Semantic Wikis     Social Semantic Web In Action                    2011-03-25Specially Prepared for Tsinghua University A...
About Me: Jesse Wang 王(嘉)欣2
Who is Vulcan3
What does Vulcan do4
It all began with a vision…5
Now the Vision Continues as Project Halo6
Project Halo’s Focus Areas                                 • Automated User-Centered              AURA                 Rea...
Project Halo’s Goals       Address the core problems        in Knowledge Bases                       – scale             ...
Crowdsourcing for Better Knowledge Acquisition9
Wiki as a Crowdsourcing Tool               This distinguishes wikis from other publication tools11
Consensus in Wikis Comes from        Collaboration         – ~17 edits/page on average in           Wikipedia (with high ...
Software Support Makes Wikis Successful        Trivial to edit by anyone        Tracking of all changes, one-         st...
Success of Wikis14
Wikis are Great, But…                             Wiki Clock?15
How About Hidden Goodies in the Wiki?Wikipedia has articlesabout…      •… all cities      •… their populations      •… the...
Enters Semantics…     To answer questions like:     •   The female majors of top 10 cities,         sorted by population, ...
What is a Semantic Wiki      A wiki that has an underlying model of the       knowledge described in its pages.      To ...
Two Perspectives         Wikis for         Metadata         Metadata for         Wikis19
Characteristics of Semantic Wikis                                    Semantic Wikis                                       ...
List of Semantic WikisAceWiki                       Semantic MediaWiki - anArtificialMemory              extension to Medi...
Basics of Semantic Wikis        Still a wiki, with regular wiki features         – Category/Tags, Namespaces, Title, Vers...
SMW Markup Syntax                 Tsinghua is a university located in                   [[Has location::Beijing]], with   ...
Define Classes      On Page Beijing a city in [[Has             Beijing is             country::China]], with population ...
Database-style Query over Wiki Data        Example: Skyscrapers in China       higher than 50 stories, built before       ...
What is the Promise of Semantic Wikis? Semantic Wikis promise  Consensus over Data Combine low-expressivity  data author...
One Key Helpful Feature of Semantic Wikis                 Semantic Wikis are “Schema-Last”                    Databases re...
Semantic MediaWiki in 2010        Open source (GPL)        Well documented        Active mailing list        Commercia...
SMW Extensions         Data I/O        • Halo Extensions, Semantic Forms, Semantic Notification, …         Query and Brows...
Wikis Can Help Information Management         Research = Locate and Find Data ? Business Intelligence Finding Expertise...
Example I: KnowIT in Johnson & Johnson   Most Frequently Asked Questions: (J&J example)        –    What are the directio...
System Architecture                      39
Example II: Knowledge Encapsulation Framework Allow modelers to exploit the „information resources‟ they  have and discov...
42
43
Example 3: Ultrapedia – An Analytical Semantic Wikipedia        Ultrapedia: An SMW demo built to explore general knowledg...
Graph Views of the Acceleration Data
Dynamic Mapping and Charting
Information Discovery via Visualization52
Video: Semantic Wikis for A New Problem                               Increasing technical complexity →                   ...
Semantic Seahawks Football Wiki56
Based on Simple Templates and Forms57
Semantic Entertainment: Query Result  Highlight Reel                                              Commercial            ...
The Inspiration        We started with a        We built a        We now have an60
We CAN Build Applications (Fairly) Easily        With all the extensions of Semantic MediaWiki.           Data I/O       ...
Collaborative Proposal Management at BT with SMW+                                       Active Bid Viewer                 ...
Social Semantic Web Applications     Omitting x examples, y pictures and z lines of text…67
Case Study 2 and Demo: Project Management with SMW+                                            Automatically             ...
Vulcan Project Management Wiki (Story)
Vulcan Project Management Wiki (Task)70
Vulcan Project Management Wiki (Visualizations)71
Screenshot of a Sprint page             Data automatically generated via template queries on page               http://wik...
Requirements for Wiki “Developers”        One need not         – Write code like a hardcore programmer         – Design, ...
Effectiveness of SMW as a Platform Choice      Packaged Software      SMW + Extensions          Custom Development     ☺Ve...
