Maximising Online Resource Effectiveness Workshop Session 7/8 Development strategy

Call a spade a spade—SCAMORE 7/8 the power of open data and appropriate metadata photo: ©GM 2010

Development strategy Session 7/8

Metadata Increases specificity Improves common, wide, unambiguous understanding Content becomes computable

Compiling metadata Working individually, prepare some metadata about familiar entities by completing the following table...

Compiling metadata Subject Property Value me me me my organisation my organisation my organisation my home town my home town my home town

Compiling metadata Subject Property Value me name “George Munroe” me organisation my organisation me email address “george@netskills.biz” my organisation name “Platypus Consultancy” my organisation year formed “2004” my organisation town/city my home town my home town name “Belfast” my home town country UK my home town population “1 million”

Compiling metadata Subject Property Value GM name “George Munroe” GM organisation PCL GM email address “george@netskills.biz” PCL name “Platypus Consultancy” PCL year formed “2004” PCL town/city BFS BFS name “Belfast” BFS country UK BFS population “1 million”

organisation GM PCL ho m e to wn BFS

name organisation George Munroe GM PCL l ai ho em m george@netskills.biz e to wn BFS

me Platypus Consultancy na name organisation George Munroe GM PCL formed in 2004 n l ai ho di em m se george@netskills.biz e ba to wn BFS

me Platypus Consultancy na name organisation George Munroe GM PCL formed in 2004 n l ai ho di em m se george@netskills.biz e ba to wn name BFS Belfast po pu la country tio n 1 million UK

name Christine Cahoon CJ or home ga l ai ni ws em s at christine@netskills.biz Platypus Consultancy kno io me town n na name organisation George Munroe GM PCL formed in 2004 n l ai ho di em m se george@netskills.biz e ba to wn name BFS Belfast po pu la country tio n 1 million UK

name Christine Cahoon CJ or home ga l ai ni ws em s at christine@netskills.biz Platypus Consultancy kno io me town n na name organisation George Munroe GM PCL formed in 2004 n l ai ho di em m se george@netskills.biz e ba to wn name BFS Belfast po pu la country name tio Brian Kelly BK n 1 million l ai em organisation ho brian@netskills.biz UK m e to wn ntry cou name UKOLN ULN BTH name Bath based in

Real metadata Resource description framework ‣ RDF is a generic "way" of using definitive metadata with web resources. ‣ RDF describes "things" (defined by uniform resource identifiers, URIs) by assigning properties and corresponding values—statements are known as "triples" consisting of [subject] [predicate] [object]. ‣ The predicate URI usually references a term in a standard metadata vocabulary, resulting in unambiguous meaning. ‣ Any part of the triple can be a URI and URIs can point to other URIs that can be read using HTTP and extended (or related) in other web resources, thus a scalable model and very flexible. http://www.w3.org/TR/rdf-primer/

What is RDFa? RDFa = Resource Description Framework in attributes

What is RDFa? Generic model for the provision of metadata RDFa = Resource Description Framework in attributes

What is RDFa? Generic model for the provision of metadata RDFa = Resource Description Framework in attributes HTML

An RDFa basics tutorial by Manu Sporny http://www.youtube.com/watch?v=ldl0m-5zLz4&feature=player_embedded

Simple RDFa web page <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML+RDFa 1.0//EN" "http://www.w3.org/MarkUp/DTD/xhtml-rdfa-1.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" xmlns:v="http://rdf.data-vocabulary.org/#"> <head profile="http://www.w3.org/1999/xhtml/vocab"> <title>Simple RDFa example</title> </head> <body> <div xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Person"> My name is George Munroe, also known online as mungeo. I am involved in several ventures but my home web site is at: <a href="http://www.platypusconsultancy.com" rel="v:url">www.platypusconsultancy.com</a>. I live in Donegal, Ulster and work as a consultant trainer at Netskills. </div> </body> </html>

RDFa distiller Extract RDF from HTML + RDFa W3C service to identify and list RDF from a web page ‣ using web address, local file or direct text inputs ‣ provides “clean” view of data hierarchy ‣ enables simple check on markup validation *and* intended meaning http://www.w3.org/2007/08/pyRdfa/

