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2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
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2013 10-03-semantics-meetup-s buxton-mark_logic_pub

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MarkLogic Semantics - presented by Stephen Buxton at Lotico Semantics Meetup 2013-10-03 …

MarkLogic Semantics - presented by Stephen Buxton at Lotico Semantics Meetup 2013-10-03
See http://www.meetup.com/semweb-25/events/125214542/

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  • I'm Stephen Buxton, Director of Product Management for Search and Semantics at MarkLogic.
  • This analogy breaks down later in the talk – as if we took a spoon and mixed triples and documents.
  • This analogy breaks down later in the talk – as if we took a spoon and mixed triples and documents.
  • I'm Stephen Buxton, Director of Product Management for Search and Semantics at MarkLogic.
  • Data Model is XMLLanguage is XQuery
  • MarkLogic is a Major Player in the Search world – we expect to be a Major Player in the Semantics world.
  • I'm Stephen Buxton, Director of Product Management for Search and Semantics at MarkLogic.
  • The BBC has created what they’ve called “Dynamic Semantic Publishing”, that combines documents and semantics to let them achieve great things in their Olympics coverage . But interest in semantics – and the combination of documents and semantics – goes across all verticals. Triples are the most granular way to store information, which makes them very simple to manage and combine – you have a bucket of facts, and when you find more facts you just throw them in the bucket. They’re a natural choice for many kinds of metadata and real-world facts, and since there are a bunch of standards around triples it’s easy to share data – the semantic web (and Open Linked Data Web) mean there are lots of triples around – we’ve created this demo using only documents from MarkMail and facts that are available out on the webReal-world facts from the Open Data Web: Events, foaf, GeonamesSources:http://www.ontotext.com/publishing Jem's blog posts: http://www.bbc.co.uk/blogs/bbcinternet/2010/07/bbc_news_redesign_telling_the.htmlhttp://www.bbc.co.uk/blogs/bbcinternet/2012/04/sports_dynamic_semantic.htmlJem's slides, including REST API and Ontologieshttp://www.slideshare.net/JemRayfield/dsp-bbcjem-rayfieldsemtech2011Jem's slides from MarkLogic World 2012http://speakerdeck.com/u/jemrayfield/p/marklogic-world-2012-bbc-dsp-jem-rayfield
  • How have we extended our Enterprise NoSQL approach with Semantics?At the STORAGE LAYER we are capable of scaling up and have all the capabilities you know to be “Enterprise” including but not limited to replication, failover, backup and recovery, transactional support and more. Those same enterprise features are available for the Triple Store. As you know, this is very different from open source approaches.The next layer are all of our INDEXES. Some of those indexes are for full text search, range indexes, geospatial indexes and reverse query indexes for alerting. Now we have added a TRIPLES INDEX and a TRIPLES CACHE to store triples in memory for efficient retrieval. A few points here worth noting:All of our indexes are designed to work together allowing organizations to do look-ups against any combination of them.We store and index our triples in 3 orders which allow us to optimize queries that use the triples. (How fast is this?)Our triples cache is a different feature that other triple stores don’t have. With MarkLogic, it’s not necessary to have all of your Triples in memory. They can be swapped in and out of the cache. Users are not constrained by physical memory limits. We optimize performance with our index and cache.At the Query Layer, we have added native SPARQL support. User can compose queries is SPARQL only or powerful combination queries where part of the query could be written in SPARQL and run against the Triple Store while another part of the query could be XQUERY or XSLT and query documents. (SQL can be used to query data.) It’s this powerful combination of results – documents, data and facts that are returned and can be used at the application layer - that’s groundbreaking. At the server layer we’ve added REST APIs to do SPARQL and GRAPH operations allowing you to build SPARQL endpoints, for example. These end points represent the addresses where the are sets of triples are returned from a SPARQL Query that can be used in search applications. But again, the combination of documents, facts and data, all presented “in context” as part of search results is what makes this so powerful. No one has this approach in an Enterprise grade technology. By the way, the MarkLogic Content Pump has been extended do to bulk loading of triples. Any questions?
  • Why does anyone use Semantic Technologies?Triples are the ultimate in schemaless – each triple represents just one atomic fact.It's very easy to combine sets of triples from different sources and query across them – you just drop all the triples into the same bucket.Triples are a natural choice for some kinds of facts, wuch as metadata and real-world facts (the capital of Qatar is Doha).Because RDF and SPARQL are standards, there tons of tools and skills and data sets out there.The Open Linked Data Web is the basis for the Semantic Web vision – you can find tons of data freely available on the web, mostly in RDF – everything from dbpedia (the triples version of wikipedia - http://dbpedia.org/About) to the CIA World Factbook (http://data-gov.tw.rpi.edu/wiki/CIA_World_Factbook) to data about drugs and clinical trials (http://www.w3.org/wiki/HCLSIG/LODD/Data).It's trivial to pull in billions of facts and combine them with your own facts, metadata, and facts-derived-from-docuemnts.