Conclusions        Semantic MediaWiki+ (http://smwforum.ontoprise.com)         –   Open-source, growing semantic wiki sof...
Acknowledgement                  80
(End of Slides)     Backups starts here81
Case Study: Battle-space Luminary System        Discover when New Information represents a change in understanding of ent...
System Design        Wiki Configuration          – Semantic MediaWiki: Large developer community, active development, ope...
Sample Content Page84
Wiki Content Design        Use Templates to Ensure Consistent Look-and-Feel          – Templates Correspond to Ontology C...
Sample Visualizations86
Wikipedia for Porsches (Acceleration Data Example)     Information Need: All Porsche models that accelerate 0-      100kp...
More Porsche Acceleration Data in Wikipedia
Ultrapedia Main Page  Main Page
Semantics for Improved Wiki NavigationTree View Control       Abstract/Summary quick preview
The Porsche 996 Acceleration Table In Ultrapedia
Same Table as a Query
Dynamically-Generated Tables forfast?              Which Porsches accelerate                                        Querie...
Graph Views of the Acceleration Data
External Data via a Live Ebay Query
Linking to External Ebay Data
Photos in Mercedes-Benz E-class W212 Gallery Section          Wiki Articles as Data
Timelines from Data Production Timeline View               Volkswagen
Dynamic Mapping and Charting
Editing Wiki Data In Place                             Return
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Semantic Wiki: Social Semantic Web In Action:

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  • Of course once you have data, Ultrapedia can support data visualizations. This is a simple Flash-based chart widget based on the same Porsche 996 data, and included in Ultrapedia’s Porsche 996 page.It shows us that while acceleration varies dramatically, top speed and peak engine power remain fairly constant across models.The chart was specified manually with a query. There are of course a huge number of possible ways to chart a set of data, and most of these ways are uninteresting.In the Ultrapedia concept, we rely on article authors to specify interesting charts for their readers that will support the particular points in the article.
  • But, did you know that Uusikaupunki, Finland, is a major hub for Porsche manufacturing?Ultrapedia allows us to drill down to look at Finland’s contribution to Porsche production.
  • The problem we are going to solve is “find the 0-60 times of all Porsche cars in Wikipedia”This is a sample Wikipedia page for the Porshe 996, showing its acceleration times in a performance data table.This table is manually built – all the table data exists as constants in the table.
  • This is a Wikipedia page showing 0-60 times for the Porsche Cayenne.If we have to manually go through every Porsche model to assemble the 0-60 data for each model and type, this is going to take a while.A better idea is to treat Wikipedia like a database, and simply query it. Enter Ultrapedia.
  • This is the Ultrapedia home page.
  • First notice that Ultrapedia can leverage all the data it extracts from Wikipedia to support a much more helpful UI.For example, Ultrapedia adds a manufacturer-based navigation system on the side, and show explanatory popups. These kinds of UI tweaks aren’t possible with MediaWiki now, and are an important benefit of having the semantic data.
  • Remember that we want to find the 0-60 acceleration data for all Porsche models that Wikipedia knows about.Let’s start by looking at a query generated table on the Ultrapedia Porsche 996 page. For comparison, Ultrapedia also includes the original performance table from Wikipedia (above)
  • This is Ultrapedia’sPorsche 996 performance table, built by a query to the Ultrapedia database of Wikipedia-extracted data.Notice that it has the same information that the original static table has, this is because we scrape the data from the static table.This table is dyamically generated at each page load out of the extracted Wikipedia data, so it is always up to date.It is sortable and also accepts feedback and ratings on individual data items.
  • Now we can answer our question about 0-60 times across all Porsche models with one simple query in Ultrapedia. We can make this an Ultrapedia-only page – the page itself just 5 queries on it (one for each acceleration range).We could also do this as one big table but it’s easier to read as 5 smaller tables.All the data here flows from Wikipedia.
  • Of course once you have data, Ultrapedia can support data visualizations. This is a simple Flash-based chart widget based on the same Porsche 996 data, and included in Ultrapedia’s Porsche 996 page.It shows us that while acceleration varies dramatically, top speed and peak engine power remain fairly constant across models.The chart was specified manually with a query. There are of course a huge number of possible ways to chart a set of data, and most of these ways are uninteresting.In the Ultrapedia concept, we rely on article authors to specify interesting charts for their readers that will support the particular points in the article.
