Semantic Wikis - Social Semantic Web in Action

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My invited talk at a technology seminar as part of Tsinghua University's centennial celebration in Seattle, WA on semantic wikis.

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  • ----- Meeting Notes (3/24/11 15:29) -----Vulcan is the MothershipProviding funds and supportPaul Allen successful
  • 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.
  • 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.
  • 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 Wikis - Social Semantic Web in Action

    1. 1. Semantic Wikis<br />Social Semantic Web In Action<br />2011-03-25<br />Specially Prepared for Tsinghua University Alumni<br />in greater Seattle area for centennial celebration <br />
    2. 2. About Me: Jesse Wang 王嘉欣<br />2<br />1998<br />1996<br />2005<br />1997<br />1993<br />1988<br />
    3. 3. Who is Vulcan<br />3<br />
    4. 4. What does Vulcan do<br />4<br />Vulcan Inc. was established in 1986 by investor and philanthropist Paul G. Allen, co-founder of Microsoft, to manage his business and philanthropic efforts. Allen is chairman of Vulcan and his sister, Jody Allen, is president and CEO. <br />
    5. 5. It all began with a vision…<br />5<br />
    6. 6. Now the Vision Continues as Project Halo<br />6<br />Automatic Question Answering System<br />Project Halo is a staged, long-range research effort by Vulcan Inc. towards the development of a "Digital Aristotle"—a reasoning system capable of answering novel questions and solving advanced problems in a broad range of scientific disciplines and related human affairs. The project focuses on creating two primary functions: a tutor capable of instructing and assessing students in those subjects, and a research assistant with broad, interdisciplinary skills to help scientists and others in their work. <br />
    7. 7. Project Halo’s Focus Areas<br />7<br />Knowledge Acquisition<br />Plus other related semantic technologies and commercial efforts<br />
    8. 8. Project Halo’s Goals<br />Address the core problems in Knowledge Bases<br />scale<br />brittleness<br />Have high impact<br />8<br />Now<br />Future<br />
    9. 9. Crowdsourcing for Better Knowledge Acquisition<br />9<br />
    10. 10. Success of Wikis<br />10<br />One of human’s greatest inventions<br />
    11. 11. 11<br />Outline<br />Wikis and Semantic Wikis<br />Crowdsourcing and Consensus on Data<br />Semantic MediaWiki and its Extensions<br />Wiki-based Knowledge Management on a Larger Scale<br />Enterprise Knowledge Management<br />Semantic Encyclopedia<br />Evolving as a Web Application Development Platform<br />Examples: Semantic Football, Agile Project Management <br />
    12. 12. A Key Feature of Wiki<br />12<br />Consensus<br />This distinguishes wikis from other publication tools<br />
    13. 13. Consensus in Wikis Comes from<br />Collaboration<br />~17 edits/page on average in Wikipedia (with high variance)<br />Wikipedia’s Neutral Point of View <br />Convention<br />Users follow customs and conventions to engage with articles effectively<br />13<br />
    14. 14. Software Support Makes Wikis Successful<br />Trivial to editby anyone<br />Tracking of all changes, one-step rollback<br />Every article has a “Talk” page for discussion<br />Notification facility allows anyone to “watch” an article<br />Sufficient security on pages, logins can be required<br />A hierarchy of administrators, gardeners, and editors<br />Software Bots recognize certain kinds of vandalism and auto-revert, or recognize articles that need work, and flag them for editors<br />14<br />
    15. 15. Finding Deeper Info<br />Wikipedia has articles about…<br /><ul><li>… all cities with info on their populations, locations and skyscrapers, etc.</li></ul>… all German cars with engine size, accelerating data…<br />Can you find: <br />Skyscrapers with 50+ floors and built after 2000 in Shanghai (or Chinese cities with 1,000,000+ people)?<br />Or German(Porsche) cars that accelerate from 0-100km/h in 5 seconds?<br />15<br />
    16. 16. How Wikipedia Answers – List!<br />16<br />http://en.wikipedia.org/wiki/List_of_fastest_cars_by_acceleration<br />
    17. 17. Going Deeper<br />17<br />http://en.wikipedia.org/wiki/List_of_German_cars<br />
    18. 18. Deeper…<br />18<br />
    19. 19. And Deeper…<br />19<br />
    20. 20. And Now…<br />20<br />
    21. 21. Look into List in Wikipedia<br />21<br />http://en.wikipedia.org/wiki/List_of_German_cars<br />
    22. 22. Editing Standard Wiki Article – Static List<br />22<br />
    23. 23. Static List, Tables, …, Not Useable Enough<br />23<br />http://en.wikipedia.org/wiki/List_of_lists_about_Oregon<br />
