Intro to the Semantic Web Landscape - 2011

What’s the trick? 1. Agreement on common terms and relationships 2. Incremental, flexible data structure 3. Good-enough modeling 4. Query interface tailored to the data model7 ©2011 Cambridge Semantics Inc. All rights reserved.

Semantic Web – 1st View • “The Semantic Web” – Link explicit data on the World Wide Web in a machine- readable fashion • …government data • …commercial data • …scientific data • …social data – In order to enable applications such as… • …targeted, semantic search • …data browsing • …automated agents World Wide Web : Web pages :: The Semantic Web : Data11 ©2011 Cambridge Semantics Inc. All rights reserved.

Semantic Web – 2nd View • “Semantic Web technologies” – A family of technology standards that ‘play nice together’, including: • Flexible data model • Expressive ontology language • Distributed query language – Drive enterprise applications, including: • Data integration & virtualization • Business intelligence • Large knowledgebases • … The technologies enable us to build applications and solutions that were not possible, practical, or feasible traditionally.12 ©2011 Cambridge Semantics Inc. All rights reserved.

A Common & Coherent Set of Technology Standards • A common set of technologies: – ...enables diverse uses – ...encourages interoperability • A coherent set of technologies: – …encourage incremental application – …provide a substantial base for innovation • A standard set of technologies: – ...reduces proprietary vendor lock-in – ...encourages many choices for tool sets13 ©2011 Cambridge Semantics Inc. All rights reserved.

2011: Where we are As technologies & tools have evolved, Semantic Web advocates have progressed through stages: Report on… Execute on… Semantic Web vision Initial experiments Experiments Technology standards Technology standards Software packages Software packages Proofs of concept Proofs of concept Initial production implementations 2nd, 3rd, … implementations— Initial production implementations network effect17 ©2011 Cambridge Semantics Inc. All rights reserved.

2011: Where we’re not Image from Trey Ideker via Enoch Huang Semantic Web technologies are not a ‘magic crank’ for discovering new drugs (or solving other problems, for that matter)!18 ©2011 Cambridge Semantics Inc. All rights reserved.

2011: Where we’re not (cont’d) “Ontology” vs. “ontology”? XML vs. RDF? Semantic Web vs. Linked Data? Data integration vs. reasoning vs. KBs RDFa vs. microformats vs. search vs. app. vs. microdata vs. development vs. … schema.org The Semantic Web still suffers from confusing and conflicting messaging, each of which claims it’s “correct”.19 ©2011 Cambridge Semantics Inc. All rights reserved.

2011: Where we’re not (cont’d) We don’t yet have standard solutions for privacy, trust, probability, and other elements of the Semantic Web vision.20 ©2011 Cambridge Semantics Inc. All rights reserved.

RDF is… A labeled, directed graph of relations between resources and literal values. • RDF graphs are collections of triples • Triples are made up of a subject, a predicate, and an object predicate subject object • Resources and relationships are named with URIs25 ©2011 Cambridge Semantics Inc. All rights reserved.

Example RDF triples • “Lee Feigenbaum works for Cambridge Semantics” Lee works for Cambridge Feigenbaum Semantics • “Lee Feigenbaum was born in 1978” Lee born in 1978 Feigenbaum • “Cambridge Semantics is headquartered in Massachusetts” Cambridge headquartered Massachusetts Semantics26 ©2011 Cambridge Semantics Inc. All rights reserved.

Why RDF? What’s different here? • The graph data structure makes merging data with shared identifiers trivial • Triples act as a least common denominator for expressing data • URIs for naming remove ambiguity – …the same identifier means the same thing28 ©2011 Cambridge Semantics Inc. All rights reserved.

Why RDF? Coping With Change Flexible Graph URIs for Agility Model naming On-the-fly The World Changes Traditionally: Change is costly Semantics: Change is cheap RDB 1 RDB 229 ©2011 Cambridge Semantics Inc. All rights reserved.