  • We can also use the data to dynamically link to other data sources. In this case we have configured the Ultrapedia Porsche 996 article to include a live ebay query to find out what the Porsche 996 sells for today…We access the ebay data through a web services interface.We can do this for arbitrary other web-service-accessible data sources, like amazon or geonames.In a government or enterprise context, we would link articles to supporting data from appropriate systems of record.
  • I don’t think I’ll be buying one… I think I’d rather send my daughter to college.
  • Pictures automatically get metadata, so Ultrapedia can deliver an iPod-like “cover flow” browsing experience with images to augment the table data. We could also embed images or videos in the tables.
  • Since Ultrapedia includes some simple internal logic about time, we can generate simple browsable timelines and use them in articles.Here we see a timeline of VW models.
  • But, did you know that Uusikaupunki, Finland, is a major hub for Porsche manufacturing?Ultrapedia allows us to drill down to look at Finland’s contribution to Porsche production.
  • Semantic Wiki: Social Semantic Web In Action:

    1. 1. Semantic Wikis Social Semantic Web In Action 2011-03-25Specially Prepared for Tsinghua University Alumni in greater Seattle area for centennial celebration
    2. 2. About Me: Jesse Wang 王(嘉)欣2
    3. 3. Who is Vulcan3
    4. 4. What does Vulcan do4
    5. 5. It all began with a vision…5
    6. 6. Now the Vision Continues as Project Halo6
    7. 7. Project Halo’s Focus Areas • Automated User-Centered AURA Reasoning and Acquisition System • Text book you can talk to • Semantic Inference with Large SILK Knowledge-base • Non-monotonic rule system / RIF • Semantic MediaWiki + SMW+ • Knowledge authoring with SMEs Plus other related semantic technologies and commercial efforts7
    8. 8. Project Halo’s Goals  Address the core problems in Knowledge Bases – scale – brittleness  Have high impact KB Effort (cost, people,…) Now Vulcan Future KB size (number of assertions, complexity…)8
    9. 9. Crowdsourcing for Better Knowledge Acquisition9
    10. 10. Wiki as a Crowdsourcing Tool This distinguishes wikis from other publication tools11
    11. 11. Consensus in Wikis Comes from  Collaboration – ~17 edits/page on average in Wikipedia (with high variance) – Wikipedia‟s Neutral Point of View  Convention – Users follow customs and conventions to engage with articles effectively12
    12. 12. Software Support Makes Wikis Successful  Trivial to edit by anyone  Tracking of all changes, one- step rollback  Every article has a “Talk” page for discussion  Notification facility allows anyone to “watch” an article  Sufficient security on pages, logins can be required  A hierarchy of administrators, gardeners, and editors  Software Bots recognize certain kinds of vandalism and auto- revert, or recognize articles that need work, and flag them for editors13
    13. 13. Success of Wikis14
    14. 14. Wikis are Great, But… Wiki Clock?15
    15. 15. How About Hidden Goodies in the Wiki?Wikipedia has articlesabout… •… all cities •… their populations •… their mayors •… the skyscrapersSo can I ask for a list ofthe world‟s 5 largestcities with a femalemayor?Or Skyscrapers inShanghai with 50+ floorsand built after 2000? 16
    16. 16. Enters Semantics… To answer questions like: • The female majors of top 10 cities, sorted by population, starting year, age… • All skyscrapers in China (Japan, Thailand,…) of 50 (40/60/70) floors or more, and built in year 2000 (2001/2002) and after, sorted by built year, floors…, grouped by cities, regions… • Median (average) base annual salary of CEOs of Fortune 100 companies in America (Europe, Asian,…) • All Porsche Vehicles Made in Germany that accelerate from 1-100 km/h less than 4 seconds • Sci-Fi movies made after year 2000 that cost less than $10M and gross more than $30M • A map showing where all Mercedes- Benz vehicles are manufactured • And many more17
    17. 17. What is a Semantic Wiki  A wiki that has an underlying model of the knowledge described in its pages.  To allow users to make their knowledge explicit and formal  Semantic Web Compatible Semantic Wiki18
    18. 18. Two Perspectives Wikis for Metadata Metadata for Wikis19
    19. 19. Characteristics of Semantic Wikis Semantic Wikis 20