    24. 24. Semantics Come To Rescue<br />To find answers like:<br /><ul><li>All Porsche vehicles made in Germany that accelerate from 1-100 km/h less than 4 seconds
    25. 25. Sci-Fi movies made after year 2000 that cost less than $10M and gross more than $30M
    26. 26. A map showing where all Mercedes-Benz vehicles are manufactured
    27. 27. 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…
    28. 28. And many more</li></ul>We need <br />structured data <br />with clear <br />and consistent <br />semantics<br />24<br />
    29. 29. What is a Semantic Wiki<br />A wiki that has an underlying model of the knowledge  described in its pages.<br />To allow users to make their knowledge explicit and formal<br />Semantic Web Compatible<br />25<br />Semantic Wiki<br />Hybrid ... Better Gas Mileage!<br />
    30. 30. Two Perspectives<br />26<br />
    31. 31. Characteristics of Semantic Wikis<br />Semantic Wikis<br />27<br />
    32. 32. List of Semantic Wikis<br />AceWiki<br />ArtificialMemory<br />Wagn - Ruby on Rails-based<br />KiWi – Knowledge in a Wiki<br />Knoodl – Semantic Collaboration tool and application platform<br />Metaweb - the software that powers Freebase<br />OntoWiki<br />OpenRecord<br />PhpWiki<br />Semantic MediaWiki - an extension to MediaWiki that turns it into a semantic wiki<br />Swirrl - a spreadsheet-based semantic wiki application<br />TaOPis - has a semantic wiki subsystem based on Frame logic<br />TikiWiki CMS/Groupware integrates Semantic links as a core feature<br />zAgile Wikidsmart - semantically enables Confluence<br />28<br />
    33. 33. Basics of Semantic Wikis<br />Still a wiki, with regular wiki features<br />Category/Tags, Namespaces, Title, Versioning, ...<br />Typed Content (built-ins + user created, e.g. categories)<br />Page/Card, Date, Number, URL/Email, String, …<br />Typed Links (e.g. properties)<br />“capital_of”, “contains”, “born_in”…<br />Querying Interface Support<br />E.g. “[[Category:Member]] [[Age::<30]]” (in SMW)<br />29<br />
    34. 34. Short History of Semantic MediaWiki<br />Born at AIFB<br />Typed links and types and more<br />Export articles as RDF<br />Maximally flexible for the wiki user<br />SMW 0.1 released by AIFB in Sept 2005<br />Parser/storage support for typed links – [[type::link | label]]<br />FactBox for semantic relations at end of article<br />Special:SearchSemantic, with basic auto-completion for link types<br />Simple query language (“ask”)<br />Vulcan kicks off Halo Extensions to SMW project in August 2007<br />SMW 1.0 released by AIFB in Dec 2007, Ontoprise releases Halo Extension 1.0 in parallel<br />“Property” instead of “Relation” and “Attribute”<br />Many new datatypes/special pages/UI features<br />30<br />
    35. 35. Semantic MediaWiki (SMW) Markup Syntax<br />31<br />[[Property::Value | Display]]<br />Tsinghua is a university located in <br />[[Has location::Beijing]], with<br />[[Has population::27000|about 27 thousands]] students.<br />In page "Property:Haslocation":<br />[[Has type::Page]]<br />In page "Property:Haspopulation":<br />[[Has type::number]]<br />
    36. 36. Special Properties<br />“Has Type” is a pre-defined “special” property for meta-data<br />Example: [[Has type::String]]<br />“Allowed Values” is another special property<br />[[Allows value::Low]], <br />[[Allows value::Medium]], <br />[[Allows value::High]]<br />In Halo Extensions, there are domain and range support<br />RDFs expressivity<br />Semantic Gardening extension also supports “Cardinality”<br />32<br />
    37. 37. Define Classes<br />33<br />Beijing is a city in [[Has country::China]], with population [[Has population::2,200,000]].<br />[[Category::Cities]]<br />Categories are used to define classes because they are better for class inheritance.<br />The Jin Mao Tower (金茂大厦) is an 88-story landmarksupertallskyscraper in …<br />[[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]]<br />Category: Skyscrapers by country <br />Category:Skyscrapers in China<br />
    38. 38. Database-style Query over Wiki Data<br />34<br />Example: Skyscrapers in China higher than 50 stories, built before 2000<br />ASK/SPARQL query target<br />{{#ask:<br /> [[Category:Skyscrapers]]<br /> [[Located in::China]]<br /> [[Floor count::>50]]<br /> [[Year built::<2000]]<br /> …<br />}}<br />Data via DBpedia<br />
    39. 39. 35<br />Why Semantic Wiki?<br /><ul><li>Annotation of existing structures with machine readable metadatalinks carry meaning, typing of links, typing of pages
    40. 40. Context dependent adaptation and presentationdifferent domains have different ways of presenting content, personal preferences, etc.
