• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Intro to the Semantic Web Landscape - 2011
 

Intro to the Semantic Web Landscape - 2011

on

  • 7,821 views

An introduction to the Semantic Web landscape as it stands near the end of 2011. Includes an introduction to the core technologies in the Semantic Web technology stack. ...

An introduction to the Semantic Web landscape as it stands near the end of 2011. Includes an introduction to the core technologies in the Semantic Web technology stack.

This material was presented at the November, 2011, Cambridge Semantic Web meetup.

Statistics

Views

Total Views
7,821
Views on SlideShare
5,077
Embed Views
2,744

Actions

Likes
15
Downloads
0
Comments
0

26 Embeds 2,744

http://www.cambridgesemantics.com 1334
http://projeliseu.blogspot.com.br 1136
http://smashingreader.com 70
http://paper.li 66
http://projeliseu.blogspot.com 46
http://projeliseu.blogspot.pt 20
http://projeliseu.blogspot.ru 12
http://www.projeliseu.blogspot.com.br 11
https://zen.myatos.net 9
http://projeliseu.blogspot.com.es 6
http://www.linkedin.com 5
http://mhopkinsdublin.tumblr.com 5
http://www.techgig.com 4
http://projeliseu.blogspot.co.uk 3
http://webcache.googleusercontent.com 3
http://127.0.0.1:9080 2
http://projeliseu.blogspot.no 2
http://192.168.10.8:9091 2
http://www.diffbot.com&_=1360862024813 HTTP 1
http://localhost:8080 1
http://projeliseu.blogspot.it 1
http://aimprosoft.com.ua:9091 1
http://projeliseu.blogspot.se 1
http://projeliseu.blogspot.com.ar 1
http://projeliseu.blogspot.fr 1
https://twitter.com 1
More...