Distilled RDFa page <?xml version="1.0" encoding="utf-8"?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:v="http://rdf.data-vocabulary.org/#" xmlns:xhv="http://www.w3.org/1999/xhtml/vocab#" xmlns:xml="http://www.w3.org/XML/1998/namespace" > <v:Person> <v:nickname>mungeo</v:nickname> <v:address> <v:Address> <v:region>Ulster</v:region> <v:locality>Donegal</v:locality> </v:Address> </v:address> <v:url rdf:resource="http://www.platypusconsultancy.com"/> <v:name>George Munroe</v:name> <v:title>consultant trainer</v:title> <v:affiliation>Netskills</v:affiliation> </v:Person> </rdf:RDF>

Real metadata Microformats and RDFa ‣ Previously RDF statements were usually provided in separate .rdf files and were not widely used because of the extra effort required to produce. ‣ Microformats consist of informal vocabularies (not referenced in the document) that have been established by rapid user adoption, ease of use and desire to create richer semantics with embedded metadata. These are used with "class" attribute in <div> and blocks or with “rel” in anchor <a …> tags. ‣ RDFa allows RDF statements to be included in ordinary HTML files using formally defined attributes within blocks, with metadata vocabularies referenced in <head>. http://www.w3.org/TR/rdfa-in-html/ http://microformats.org/wiki/Main_Page

Data integration Seamless use of data in a web page with desktop applications ‣ use of microformats tools to generate contact information in a web page ‣ viewing of web page containing microformats with an “aware” browser ‣ addition of data in the web page to desktop address book http://microformats.org/code-tools http://en.wikipedia.org/wiki/HCard

Metadata vocabularies The importance of using commonly understood and accessible metadata language Everyone (and every computer) must have a common understanding of what particular “things“ (entities and their properties) actually are ‣ concept of XML namespaces, identifying vocabularies (descriptions of what properties could be defined for a particular entity) available on the web ‣ these descriptions supplied as RDF (or RDFa) files with a URL (URI) And there’s more to it than just a flat list of entities and properties ‣ a real understanding involves being aware of the relationships between entity classes as well as what properties are associated with an entity ‣ these relationships can be defined using other vocabularies (OWL) ‣ a very complex “ontology” can be built very simply from triples where the object of one triple may be the subject of another

Exploring vocabularies Commonly used metadata vocabularies Google (person, organisation, review, event, recipe) ‣ http://rdf.data-vocabulary.org/ FOAF (Friend Of A Friend) ‣ http://xmlns.com/foaf/0.1/ GoodRelations (ecommerce) ‣ http://www.heppnetz.de/ontologies/goodrelations/v1.owl Dublin Core (generic document) ‣ http://dublincore.org/2008/01/14/dcelements.rdf Creative Commons (licensing) ‣ http://creativecommons.org/ns SKOS (Simple Knowledge Organisation System) ‣ http://www.w3.org/2009/08/skos-reference/skos.rdf

Metadata—deployment RDFa and linked data in UK government web- sites Mark Birbeck, Nodalities Magazine, 29 July 2009 The UK government’s Central Office of Information had a straightforward problem to solve: how could they create a centralised web-site of information that the public could search and access, when the source of that information could be any government department database or any public sector web-site? By using RDFa to address the challenge of making distributed data available in one place, the COI avoided having to make changes to each department's systems. But once each department is publishing RDFa, it becomes possible for third parties to consume that information however they see fit. Such a flexible architecture is crucial in the age of open government, and is a cornerstone of linked open data. http://blogs.talis.com/nodalities/2009/07/rdfa-and-linked-data-in-uk-government-web-sites.php

Metadata—deployment TSO announces major new platform to accelerate open data drive TSO partners with Garlik on hosted "trillion triple" RDF platform, 18 January 2010 TSO (The Stationery Office), the public sector division of Williams Lea, has today announced a partnership with Garlik, the leading semantic technology innovator, to launch what is believed to be the world's most scalable, securely hosted RDF platform for use by UK Central and Local Government departments. As the largest publisher in the UK of public sector documents (over 8,000 titles a year), TSO has taken this proactive step to provide its core public sector customers with the ability to participate with confidence in the Government's open data initiative. http://www.tso.co.uk/press/latestnews/archive/2010/triplestore/