    41. 41. Improved, “intelligent”, search and navigationqueries to the structure, visualisation of structure, derived information
    42. 42. Improved interoperability between systemsexchange of content, integration of different systems, agents, etc.</li></li></ul><li>What is the Promise of Semantic Wikis?<br />Semantic Wikis promise Consensus over Data<br />Combine low-expressivity data authorship with the best features of traditional wikis<br />User-governed, user-maintained, user-defined<br />Easy to use as an extension of text authoring<br />36<br />The ultimate <br />data aggregator<br />
    43. 43. 37<br />Challenges on Data Consensus<br />Data modeling is (seemingly) a specialized skill<br />Finding disagreements in data is difficult<br />Consistently revising data schemas is difficult<br />Consistency of schema information (“Population”, “Pop”, “Number_of_inhabitants”, etc...)<br />Consistency of types, units of measure, application of rules…<br />Semantics/interpretation of properties need explanation for humans<br />…<br />
    44. 44. One Key Helpful Feature of Semantic Wikis<br />38<br />Semantic Wikis are “Schema-Last”<br />Databases require DBAs and schema design; <br />Semantic Wikis develop and maintain the schema in the wiki<br />
    45. 45. Semantic MediaWiki Community<br />Open source (GPL)<br />Well documented<br />Active mailing list<br />Commercial support available<br />World-wide community<br />Regular Conferences<br />Next SMWCon 4/28-30, 2011 Arlington, VA<br />39<br />http://semantic-mediawiki.org/<br />Very stable SMW core<br />Mature while still growing, slowly but steadily<br />
    46. 46. SMW Extensions – Help Build Great Things<br />40<br />
    47. 47. Example: Ultrapedia – Semantic Wikipedia<br />Ultrapedia: An SMW demo built to explore general knowledge acquisition in a wiki<br />Wikipedia merged with the power of a database<br />Help Readers and Writers Be More Productive<br />41<br />An Analytical Encyclopedia<br />
    48. 48. Data Flow in the Ultrapedia Prototype <br />Real-time feed of WP changes<br /><ul><li>Note most WP page changes will be text and have no semantic import</li></ul>English Wikipedia subset<br />Dynamic extraction of WP semantic data into RDF<br />DBpedia update stream<br /><ul><li>WP page text updates
    49. 49. DBpedia data updates</li></ul>WP updates<br /><ul><li>User-created page updates in Wikipedia</li></ul>Ultrapedia<br />Enhanced Ultrapedia Usability<br /><ul><li>Familiar WP page text and layout
    50. 50. Exhibit-based visualizations
    51. 51. Dynamic tables/categories
    52. 52. Faceted navigation
    53. 53. Queries (both standing and ad-hoc)
    54. 54. Linked to relevant external data</li></ul>Wikipedia-based Corrections<br /><ul><li>UP shows the user where to correct data in WP so that DBpedia will extract the correction
    55. 55. Ultrapedia exposes the data source in terms of where the data was extracted from WP
    56. 56. WP changes and corrections get quickly propagated to UP</li></li></ul><li>Ultrapedia: An Analytic Encyclopedia<br />Goal: Prototype a small semantic encyclopedia<br />Create an semantic version of a part of Wikipedia<br />Software is SMW+, Ontobrokertriplestore, DBpedia<br />Show what a data-aware encyclopedia might look like<br />Ultrapedia Prototype Details<br />Test domain is German cars<br />~2500 Wikipedia pages, ~40000 triples<br />Features<br />Similar look and feel to Wikipedia<br />Dynamic tables and charts<br />Powerful queries<br />Navigation beyond search<br />Edit, discuss and rate data<br />SPARQL-based queries<br />Derived assertions (via OntoBroker)<br />