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • This initial example shows how a Semantic Web approach differs from both traditional search as well as siloed databases.
  • Search gives lots of potential hits, but no targeted results. It requires a large investment to manually sort through the hits to see if there are any concrete results within them.
  • Search within a specific domain is a bit better, but shares the same basic limitations.
  • This is probably the most common way to find answers – look in specific databases. As soon as a problem spans multiple databases, however, you run into the silo problem: you need to ask part of the question against database A, part against database B, and manually figure out how to combine the results from both to get an answer to the overall question. This is magnified if there are 3, 5, or 20 databases involved in getting an answer.
  • With a Semantic Web approach, the siloes are broken down, the data is linked together, and a single query can result in a targeted list of specific results.
  • One of the goals of this tutorial is to de-mystify the all of the names of technologies, tools, projects, etc. that swirl around the Semantic Web story.And since I saw that as I researched this presentation, everyone seems to like this particular Gary Larson cartoon, it behooved me to include it.
  • Different nuances, but the same actual thing. Still, you can often tell a lot about someone’s view of Semantic Web based on the terms they choose to you to describe it. Linked Data Web has been – relatively speaking – successful in gaining traction.
  • This is the ultimate vision as per the original Scientific American article. Referred to last week as the “top-down approach”.
  • Many of the people that have been building the technologies, standards, and tools are doing so with these ends in mind. They have (disruptive, game-changing) problems today and these technologies provide a way to solve them today.
  • http://www.flickr.com/photos/reverendsam/2367569306/The good – emphasize the importance of the foundational layers (URIs and RDF) ; emphasizes the long-term roadmap/vision of what’s needed for the Semantic WebThe bad – implies that perhaps things can’t be taken serious until all the pieces are in place ; implies an order to the research ; various versions of the cake tell different stories (importance of XML, absence of query, lack of UI/application layer, …)Valentin Zacharias wrote about the “infamy” part of the layer cake here: http://www.valentinzacharias.de/blog/2007/04/ban-semantic-web-layer-cake.html
  • http://www.flickr.com/photos/reverendsam/2367569306/The good – emphasize the importance of the foundational layers (URIs and RDF) ; emphasizes the long-term roadmap/vision of what’s needed for the Semantic WebThe bad – implies that perhaps things can’t be taken serious until all the pieces are in place ; implies an order to the research ; various versions of the cake tell different stories (importance of XML, absence of query, lack of UI/application layer, …)Valentin Zacharias wrote about the “infamy” part of the layer cake here: http://www.valentinzacharias.de/blog/2007/04/ban-semantic-web-layer-cake.html
  • What’s been happening this whole time? (Between the introduction of the vision and today.) A lot of technology, standards, tool, and product development. Also, a lot of advocacy.
  • The Ontology/ontology dichotomy is captured well by Jim Hendler at http://www.cs.rpi.edu/%7Ehendler/presentations/SemTech2008-2Towers.pdf
  • Of course, these are all unsolved problems in the relational world as well, but they may be magnified with the highly distributed nature of the Semantic Web.
  • Definition.
  • Prescriptive.
  • Descriptive.
  • Formal.
  • The first is as opposed to relational tables or XML schemas where the schema needs to be explicitly adjusted to accommodate whatever data is being merged.The second is due to the expressivity of the model – can handle lists, trees, n-ary relations, etc.The third is as opposed to table & column identifiers or XML attribute names.
  • (This slide best told with animation in the original PowerPoint.)The Semantic Web paradigms allows new and updated data to be brought “into the fold” incrementally, without starting over. This makes it particularly amenable to changing requirements.