    20. 20. List of Semantic WikisAceWiki Semantic MediaWiki - anArtificialMemory extension to MediaWiki thatWagn - Ruby on Rails-based turns it into a semantic wikiKiWi – Knowledge in a Wiki Swirrl - a spreadsheet-based semantic wiki applicationKnoodl – SemanticCollaboration tool and TaOPis - has a semantic wikiapplication platform subsystem based on Frame logicMetaweb - the software thatpowers Freebase TikiWiki CMS/Groupware integrates Semantic links as aOntoWiki core featureOpenRecord zAgile Wikidsmart - semanticallyPhpWiki enables Confluence 21
    21. 21. Basics of Semantic Wikis  Still a wiki, with regular wiki features – Category/Tags, Namespaces, Title, Versioning, ...  Typed Content (built-ins + user created, e.g. categories) – Page/Card, Date, Number, URL/Email, String, …  Typed Links (e.g. properties) – “capital_of”, “contains”, “born_in”…  Querying Interface Support – E.g. “[[Category:Member]] [[Age::<30]]” (in SMW)22
    22. 22. SMW Markup Syntax Tsinghua is a university located in [[Has location::Beijing]], with [[Has population::27,000]] students. In page "Property:Has location": In page "Property:Has population": [[Has type::Page]] [[Has type::number]]24
    23. 23. Define Classes  On Page Beijing a city in [[Has Beijing is country::China]], with population  One possible solution: [[Has population::2,200,000]]. – Beijing is a [[Is a::city]] [[Category::Cities]] Categories are used to define classes because they are better for class inheritance. The Jin Mao Tower (金茂大厦) is an 88-story landmark supertall skyscraper in … [[Categories: 1998 architecture | Skyscrapers in Shanghai | Hotels in Shanghai | Skyscrapers over 350 meters | Visitor attractions in Shanghai | Landmarks in Shanghai | Skidmore, Owings and Merrill buildings]] Category:Skyscrapers in China Category: Skyscrapers by country26
    24. 24. Database-style Query over Wiki Data Example: Skyscrapers in China higher than 50 stories, built before 2000 ASK/SPARQL query target {{#ask: [[Category:Skyscrapers]] [[Located in::China]] [[Floor count::>50]] [[Year built::<2000]] … }}27
    25. 25. What is the Promise of Semantic Wikis? Semantic Wikis promise Consensus over Data Combine low-expressivity data authorship with the best features of traditional wikis User-governed, user- maintained, user-defined Easy to use as an extension of text authoring 29
    26. 26. One Key Helpful Feature of Semantic Wikis Semantic Wikis are “Schema-Last” Databases require DBAs and schema design; Semantic Wikis develop and maintain the schema in the wiki31
    27. 27. Semantic MediaWiki in 2010  Open source (GPL)  Well documented  Active mailing list  Commercial support available  World-wide community  Regular Conferences – Next SMWCon 4/28-30, 2011 Arlington, VA Very stable SMW core Mature while still growing, slowly but steadily32
    28. 28. SMW Extensions Data I/O • Halo Extensions, Semantic Forms, Semantic Notification, … Query and Browsing • Semantic Toolbar, Semantic Drilldown, Enhanced Retrieval, Search… Visualization • Semantic Result Printers, Tree View, Exhibit, Flash charts… Other useful extensions • HaloACL, Deployment, Triplestore Connector, Simple Rules… • Semantic WikiTags and Subversion Integration extensions • Upcoming Linked Data Extension, with R2R and SILK from F.U.Berlin33
    29. 29. Wikis Can Help Information Management Research = Locate and Find Data ? Business Intelligence Finding Expertise Internal Encyclopedia Documentation Enterprise Search Crowd Sourcing is a Great Solution! 37
    30. 30. Example I: KnowIT in Johnson & Johnson Most Frequently Asked Questions: (J&J example) – What are the directions between two J&J sites? – What is the meaning of KOL ? HLM ? DRU ? – What data sources can we use to compare biological pathways? – Can you give us a list of R&D applications, related servers and stakeholders and send us an update every six months? Capture Facts About Things – Definitions, concepts, questions – Locations – Data sources – Organizations and people – Technologies and systems 38
    31. 31. System Architecture 39