  • Why does anyone use Semantic Technologies?Triples are the ultimate in schemaless – each triple represents just one atomic fact.It's very easy to combine sets of triples from different sources and query across them – you just drop all the triples into the same bucket.Triples are a natural choice for some kinds of facts, wuch as metadata and real-world facts (the capital of Qatar is Doha).Because RDF and SPARQL are standards, there tons of tools and skills and data sets out there.The Open Linked Data Web is the basis for the Semantic Web vision – you can find tons of data freely available on the web, mostly in RDF – everything from dbpedia (the triples version of wikipedia - http://dbpedia.org/About) to the CIA World Factbook (http://data-gov.tw.rpi.edu/wiki/CIA_World_Factbook) to data about drugs and clinical trials (http://www.w3.org/wiki/HCLSIG/LODD/Data).It's trivial to pull in billions of facts and combine them with your own facts, metadata, and facts-derived-from-docuemnts.
  • I'm Stephen Buxton, Director of Product Management for Search and Semantics at MarkLogic.
  • 1st point – We have a rich search application – there’s a lot of information2nd point – But we can we can make a rich search application even richer – The application knows about sources of data for Hadoop. It reaches out to those sources and dynamically retrieves the information wrapping even more context about your search.
  • Cf. Google Knowledge Graph
  • And since we have facts stored about the people, when we search for people affiliated with IBM, even though the email address does not have IBM in the email domain, because we have a fact stored about Sam Ruby (he works at IBM), this is what is returned in the search. Our semantic Application was informed by facts.Cf Bob duCharme's talk at semtechbiz 2013 San Francisico
  • The entity extraction vendors are getting very good – not only can they pull entities out of free-flowing text, they can pull out facts ("events").
  • I'm Stephen Buxton, Director of Product Management for Search and Semantics at MarkLogic.
  • [SB: Need something here that says "and if you're only interested in Triples, now you can embed them in documents"]
  • .. if you're only interested in Triples, now you can embed them in documents
  • I'm Stephen Buxton, Director of Product Management for Search and Semantics at MarkLogic.
  • I'm Stephen Buxton, Director of Product Management for Search and Semantics at MarkLogic.
  • Attribute: Joe Rockwell, consultant
  • Transcript

    • 1. Slide 1 Copyright © 2013 MarkLogic® Corporation. All rights reserved. © COPYRIGHT 2013 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. Stephen Buxton Lotico meetup, NYC October 3rd, 2013 Semantics is the future of Search is the future of Semantics
    • 2. Slide 2 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics is the future of Search is the future of Semantics  Introduction: what does the title mean?  MarkLogic: who's that?  Imagine a World with Search AND Semantics  Rich Search Applications … plus Semantics  Semantics Applications … plus Search  Bringing it all together: Use Cases  Where To Next?
    • 3. Slide 3 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Two Hemispheres, One Brain
    • 4. Slide 4 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Two Hemispheres, One Brain Triples:  Highly structured  Atomic  Do one thing well XML:  Flexible structure  Rich documents  Rich applications
    • 5. Slide 5 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics is the future of Search is the future of Semantics  Introduction: what does the title mean?  MarkLogic: who's that?  Imagine a World with Search AND Semantics  Rich Search Applications … plus Semantics  Semantics Applications … plus Search  Bringing it all together: Use Cases  Where To Next?
    • 6. Slide 6 Copyright © 2013 MarkLogic® Corporation. All rights reserved. The MarkLogic Advantage Search & Query ACID Transactions High Availability / Disaster Recovery Government-grade Security Semantics Elasticity Cloud Deployment Hadoop for Storage & Compute The Only Enterprise NoSQL Database
    • 7. Slide 7 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Real Value From Big Data Make The World More Secure Provide Access To Valuable Information Create New Revenue Streams Gain Insights to Increase Market Share Reduce Bottom Line Expense
    • 8. Slide 8 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics is the future of Search is the future of Semantics  Introduction: what does the title mean?  MarkLogic: who's that?  Imagine a World with Search AND Semantics  Rich Search Applications … plus Semantics  Semantics Applications … plus Search  Bringing it all together: Use Cases  Where To Next?