Why RDF? Add Meaning to Data With traditional technology: Cust ID Name Referred By Work Phone 29212 Travis Ember Janet Cassy Barbara Cassy 212-555-5001 Inside the 30012 Jessica Evalta Brian Meedly 617-555-2325 database 59235 Hector Samton Agatha Browne 732-555-8715 29212 Travis Ember Janet Cassy 212-555-5001 30012 Jessica Evalta Brian Meedly 617-555-2325 Outside the 59235 Hector Samton Agatha Browne 732-555-8715 database No one knows what these numbers and names mean!30 ©2011 Cambridge Semantics Inc. All rights reserved.

Why RDF? Add Meaning to Data With Semantic Web technology: name Text Person referred by Data Text description mobile phone Text name Travis Ember Person2912 referred by Data, Janet Cassy wherever it mobile appears phone 212-555-5001 The meaning always travels with the data31 ©2011 Cambridge Semantics Inc. All rights reserved.

What does RDF look like? • RDF is the model, for which there are several concrete syntaxes: – RDF/XML – standard, complex XML syntax – Turtle – common, textual, triples-oriented syntax • …currently being standardized by the RDF working group – N3 – more expressive superset of Turtle – N-Triples – textual, line-oriented, useful for streaming When writing RDF by hand and in many guides, examples, and discussions these days, you’ll see Turtle most often.32 ©2011 Cambridge Semantics Inc. All rights reserved.

A Bit of Turtle • Write a triple by writing its parts separated by spaces (subject predicate object) @prefix ex: <http://example.org/myvocab/> . @prefix geo: <http://geonames.example/> . ex:LeeFeigenbaum ex:employer ex:CambridgeSemantics . ex:LeeFeigenbaum ex:birthYear 1978 . ex:CambridgeSemantics ex:headquarters geo:BostonMA . geo:BostonMA ex:population 574000 .33 ©2011 Cambridge Semantics Inc. All rights reserved.

Why SPARQL? SPARQL lets us: • Pull information from structured and semi-structured data. • Explore data by discovering unknown relationships. • Query and search an integrated view of disparate data sources. • Glue separate software applications together by transforming data from one vocabulary to another. • Update RDF data in bulk38 ©2011 Cambridge Semantics Inc. All rights reserved.

Dealer 2Dealer 1 Dealer 3 Employee ERP / Budget Directory System Web EPA Fuel Efficiency Spreadsheet SPARQL Query Engine What automobiles get more than 25 miles per gallon and can be purchased at a dealer located within 10 miles of one of my employees? SELECT ?automobile WHERE { ?automobile a ex:Car ; epa:mpg ?mpg ; ex:dealer ?dealer . ?employee a ex:Employee ; geo:loc ?loc . ?dealer geo:loc ?dealerloc . FILTER(?mpg > 25 && geo:dist(?loc, ?dealerloc) <= 10) . } Web dashboard SPARQL query

The SPARQL 1.1 Landscape Includes • A query language – Now with aggregates, subqueries, property paths, negation, & more • An update language • An HTTP protocol for issuing SPARQL queries & updates • A REST protocol for reading/writing RDF data • A service description mechanism & vocabulary • Basic federated query extensions • Standard semantics for mixing query with reasoning40 ©2011 Cambridge Semantics Inc. All rights reserved.

From the explicit to the inferred • 3 pieces of the Semantic Web technology stack are about describing a domain well enough to capture (some of) the meaning of resources and relationships in the domain – RDF Schema – OWL – RIF Apply knowledge to data to get more data.41 ©2011 Cambridge Semantics Inc. All rights reserved.

RDF Schema is… • Elements of: – Vocabulary (defining terms) • I define a relationship called “prescribed dose.” – Schema (defining types) • “prescribed dose” relates “treatments” to “dosages” – (my prescribed dose is 2mg; therefore 2mg is a dosage) – Taxonomy (defining hierarchies) • Any “doctor” is a “medical professional” – (therefore Dr. Brown is a medical professional)43 ©2011 Cambridge Semantics Inc. All rights reserved.