    32. 32. Example II: Knowledge Encapsulation Framework Allow modelers to exploit the „information resources‟ they have and discover new, potentially relevant material across new media types KEF aims to provide: – an effective method for storing, retrieving, reviewing and annotating your documents – an environment where you can share these materials with team members and discuss – a mechanism to discover new, related information for social and traditional media – a means to link this material to model representations to aid analysis and game-play Achieved by a semantic wiki enabled with an NLP pipeline 41
    33. 33. 42
    34. 34. 43
    35. 35. Example 3: Ultrapedia – An Analytical Semantic Wikipedia  Ultrapedia: An SMW demo built to explore general knowledge acquisition in a wiki  Wikipedia merged with the power of a database – Data extracted from Wikipedia Infobox and Table data; stored in RDF – For Authors: tools to create more compelling articles • Great visualizations: charts, tables, timelines, photos, analytics • Always up-to-date across the Encyclopedia • Encourage data consistency and find data errors • Link in other web data sources – For Readers: • Enhanced articles and data interaction • Faceted navigation • Sophisticated queries (both standing and ad-hoc)  Maintenance via the Wikipedia update process – Data is from the article text, with simple ways for article authors to maintain and extend it. – Authors and readers always in the loop for merging, updating, validating, mapping45
    36. 36. Graph Views of the Acceleration Data
    37. 37. Dynamic Mapping and Charting
    38. 38. Information Discovery via Visualization52
    39. 39. Video: Semantic Wikis for A New Problem Increasing technical complexity → ← Increasing User Participation  Social tag-based  Algorithm-based Semantic characterization object Entertainment  Keyword search over Wiki characterization tag data  Database-style  Inconsistent  Social database-style search semantics characterization  Consistent semantics  Easy to engineer  Database search +  Extremely difficult to wiki text search engineer  Semantic consistency via wiki mechanisms  Easy to engineer55
    40. 40. Semantic Seahawks Football Wiki56
    41. 41. Based on Simple Templates and Forms57
    42. 42. Semantic Entertainment: Query Result  Highlight Reel  Commercial Look/Feel  Play-by-play video search  Highlight reel generation  Search on crowd-defined patterns (“touchdowns with big hits”)  Tree-based navigation widget  Very favorable economics
    43. 43. The Inspiration  We started with a  We built a  We now have an60
    44. 44. We CAN Build Applications (Fairly) Easily  With all the extensions of Semantic MediaWiki. Data I/O • Halo Extensions, Semantic Forms, Semantic Notification, … Query and Browsing • Semantic Toolbar, Semantic Drilldown, Enhanced Retrieval, Search… Visualization • Semantic Result Printers, Tree View, Exhibit, Flash charts… Other useful extensions • HaloACL, Deployment, Triplestore Connector, Simple Rules… • Semantic WikiTags and SVN Integration extensions • Upcoming Linked Data Extension, with R2R and SILK from FUB61
    45. 45. Collaborative Proposal Management at BT with SMW+ Active Bid Viewer Service Desk Selector65
    46. 46. Social Semantic Web Applications Omitting x examples, y pictures and z lines of text…67
    47. 47. Case Study 2 and Demo: Project Management with SMW+  Automatically populate tables  Just the data you want,  At the level you want  Calendars and timelines  Workflows  Personal menus  Form-oriented inputs  Notifications via email/RSS  MS Office integration  SVN integration68
    48. 48. Vulcan Project Management Wiki (Story)
    49. 49. Vulcan Project Management Wiki (Task)70
    50. 50. Vulcan Project Management Wiki (Visualizations)71
    51. 51. Screenshot of a Sprint page Data automatically generated via template queries on page http://wiking.vulcan.com/dev/index.php/Sprint_10102072
    52. 52. Requirements for Wiki “Developers”  One need not – Write code like a hardcore programmer – Design, setup RDBMS or make frequent schema changes – Possess knowledge of a senior system admin  Instead one need – Configure the wiki with desired extensions – Design and evolve the data model (schema) – Design Content • Customize templates, forms, styles, skin, etc.  The bar is dramatically lowered to build applications – “Source code” is part of the open content of wiki too!73
