Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Slide 1 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
© COPYRIGHT 2013 MARKLOGIC CORPORATION. ALL RIGHTS R...
Slide 2 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics is the future of Search is the future of S...
Slide 3 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Two Hemispheres, One Brain
Slide 4 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Two Hemispheres, One Brain
Triples:
 Highly structu...
Slide 5 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics is the future of Search is the future of S...
Slide 6 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
The MarkLogic Advantage
Search & Query
ACID Transa...
Slide 7 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Real Value From Big Data
Make The World More Secure
...
Slide 8 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics is the future of Search is the future of S...
Slide 9 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Dynamic Semantic Publishing
BBC Sports
 Size and Co...
Slide 10 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Dynamic Semantic Publishing
Slide 11 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Dynamic Semantic Publishing
Slide 12 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Dynamic Semantic Publishing: A Solution
 Store, ma...
Slide 13 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Dynamic Semantic Publishing: A Solution
 At query ...
Slide 14 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Dynamic Semantic Publishing: A Solution
 At query ...
Slide 15 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics Architecture
TRIPLE
XQY XSLT SQL SPARQL
G...
Slide 16 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Why Semantic Technologies?
 Triples are atomic – e...
Slide 17 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Why Semantics and Search?
 Many use cases need doc...
Slide 18 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics is the future of Search is the future of ...
Slide 20 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Rich Search Applications .. Made Richer
Rich Search...
Slide 21 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Rich Search Applications .. Made Richer
Name: John ...
Slide 22 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Search With Real-World Context
Slide 23 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
The World of Triples
Linked Open Data
(Free semanti...
Slide 24 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Triples from free-flowing text
assumed risk of
acqu...
Slide 25 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics is the future of Search is the future of ...
Slide 26 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics + Search [1]
Slide 27 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics + Search [2]
How do you deal with …
 Pro...
Slide 28 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Triples and Documents
Documents can contain triples...
Slide 29 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Triples and Documents
Triples can be annotated in d...
Slide 30 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Triples and Documents
Documents can contain triples...
import module namespace sem = "http://marklogic.com/semantics"
at "/MarkLogic/semantics.xqy";
sem:sparql('
SELECT ?country...
Slide 32 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics + Search [3]
 Combination queries – simp...
Slide 33 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Combination Query: Example
<SAR>
<title>Suspicious ...
Slide 34 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Combination Query: Example
<SAR>
<title>
Suspicious...
Slide 35 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Combination Queries
 SPARQL -centric:
 SPARQL wit...
Slide 36 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics is the future of Search is the future of ...
Slide 37 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics and Search – Use Cases
 Publishers and m...
Slide 38 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Semantics is the future of Search is the future of ...
Slide 39 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Search: Understand, Discover, Make decisions
Search...
Slide 40 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Understand, Discover, Make Decisions
Slide 41 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Understand, Discover, Make Decisions
http://www.marklogic.com/summit-series/
Slide 43 Copyright © 2013 MarkLogic® Corporation. All rights reserved.
Any Questions?
stephen.buxton@marklogic.com
2013 10-03-semantics-meetup-s buxton-mark_logic_pub
Upcoming SlideShare
Loading in …5
×

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

810 views

Published on

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

Published in: Technology
  • Be the first to comment

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

  1. 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. 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. 3. Slide 3 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Two Hemispheres, One Brain
  4. 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. 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. 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. 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. 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. 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. 10. Slide 10 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing
  11. 11. Slide 11 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Dynamic Semantic Publishing
  12. 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. 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. 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. 15. Slide 15 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics Architecture TRIPLE XQY XSLT SQL SPARQL GRAPH SPARQL
  16. 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. 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. 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. 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. 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. 21. Slide 22 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Search With Real-World Context
  22. 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. 23. Slide 24 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Triples from free-flowing text assumed risk of acquired by
  24. 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. 25. Slide 26 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Semantics + Search [1]
  26. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 39. Slide 40 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Understand, Discover, Make Decisions
  40. 40. Slide 41 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Understand, Discover, Make Decisions
  41. 41. http://www.marklogic.com/summit-series/
  42. 42. Slide 43 Copyright © 2013 MarkLogic® Corporation. All rights reserved. Any Questions? stephen.buxton@marklogic.com

×