OWL is… • Elements of ontology – Same/different identity • “author” and “auteur” are the same relation • two resources with the same “ISBN” are the same “book” – More expressive type definitions • A “cycle” is a “vehicle” with at least one “wheel” • A “bicycle” is a “cycle” with exactly two “wheels” – More expressive relation definitions • “sibling” is a symmetric predicate • the value of the “favorite dwarf” relation must be one of “happy”, “sleepy”, “sneezy”, “grumpy”, “dopey”, “bashful”, “doc”45 ©2011 Cambridge Semantics Inc. All rights reserved.

RIF is… • Standard representation for exchanging sets of logical and business rules • Logical rules – A buyer buys an item from a seller if the seller sells the item to the buyer – A customer becomes a "Gold" customer as soon as his cumulative purchases during the current year top $5000 • Production rules – Customers that become "Gold" customers must be notified immediately, and a golden customer card will be printed and sent to them within one week – For shopping carts worth more than $1000, "Gold" customers receive an additional discount of 10% of the total amount52 ©2011 Cambridge Semantics Inc. All rights reserved.

R2RML is… An RDF vocabulary for specifying mappings from relational data to RDF data (and SPARQL). The following R2RML slides are courtesy of Alex Miller: http://www.slideshare.net/alexmiller/releasing-relational-data-to-the-semantic-web-763472756 ©2011 Cambridge Semantics Inc. All rights reserved.

Linked Data is… • A simple set of 4 guidelines for publishing RDF data on the Web (over HTTP) – Developed by Tim Berners-Lee in 2006 1. Use URIs as names for things • Globally unique identity 2. Use HTTP URIs • Everyone has a Web browser/client 3. When someone looks up a URI, provide useful information • …in the form of RDF data 4. Include links to other URIs • Foster discovery of additional information62 ©2011 Cambridge Semantics Inc. All rights reserved.

RDFa Example My name is Manu Sporny and you can give me a ring via 1-800-555-0155. <img rel="image" src="http://manu.sporny.org/images/manu.png" /> I have a <a rel="foaf:weblog" href="http://manu.sporny.org/">blog</a>. Example courtesy of Manu Sporny: http://manu.sporny.org/2011/rdfa-lite/69 ©2011 Cambridge Semantics Inc. All rights reserved.

Types of RDF Tools • Triple stores – Built on relational database—increasingly less common – Native RDF store • Development libraries • Full-featured application servers Most RDF tools contain some elements of each of these.74 ©2011 Cambridge Semantics Inc. All rights reserved.

Finding RDF Tools • Community-maintained lists – http://esw.w3.org/topic/SemanticWebTools • Emphasis on large triple stores – http://esw.w3.org/topic/LargeTripleStores • Michael Bergman’s Sweet Tools searchable list: – http://www.mkbergman.com/?page_id=325 • Community forums: – http://answers.semanticweb.com – #swig on irc.freenode.net – semantic-web@w3.org75 ©2011 Cambridge Semantics Inc. All rights reserved.

Types of SPARQL Tools • Query engines – Things that can run queries – Most RDF stores provide a SPARQL engine • Query rewriters – E.g. to query relational databases (more later) • Endpoints – Things that accept queries on the Web and return results • Client libraries – Things that make it easy to ask queries76 ©2011 Cambridge Semantics Inc. All rights reserved.

Finding SPARQL Tools • Community-maintained list of query engines – http://esw.w3.org/topic/SparqlImplementations • Publicly accessible SPARQL endpoints – http://esw.w3.org/topic/SparqlEndpoints • Michael Bergman’s Sweet Tools searchable list: – http://www.mkbergman.com/?page_id=325 • Community forums: – http://answers.semanticweb.com – #swig on irc.freenode.net – semantic-web@w3.org77 ©2011 Cambridge Semantics Inc. All rights reserved.