    • 9. Slide 9 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing BBC Sports  Size and Complexity:  # of athletes  # of teams  # of assets (match reports, statistics, etc.)  # of relations (facts)  Rich user experience  See information in context  Personalize content  Easy navigation  Intelligently serve ads (outside of UK)  Manageable  Static pages? Too many, too fast-changing  Limited number of journalists  Automate as much as possible The Challenge Goals
    • 10. Slide 10 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing
    • 11. Slide 11 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing
    • 12. Slide 12 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing: A Solution  Store, manage documents  Stories  Blogs  Feeds  Profiles  Store, manage values  Statistics  Full-Text search  Performance, scalability  Robustness  Metadata about documents  Tagged by journalists  Added (semi-)automatically  Inferred  Facts reported by journalists  Real-world facts from the Open Data Web Document Database Triple Store
    • 13. Slide 13 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing: A Solution  At query time, dynamically aggregate stories, blogs, feeds, images, profiles, results, statistics, videos for a particular concept such as "West Ham". (See Jem Rayfield, BBC, http://bbc.in/I1NdkB)  we are not publishing pages, but publishing content as assets which are then organized by the metadata dynamically into pages (John O'Donovan, BBC and PA) Document Database Triple Store
    • 14. Slide 14 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing: A Solution  At query time, dynamically aggregate stories, blogs, feeds, images, profiles, results, statistics, videos for a particular concept such as "Chelsea". (See Jem Rayfield, BBC, http://bbc.in/I1NdkB)  we are not publishing pages, but publishing content as assets which are then organized by the metadata dynamically into pages (John O'Donovan, BBC and PA) Document Database Triple Storewith
    • 15. Slide 15 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics Architecture TRIPLE XQY XSLT SQL SPARQL GRAPH SPARQL
    • 16. Slide 16 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Why Semantic Technologies?  Triples are atomic – easy to create, manage, combine  Semantic Web shares data as triples  A natural choice for metadata and real-world facts  .. and facts embedded in a document  Standards encourage tools and sharing  Graph model – easy to follow links  Ontologies – infer new facts Because …
    • 17. Slide 17 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Why Semantics and Search?  Many use cases need documents, triples, and data  One database means a simple, efficient, powerful architecture  Combination queries – query documents, triples, data in a single query – open up new possibilities Because …
    • 18. Slide 18 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics is the future of Search is the future of Semantics  Introduction: what does the title mean?  MarkLogic: who's that?  Imagine a World with Search AND Semantics  Rich Search Applications … plus Semantics  Semantics Applications … plus Search  Bringing it all together: Use Cases  Where To Next?
    • 19. Slide 20 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Rich Search Applications .. Made Richer Rich Search Application: • 60 million docs indexed • Links to email messages • Snippets about e-mail • Sender data • Facets • Search trends
    • 20. Slide 21 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Rich Search Applications .. Made Richer Name: John Smith Affiliation: IBM Timezone: PST Committer: Hadoop
    • 21. Slide 22 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Search With Real-World Context
    • 22. Slide 23 Copyright © 2013 MarkLogic® Corporation. All rights reserved. The World of Triples Linked Open Data (Free semantic facts available to anyone) Proprietary Semantic Facts (Facts and Taxonomies in your organization) SemanticWorld DocumentWorld Facts from Free-Flowing Text (Derived from semantic enrichment) MarkLogic Facts in Documents (Part of metadata or added with authoring tools)
    • 23. Slide 24 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Triples from free-flowing text assumed risk of acquired by
    • 24. Slide 25 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics is the future of Search is the future of Semantics  Introduction: what does the title mean?  MarkLogic: who's that?  Imagine a World with Search AND Semantics  Rich Search Applications … plus Semantics  Semantics Applications … plus Search  Bringing it all together: Use Cases  Where To Next?