  • Main message: With relational technology, you lose the meaning of the data as soon as it exits the database – and so you end up hard-coding the knowledge of what the data means throughout every part of a software application. This is very error-prone and means it’s extremely tough to change anything.
  • Main message: With semantics, the data always travels with its meaning, and the data looks the same inside and outside the database.
  • Definition.
  • Prescriptive.
  • Descriptive.
  • Descriptive (part 2). This is leagues ahead of the situation with SQL! Major deployment help on the Web.
  • Definition.
  • Definition.
  • We call this “semantic data virtualization”.Databases that traditionally manage enterprise data are IT artifacts.They’re crafted by IT, for IT: asking scientists or other business domain experts to understand a relational model with scores of tables, IDs, key/value tables, unused columns, etc. is completely unrealistic.The semantic model is a conceptual model. It eschews IDs, keys, etc. in favor of concepts and relationships expressed/expressible in human language. This is reflected in software that is built with Semantic Web data. This means that when a researcher is linking their results spreadsheet, they’re dealing only in concepts that they’re familiar with (trades, accounts, settlements, securities, etc.). And that in turn means that this approach works regardless of whatever spreadsheet layout a particular collaborator is using: researchers can continue using their current spreadsheets, with no change.
  • Definition.
  • Courtesy W3C SWEO group, http://linkeddata.org/docs/eswc2007-poster-linking-open-data.pdf
  • Also see examples later in this deck – Semantic Web In Use – would be nice to have an example of RDFa markup
  • Possible answers: Few people are driven by data ownership, data portabilityPeople are drawn to specific sitesPeople _want_ to segment their online profiles (c.f. Facebook vs. LinkedIn)Drupal—which runs 1% of the world’s Web sites—is on the leading edge of adoption of the Semantic Web for content-driven sites. Drupal 7 exposes the semantics of Drupal sites’ natural structures to Google/Yahoo! with RDFa. Also modules for SIOC and Facebook OGP.
  • The key point here is that though FB published this protocol, it relies on open Semantic Web standards (RDFa) that anyone else can consume. The same semantics allow people to link the “Like” button to the type of artifact being liked (movie, here) and also can allow search engines to give more structure, query engines to find more data, etc.
  • Image courtesy of http://bio2rdf.org/ .Scientific data makes up a significant portion of the current Linked Data Web. This is information on proteins and genes, pathways, and sequences, chemistry and genetics, … This diagram shows some of the information available and how its linked together. Nodes are sized according to their quantity of data, and links are sized according to the quantity of links.
  • Google (Rich Snippets) and Yahoo! (originally Search Monkey) consume semantic markup to enhance search listings.
  • http://searchnewscentral.com/20110207129/Technical/rdfa-the-inside-story-from-best-buy.html
  • Many enterprise uses of Semantic Web / Linked Data are highlighted at: http://www.w3.org/2001/sw/sweo/public/UseCases/
  • Question: Where in this scenario do you think Semantic Web concepts and technologies are being employed? What would the alternative be?Answers: integrating data to get as large a universe as possible; rules and reasoning to intelligently filter the data
  • Combine manual tagging with ontology-driven reasoning and ontology-driven dynamic aggregation (700 index pages, more than the rest of the sports site combined) to produce a dynamic, cross-indexed, cross-linked, useful site for the World Cup.What is the semantic value here? * Produce an information rich site at many levels of aggregation (player, team, geography, group, …) without employing a large fleet of editors to curate the site’s _content_. Instead, maintain an ontology and provide a content tagging process. * Use the ontology to help automate the tagging process (forward-chaining inference based on taxonomies)For more details:http://www.bbc.co.uk/blogs/bbcinternet/2010/07/bbc_world_cup_2010_dynamic_sem.html http://www.bbc.co.uk/blogs/bbcinternet/2010/07/the_world_cup_and_a_call_to_ac.html
  • Other governments with similar efforts. Australia, Sweden,New Zealand, … , various local governments