OWL Tools and Infrastructure • Editors/environments – Protégé, TopBraid, Oiled, Ontotrack, … • Reasoning systems – Pellet, FaCT++, Hermit, Racer, CEL, … • Reasoning integrated into RDF databases – OWLIM, Oracle RDF, Stardog, Virtuoso78 ©2011 Cambridge Semantics Inc. All rights reserved.

What about… everything else? Standards don’t yet exist, but many tools exist to derive RDF and/or run SPARQL queries against other sources of data.81 ©2011 Cambridge Semantics Inc. All rights reserved.

Semantic Web In Use: Social Data • People, relationships – Friend Of A Friend (“FOAF”) – foaf:knows – Self-published or site-published (LiveJournal, hi5, …) • Blogs, discussion forums, mailing lists – Semantically Interlinked Online Communities (“SIOC”) – Plug-ins for popular blogging & CMS platforms • Calendars, vCards, reviews, … – One-offs87 ©2011 Cambridge Semantics Inc. All rights reserved.

Semantic Web In Use: Enterprises on the Web • Thesis: Describe your business more precisely and drive more (and better) traffic to your site • Example: NYTimes publishes their article classification scheme as linked data • Example: Best Buy, Overstock.com use RDFa to annotate product listings90 ©2011 Cambridge Semantics Inc. All rights reserved.

Semantic Web In Use: Inside the Enterprise • Many and Varied Applications Across Industries – Health care and pharma • integration, classification, ontologies – Oil & Gas • integration, classification – Finance • structured data, ontologies, XBRL – Publishing • metadata – Libraries & museums • metadata, classification – IT • rapid application development & evolution92 ©2011 Cambridge Semantics Inc. All rights reserved.

Targeting High-Potential Opportunities in Pharma ... Territory Profile Preferred Regional targets Analyst Per-analyst relevance filter Universe of considered opportunities High-potential opportunities Mobile device93 ©2011 Cambridge Semantics Inc. All rights reserved.

Delivering Dynamic, Data-driven Websites “publishing stack is a great innovation for the BBC as dynamicthe first to The development of this new high-performance we are semantic use this technology on such a high-profile site. It also puts us at thecutting edge of development for the next phase of the Internet, Web 3.0.94 ©2011 Cambridge Semantics Inc. All rights reserved.

Semantic Web In Use: Government data – Since January 2010, 2,500 (large) datasets published as Linked Data – Since May 2009, 250,000 (smaller) datasets published (CSV, XML, …) – RPI project to convert datasets to Linked Data95 ©2011 Cambridge Semantics Inc. All rights reserved.

Where do Semantic Web technologies shine? • These are horizontal, enabling technologies. • But they apply particularly well to problems with these characteristics: – Heterogeneous data from multiple, diverse sources • Increasing reliance on connections within this data – Rapidly changing information needs – Significant early-mover advantage – Cross-organizational collaboration – Large amounts of data that would benefit from classification97 ©2011 Cambridge Semantics Inc. All rights reserved.

Getting Started with Semantic Web technologies • Goal: quick tactical wins on the path to large strategic value • Be sure to consider the operational ramifications – Who does what differently? • Ideal Semantic Web projects/applications have an incremental path towards broad deployment that generates demonstrable value along the way99 ©2011 Cambridge Semantics Inc. All rights reserved.

Choose practical, enterprise-ready tools • Look beyond the core Semantic Web capabilities and consider: – integration with existing enterprise systems – development & extension models – deployment, logging, maintenance, backup – tooling – user experience If you choose to build new components and assemble existing components together, it’s quite likely you’ll end up reinventing the wheel.100 ©2011 Cambridge Semantics Inc. All rights reserved.

Plan for Acquiring Expertise • What level of expertise is necessary? – Technologies only? – Technologies + API? – Technologies + tooling? – Tooling only? – … • How will we acquire the expertise? – In-house (and if so, how?) – Vendor services – 3rd-party services – Open-source community101 ©2011 Cambridge Semantics Inc. All rights reserved.

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Intro to the Semantic Web Landscape - 2011

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