Metadata—deployment RDFa adoption 21 January 2010

The open graph protocol Facebook and the open graph protocol Announced at the Facebook Developers Conference, 21 April 2010 The Open Graph protocol enables you to integrate your web pages into the social graph. It is currently designed for web pages representing profiles of real-world things—things like movies, sports teams, celebrities, and restaurants. Once your pages become objects in the graph, users can establish connections to your pages as they do with Facebook Pages. Based on the structured data you provide via the Open Graph protocol, your pages show up richly across Facebook: in user profiles, within search results and in News Feed. With the open graph protocol, any URL can be treated just like a Facebook page. http://opengraphprotocol.org/ http://developers.facebook.com/docs/opengraph

The “open data” movement Linking Open Data project The goal is to extend the web by publishing various open data sets as RDF on the web and by setting RDF links between data items in different data sources. These RDF links then enable navigation from a data item within one data source to related data items within other sources using a semantic web browser. RDF links can also be followed by the crawlers of semantic web search engines, which may provide sophisticated search and query capabilities over crawled data. As query results are structured data and not just links to HTML pages, they can be used within other applications. http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData/

The “open data” movement http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData/

The “open data” movement Contains 4.7 billion triples, interlinked by around 142 million RDF links http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData/

Open linked data School of Electronics and Computer Science (ECS) at University of Southampton releases all public data in open linked data format Joyce Lewis, 13 July 2010 In what is believed also to be a world-first, ECS has become the UK’s first University department to release all its public data in open linked data format. In accordance with the spirit of the open linked data initiative, ECS has released all its own data for public reuse. This includes data about research papers in the EPrints archive (announced this in the official global rankings as one of the top ten in the world), people in the School, research groups, teaching modules, seminars and events, buildings and rooms. All public (RDF) data from rdf.ecs.soton.ac.uk and eprints.ecs.soton.ac.uk is now available and can be reused for any legal purpose, including derivative works and commercial use. The School has opted for a creative commons public domain (CC0) license to allow the data to be reused. Christopher Gutteridge, ECS Web Projects Manager, comments: “We believe that in the future this will become common practice for certain types of open data, and it is our responsibility to lead the way in setting the standards of best practice.” http://www.ecs.soton.ac.uk/about/news/3313

Open and linked data It's all semantics: open data, linked data and the semantic web Richard MacManus, ReadWriteWeb, 31 March 2010 Titti Cimmino put it nicely: Open Data is simply 'data on the web,' whereas Linked Data is a 'web of data.' However, the idea of Open Data is to turn it into Linked Data. As John S. Erickson pointed out, the first priority of Data.gov.uk (and its U.S. counterpart) is to publish lots of Open Data. The next step is to work towards linking it all up. This is already starting to happen. Answering a question I posed on Twitter, Kingsley Idehen confirmed that Data.gov.uk is currently a combination of Open Data and Linked Data. http://www.readwriteweb.com/archives/open_data_linked_data_semantic_web.php