Intro to the Semantic Web Landscape - 2011 Intro to the Semantic Web Landscape - 2011 Presentation Transcript

  • The Semantic Web Landscape A Practical IntroductionContact:Lee Feigenbaumlee@cambridgesemantics.comVP TechnologyCo-chair, W3C SPARQL Working Group ©2011 Cambridge Semantics Inc. All rights reserved.
  • Example: Alzheimer’s Drug Discovery What genes are involved in signal transduction and are related to pyramidal neurons?2 ©2011 Cambridge Semantics Inc. All rights reserved.
  • General search: 223,000 hits, 0 results3 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Domain-limited search: Still 2,580 potential results4 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Specific databases: Too many silos!5 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Linked Scientific Data: 32 targeted results6 ©2011 Cambridge Semantics Inc. All rights reserved.
  • 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.
  • WHAT IS THE SEMANTIC WEB?8 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Names9 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Branding • Semantic Web • Web of Data • Giant Global Graph • Data Web • Web 3.0 • Linked Data Web • Semantic Data Web • Enterprise Information Web10 ©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.
  • The (In)Famous Layer Cake14 ©2011 Cambridge Semantics Inc. All rights reserved.
  • The (In)Famous Layer Cake15 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Semantic Web Technology Timeline 1999 2001 2004 2007 2008 2011 RIF16 ©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.
  • What do Semantic Web solutions look like?21 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RDF is… Resource Description Framework22 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RDF is… The data model of the Semantic Web.23 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RDF is… A flexible data model that features unambiguous identifiers and named relations between pairs of resources.24 ©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.
  • Triples connect to form graphs Lee works for Cambridge Feigenbaum Semantics headquartered born in lives in 1978 Massachusetts capital Boston27 ©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.
  • SPARQL is… SPARQL Protocol And RDF Query Language34 ©2011 Cambridge Semantics Inc. All rights reserved.
  • SPARQL is… The query language of the Semantic Web.35 ©2011 Cambridge Semantics Inc. All rights reserved.
  • SPARQL is… A SQL-like language for querying sets of RDF graphs.36 ©2011 Cambridge Semantics Inc. All rights reserved.
  • SPARQL is… A simple protocol for issuing queries and receiving results over HTTP. So… Every SPARQL client works with every SPARQL server!37 ©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.
  • RDFS is… RDF Schema42 ©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.
  • WOL OWL is… Web Ontology Language44 ©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.
  • OWL: Rich Class Definitions • A class is a (named) collection of things with similar attributesImage courtesy of Fabien Gandon46 ©2011 Cambridge Semantics Inc. All rights reserved.
  • OWL: Rich Class Definitions • A class is a (named) collection of things with similar attributesImage courtesy of Fabien Gandon47 ©2011 Cambridge Semantics Inc. All rights reserved.
  • OWL: Rich Class Definitions • A class is a (named) collection of things with similar attributesImage courtesy of Fabien Gandon48 ©2011 Cambridge Semantics Inc. All rights reserved.
  • OWL: Rich Class Definitions49 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Why Ontologies? Put Data Within Reach of Domain Experts High-fidelity mappings make data reusable for many situations50 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RIF is… Rules Interchange Format51 ©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.
  • Fantasy Land Architecture Ontology / + Schema Custom Custom Custom Custom Custom Custom UI UI UI UI UI UI53 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Reality Internet DB2 XML LDAP Oracle Directory RDB Custom Custom Custom Custom Custom Custom UI UI UI UI UI UI54 ©2011 Cambridge Semantics Inc. All rights reserved.
  • R2RML is… Relational to RDF Mapping Language55 ©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.
  • GRDDL is… Gleaning Resource Descriptions from Dialects of Language60 ©2011 Cambridge Semantics Inc. All rights reserved.
  • GRDDL is… A method for authoritatively getting RDF data from XML and XHTML documents.61 ©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.
  • The LOD Cloud, 200763 ©2011 Cambridge Semantics Inc. All rights reserved.
  • The LOD Cloud, 200864 ©2011 Cambridge Semantics Inc. All rights reserved.
  • The LOD Cloud, 200965 ©2011 Cambridge Semantics Inc. All rights reserved.
  • LOD, 201166 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RDFa is… RDF in Attributes67 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RDFa is… A collection of HTML attributes that allow RDF to be embedded directly in Web pages.68 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RDFa Example <p vocab="http://schema.org/" prefix="foaf: http://xmlns.com/foaf/0.1/" about="#manu" typeof="Person"> My name is <span property="name">Manu Sporny</span> and you can give me a ring via <span property="telephone">1-800-555-0155</span>. <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>. </p> Example courtesy of Manu Sporny: http://manu.sporny.org/2011/rdfa-lite/69 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Why RDFa? • Don’t Repeat Yourself (DRY) • In-context metadata (copy & paste) • Authoritative (no screen scraping)70 ©2011 Cambridge Semantics Inc. All rights reserved.
  • RDFa in action71 ©2011 Cambridge Semantics Inc. All rights reserved.
  • SEMANTIC WEB LANDSCAPE TODAY72 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Semantic Web Tools In 2011, there are a wide variety of open-source and commercial Semantic Web tools available.73 ©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.
  • Visualizing and Publishing Vocabularies79 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Reusable, public ontologies FOAF The Event Ontology Measurement Units Ontology80 ©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.
  • LDAP Directories Squirrel RDF http://jena.sourceforge.net/SquirrelRDF/82 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Excel spreadsheets Anzo for Excel http://www.cambridgesemantics.com/products/anzo_for_excel83 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Web-based data sources Virtuoso Sponger Cartridges http://virtuoso.openlinksw.com/dataspace/dav/wiki/Main/VirtSponger84 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Unstructured Text Calais http://www.opencalais.com/85 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Unstructured Text Zemanta Web Service http://developer.zemanta.com/86 ©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.
  • Social Data Example • Facebook Open Graph Protocol88 ©2011 Cambridge Semantics Inc. All rights reserved.
  • Semantic Web In Use: Scientific Data May 12, 2009 8989 ©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.
  • Measurable Results • 30% increase in search-engine traffic • 15% increase in click-through-rate for search ads91 ©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.
  • TAKE-AWAY ADVICE96 ©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 Don’t boil the ocean.98 ©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.
  • Thanks & Discussion • I’m always happy to field questions & engage in discussion: lee@cambridgesemantics.com102 ©2011 Cambridge Semantics Inc. All rights reserved.