    53. 53. Effectiveness of SMW as a Platform Choice Packaged Software SMW + Extensions Custom Development ☺Very quick to ☺ Still quick to N Slow to develop obtain program ☺Extremely flexible N Hard to customize ☺ Easy to customize N High cost to develop N Expensive ☺ Low-moderate cost and maintain  Microsoft Project  Vulcan Project Wiki  .NET Framework  Version One  B.L.S.  J2EE, …  Microsoft  RPI map  Ruby on rails SharePoint74
    54. 54. Conclusions  Semantic MediaWiki+ (http://smwforum.ontoprise.com) – Open-source, growing semantic wiki software system – Wiki-style text + semantic markups – Collaborative, user-governed subject models and data curation – Simple and extensible data models with easy import/export  SMW+ has many government and industry users – People built applications with it Knowledge Management via KB Effort (cost, people,…)  Now crowds can work – A way to leverage and exploit web-collected data Vulcan – A lightweight collaborative knowledge management tool Future  A new platform for lightweight KB size (number of assertions, complexity…) web application development79
    55. 55. Acknowledgement 80
    56. 56. (End of Slides) Backups starts here81
    57. 57. Case Study: Battle-space Luminary System  Discover when New Information represents a change in understanding of entities – Discovery of explicit entity links, implicit relationships  Large Volumes of Data in various formats – Unstructured news articles – Tactical Reports, Field Intelligence – Structured Database Information  Use Wiki Pages to represent current knowledge about an entity – “what we know”  Domain Ontology to represent domain of information – “what we want to know”  Issue Alerts when Significant Events occur – New information according to category – Changing information on topics of interest – Need to send information to various devices – cell phones, email, etc.82
    58. 58. System Design  Wiki Configuration – Semantic MediaWiki: Large developer community, active development, open source. Wikipedia uses MediaWiki, so scalability and performance are important. – Semantic Results Format: Provides various rich media displays of semantic information, including graphs, timelines, maps – Semantic Forms: Provides convenient user interface for entering semantic data into wiki, avoiding cumbersome wikitext – Semantic Notifications: Enables sending of notifications when results of semantic query change.  Domain Ontology – Created OWL Ontology for Terrorism  Semantic Parsing, Extraction, Reasoning – Java Process using various Open-Source Toolkits – Rapid plugin of new technologies83 – Multiple Data Sources supported
    59. 59. Sample Content Page84
    60. 60. Wiki Content Design  Use Templates to Ensure Consistent Look-and-Feel – Templates Correspond to Ontology Classes – Fields within Templates correspond to Properties within Ontology – Rich Content Visualizations derived in consistent way  Hierarchical Categories match Class Hierarchy within Ontology – Ensures Validity for Properties – Category included on each Template page to ensure consistency  Forms Provide ability for users to enter data directly into wiki without knowing Wiki Text – Each form corresponds to a Template – Fields within forms correspond to the fields/properties within the Template – GUI can include auto-completion – Created Page immediately linked semantically to rest of Wiki85
    61. 61. Sample Visualizations86
    62. 62. Wikipedia for Porsches (Acceleration Data Example)  Information Need: All Porsche models that accelerate 0- 100kph in under 5, 6, and 7 seconds
    63. 63. More Porsche Acceleration Data in Wikipedia
    64. 64. Ultrapedia Main Page Main Page
    65. 65. Semantics for Improved Wiki NavigationTree View Control Abstract/Summary quick preview
    66. 66. The Porsche 996 Acceleration Table In Ultrapedia
    67. 67. Same Table as a Query
    68. 68. Dynamically-Generated Tables forfast? Which Porsches accelerate Queries  Information Need: All Porsche models that accelerate 0- 100kph in under 5, 6, and 7 seconds
    69. 69. Graph Views of the Acceleration Data
    70. 70. External Data via a Live Ebay Query
    71. 71. Linking to External Ebay Data
    72. 72. Photos in Mercedes-Benz E-class W212 Gallery Section Wiki Articles as Data
    73. 73. Timelines from Data Production Timeline View Volkswagen
    74. 74. Dynamic Mapping and Charting
    75. 75. Editing Wiki Data In Place Return

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