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary. Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary. Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. 3. Timely. Data is made available as quickly as necessary to preserve the value of the data. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary. Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. 3. Timely. Data is made available as quickly as necessary to preserve the value of the data. 4. Accessible. Data is available to the widest range of users for the widest range of purposes. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary. Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. 3. Timely. Data is made available as quickly as necessary to preserve the value of the data. 4. Accessible. Data is available to the widest range of users for the widest range of purposes. 5. Machine processable. Data is reasonably structured to allow automated processing. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary. Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. 3. Timely. Data is made available as quickly as necessary to preserve the value of the data. 4. Accessible. Data is available to the widest range of users for the widest range of purposes. 5. Machine processable. Data is reasonably structured to allow automated processing. 6. Non-discriminatory. Data is available to anyone, with no requirement of registration. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary. Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. 3. Timely. Data is made available as quickly as necessary to preserve the value of the data. 4. Accessible. Data is available to the widest range of users for the widest range of purposes. 5. Machine processable. Data is reasonably structured to allow automated processing. 6. Non-discriminatory. Data is available to anyone, with no requirement of registration. 7. Non-proprietary. Data is available in a format over which no entity has exclusive control. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open data Open data principles December 7-8, 2007—30 open government advocates gathered to develop principles of open government data in California, resulting in 8 fundamental principles for open government data. Governments can become more effective, transparent, and relevant by embracing. 1. Complete. All public data is made available. Public data is data that is not subject to valid privacy, security or privilege limitations. 2. Primary. Data is as collected at the source, with the highest possible level of granularity, not in aggregate or modified forms. 3. Timely. Data is made available as quickly as necessary to preserve the value of the data. 4. Accessible. Data is available to the widest range of users for the widest range of purposes. 5. Machine processable. Data is reasonably structured to allow automated processing. 6. Non-discriminatory. Data is available to anyone, with no requirement of registration. 7. Non-proprietary. Data is available in a format over which no entity has exclusive control. 8. License-free. Data is not subject to any copyright, patent, trademark or trade secret regulation. Reasonable privacy, security and privilege restrictions may be allowed. http://wiki.opengovdata.org/index.php?title=OpenDataPrinciples

Open government The currents of our time Carl Malamud, Gov 2.0 Summit, 7-8 September 2010 If our government is to do the jobs with which we have entrusted it—if government is to ensure that the air we breathe and the water we drink are safe, or that every child is to be given a chance to flourish—if we are to accomplish these goals, the machinery of our government must be made to work properly... Our federal government spends $81.9 billion a year on Information Technology. Much of that is wasted effort. We build systems so badly, it is crippling the infrastructure of government. http://public.resource.org/currents/

RDFa tools https://addons.mozilla.org/en-US/firefox/addon/195085/

RDFa tools RDF/RDFa related tools RDFa distiller (extract pure RDF from HTML + RDFa) ‣ http://www.w3.org/2007/08/pyRdfa/ ‣ get RDF directly from http://example.com/sample.html using single address http://www.w3.org/2007/08/pyRdfa/extract?uri=http://example.com/sample.html RDF validator and grapher ‣ http://www.w3.org/RDF/Validator/ Google’s RDFa tutorial ‣ http://www.google.com/support/webmasters/bin/answer.py? hl=en&answer=146898 Operator plug in for Firefox ‣ https://addons.mozilla.org/en-US/firefox/addon/4106 DBpedia applications (try e.g. the relation finder) ‣ http://wiki.dbpedia.org/Applications OpenLink Data Explorer extension for Firefox ‣ https://addons.mozilla.org/en-US/firefox/addon/8062 List global namespaces and entities ‣ http://pingthesemanticweb.com/

Discovery using RDF links DBpedia applications DBpedia is RDF data extracted from the well structured wikipedia pages (13 million) ‣ open web page at: http://wiki.dbpedia.org/Applications ‣ select the “Relation Finder” application ‣ on the left hand side of the page enter two “entities” that are likely to have several mentions in wikipedia ‣ select “Find Relations” and watch the RDF links begin to match up to reveal interesting direct and indirect information about the entities ‣ explore some of the other DBpedia applications and determine if there is any relevance to your own work

SPARQL Exploring, mining, combining RDF triples using a simple query language ‣ requires a “SPARQL” endpoint as query engine to examine data and present results ‣ generic (using any data set) or specific (using a particular data set) available ‣ typical SPARQL query using dbpedia data set: PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT DISTINCT ?person FROM <http://dbpedia.org/> WHERE { ?person foaf:name ?name . GRAPH ?g1 { ?person a foaf:Person } GRAPH ?g2 { ?person a foaf:Person } FILTER(?g1 != ?g2) . } ‣ potentially extremely powerful search of many resources http://dbpedia.org/snorql/

The “open data” movement http://www.ted.com/talks/tim_berners_lee_the_year_open_data_went_worldwide.html

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Maximising Online Resource Effectiveness Workshop Session 7/8 Development strategy

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Maximising Online Resource Effectiveness Workshop Session 7/8 Development strategy — Presentation Transcript