    • 25. Slide 26 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics + Search [1]
    • 26. Slide 27 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics + Search [2] How do you deal with …  Provenance – what's the source? And its source? And so on ..  Reification – what's my confidence? Author? Date?  Bi-Temporal – two date ranges Answer questions like:  Which countries did Nixon visit?  .. before 1974?  .. only show me answers where I have at least 80% confidence  .. and the source is AP Newswire OR BBC
    • 27. Slide 28 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Triples and Documents Documents can contain triples <article> <meta> <title>Man bites dog</title> <sem:triple> <sem:subject>http://example.org/news/42</sem:subject> <sem:predicate>http://example.org/published</sem:predicate> <sem:object>2013-09-10</sem:object> </sem:triple> …
    • 28. Slide 29 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Triples and Documents Triples can be annotated in documents <source>AP Newswire</source> <sem:triple date="1972-02-21" confidence="100"> <sem:subject>http://example.org/news/Nixon</sem:subject> <sem:predicate>http://example.org/wentTo</sem:predicate> <sem:object>China</sem:object> </sem:triple> …
    • 29. Slide 30 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Triples and Documents Documents can contain triples <article> <meta> <title>Man bites dog</title> <sem:triple> <sem:subject>http://example.org/news/42</sem:subject> <sem:predicate>http://example.org/published</sem:predicate> <sem:object>2013-09-10</sem:object> </sem:triple> … Triples can be annotated in documents <source>AP Newswire</source> <sem:triple date="1972-02-21" confidence="100"> <sem:subject>http://example.org/news/Nixon</sem:subject> <sem:predicate>http://example.org/wentTo</sem:predicate> <sem:object>China</sem:object> </sem:triple> …
    • 30. import module namespace sem = "http://marklogic.com/semantics" at "/MarkLogic/semantics.xqy"; sem:sparql(' SELECT ?country WHERE { <http://example.org/news/Nixon> <http://example.org/wentTo> ?country } ', (), (), cts:and-query( ( cts:path-range-query( "//sem:triple/@confidence", ">", 80) , cts:path-range-query( "//sem:triple/@date", "<", xs:date("1974-01-01")), cts:or-query( ( cts:element-value-query( xs:QName("source"), "AP Newswire" ), cts:element-value-query( xs:QName("source"), "BBC" ) ) ) ) ) ) Which countries did Nixon visit?  .. before 1974?  .. only show me answers where I have at least 80% confidence  .. and the source is AP Newswire OR BBC
    • 31. Slide 32 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics + Search [3]  Combination queries – simple, easy, efficient, powerful  Query across triples, documents, data  Leverage context Answer questions like:  I have a partial match on a license plate number – a witness to a crime says it starts with ABC  Are there any incident reports around the time of the crime, around the location of the crime, that mention a black van?  If yes, show me the names and addresses of the license holders
    • 32. Slide 33 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Combination Query: Example <SAR> <title>Suspicious vehicle…Suspicious vehicle near stadium <date> <type> <threat> 2012-11-12Z observation/surveillance <type>suspicious activity <category>suspicious vehicle <location> <lat>37.497075 <long>-122.363319 <subject>IRIID <subject>IRIID <predicate> <predicate> isa value <triple> <triple> <object>license-plate <object>ABC 123 <description>A black van…A black van with license plate ABC 123 was observed parked behind the airport sign… </title> </date> </type> </type> </category> </threat> </lat> </long> </location> </subject> </subject> </predicate> </predicate> </object> </object> </description> </SAR> </triple> </triple> XML document – a SAR report
    • 33. Slide 34 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Combination Query: Example <SAR> <title> Suspicious vehicle… <date> 2012-11-12Z <type> <threat> suspicious activity <category> suspicious vehicle <location> <lat> 37.497075 <long> -122.363319 <description> A black van… <subject> <subject> <predicate> <object> IRIID IRIID isa value license-plate ABC 123<predicate> <object> observation/surveillance <type> <triple> <triple>
    • 34. Slide 35 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Combination Queries  SPARQL -centric:  SPARQL with XQuery built-in functions  SPARQL with a search argument  SPARQL with variable bindings  SPARQL with forest-ids  XQuery -centric: Inside an XQuery program:  sem:sparql( sparql query, search criteria )  cts:triples( subject, predicate, object , search criteria)  cts:triple-range-query( subject, predicate, object , [=,<,>] )
    • 35. Slide 36 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics is the future of Search is the future of Semantics  Introduction: what does the title mean?  MarkLogic: who's that?  Imagine a World with Search AND Semantics  Rich Search Applications … plus Semantics  Semantics Applications … plus Search  Bringing it all together: Use Cases  Where To Next?
    • 36. Slide 37 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics and Search – Use Cases  Publishers and media organizations look to use the combined Enterprise NoSQL database and triple store as a way to speed implementation of Dynamic Semantic Publishing.  Financial institutions query triples in the context of a document to manage Reference Data and understand risk.  Intelligence, law enforcement, fraud investigators and analysts are able to discover connections and patterns in facts and documents to find bad guys faster.  Procurement agents are creating decision support tools to rationalize purchasing decisions, vendors and bid management.  Pharmaceutical companies and governing organizations are using facts and documents together to assess risks and to decide which drug trials to invest in.
    • 37. Slide 38 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics is the future of Search is the future of Semantics  Introduction: what does the title mean?  MarkLogic: who's that?  Imagine a World with Search AND Semantics  Rich Search Applications … plus Semantics  Semantics Applications … plus Search  Bringing it all together: Use Cases  Where To Next?
    • 38. Slide 39 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Search: Understand, Discover, Make decisions Search Fetch documents Extract relevant facts Analyze Old Search Fetch facts, data, and documents in context Analyze and annotate Fetch supporting facts, data, and documents As needed New
    • 39. Slide 40 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Understand, Discover, Make Decisions
    • 40. Slide 41 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Understand, Discover, Make Decisions
    • 41. http://www.marklogic.com/summit-series/
    • 42. Slide 43 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Any Questions? stephen.buxton@marklogic.com

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