-rdflib mashup which uses a few data sets to trace location information and project funding in research organisations:http: //johngoodwin225.wordpress.com/2011/01/18/ Autocomplete while typing to find a (mostly) DBpedia oder how-can-i-use-the-ordnance-survey-linked-data-a-python-rdflib-example/ WikiMedia entry for a query Javascript widget. A simple mashup with some of the BBC linked data and DBpedia linked data. The goal is to show TV and radio shows about different places, ie. to get geo-location info about shows?! 01/20/a-crude-bbc-places-linked-data-mashup/ Source code: result at Shows a few ways how to use python-rdflib download and query a graph. sql2/example/test.py sql2/example_jena/test.py Triple Store setup Datasets How to install and start Jena/Fuseki: apache.org/jena/documentation/serving_data/ Run Server, eg../fuseki-server --loc=db /ds Upload data: ldspider echo > url file java -jar ldspider-1.1e.jar -s uri file -b follow -oe ldspider generates a 4-tuple (last element is the graph name named graph The LOD Cloud: lod/lod-datasets_ _colored.htmlxx For example, DBpedia file:

11 Exercise Projekte: Themen (15min) Do a simple SPARQL query on DBpedia data for Mike Tyson : What is his birthdate? 1. Linked Data Mashup (Python, PHP) 2. SQL + PHP / Python 3. Projekt mit Unternehmen: RB Games Projekte: Linked Data Projekte: SQL Python, Java oder PHP. Python preferred, da schon Referenz-Code... Ideen von Teilnehmern Bei einem LD Projekt wird mit der Implementierung etwas später begonnen, die erste Woche besteht aus Brainstorming und Sichtung von LD Datenquellen DB-basiert (SQL: PostgreSQL) Recht freie Themenwahl, Ideen der Teilnehmer gefragt. Programmierung mit Python bzw PHP (event. Java)

12 Projekte: RB-Games Ende Thema vorgegeben Hr. Bitzner Fragen? Fr. Ehlers von der Hauptuni: Untersuchung über Wohlbefinden im Studium hat nichts mit dieser LV zu tun! :-)