    57. 57. Better Views of the Wiki Data<br />http://wiking.vulcan.com/up/index.php/Porsche_996<br />
    58. 58. Dynamic Views of the Acceleration Data<br />
    59. 59. Graph Views of the Acceleration Data<br />
    60. 60. Dynamic Mapping and Charting<br />
    61. 61. Information Discovery via Visualization<br />48<br />
    62. 62. The Inspiration<br />We started with a <br />We could have an<br />49<br />wiki site<br />web <br />application<br />
    63. 63. 50<br />Video: Semantic Wikis for A New Problem<br />Semantic Entertainment <br />Wiki<br /><ul><li>Social database-style characterization
    64. 64. Database search + wiki text search
    65. 65. Semantic consistency via wiki mechanisms
    66. 66. Easy to engineer</li></ul>Increasing technical complexity -><br /> ← Increasing User Participation<br />Social tag-based characterization<br />Keyword search over tag data<br />Inconsistent semantics<br />Easy to engineer<br /><ul><li>Algorithm-based object characterization
    67. 67. Database-style search
    68. 68. Consistent semantics
    69. 69. Extremely difficult to engineer</li></li></ul><li>Semantic Seahawks Football Wiki<br />51<br />
    70. 70. Based on Simple Templates and Forms<br />52<br />
    71. 71. Template:Run Source Code <br /><noinclude><br /> This is the 'Run' template.<br /> It should be called in the following format:<br /><pre><br /> {{Run<br /> |Running Back=<br /> |Run Direction Type=<br /> |Yardage=<br /> |Run of X Yards=<br /> |Result of Run Type=<br /> }}<br /></pre><br />Edit the page to see the template text.<br /></noinclude> <br /><includeonly><br />{| class="wikitable"<br />{{#if:{{{Running Back|}}}|<br />! Running Back<br />{{!}} {{#arraymap:{{{Running Back|}}}|,|x|[[Running Back::x]]}} <br />{{!}}- }}<br />{{#if:{{{Run Direction Type|}}}|<br />! Run Direction Type<br />{{!}} {{#arraymap:{{{Run Direction Type|}}}|,|x|[[Run Direction Type::x]]}}<br />{{!}}- }}<br />{{#if:{{{Yardage|}}}|<br />! Yardage<br />{{!}} {{#arraymap:{{{Yardage|}}}|,|x|[[Yardage::x]]}}<br />{{!}}- }}<br />{{#if:{{{Run of X Yards|}}}|<br />! Run of X Yards<br />{{!}} [[Run of X Yards::{{{Run of X Yards|}}}]]<br />{{!}}- }}<br />{{#if:{{{Result of Run Type|}}}|<br />! Result of Run Type<br />{{!}} {{#arraymap:{{{Result of Run Type|}}}|,|x|[[Result of Run Type::x]]}}<br />}}<br />|}<br />[[Category:Play]]<br /></includeonly><br />53<br />
    72. 72. Semantic Entertainment: Query Result  Highlight Reel<br /><ul><li>Commercial Look/Feel
    73. 73. Play-by-play video search
    74. 74. Highlight reel generation
    75. 75. Search on crowd-defined patterns (“touchdowns with big hits”)
    76. 76. Tree-based navigation widget
    77. 77. Very favorable economics</li></ul>Demo<br />
    78. 78. We CAN Build Applications (Fairly) Easily<br />With all the extensions of Semantic MediaWiki.<br />55<br />Social Semantic <br />Web Applications<br />
    79. 79. Showcase: NPS Wiki: Browse People<br />56<br />
    80. 80. View of Data in NPS Wiki<br />57<br />
    81. 81. Show case: Work Order Processing Wiki (NGT)<br />58<br />
    82. 82. Collaborative Proposal Management at BT with SMW+<br />59<br />Active Bid Viewer<br /> Service Desk Selector<br />
    83. 83. Showcase: RPI Map<br />60<br />RPI Map<br />http://map.rpi.edu<br />A mash-up map application based on Semantic MediaWiki<br />Provides location-based information in the RPI campus<br />Integrates data from various external sources<br />Visualizes integrated data using Google Map<br />
    84. 84. Social Semantic Web Applications<br />61<br />Omitting x examples, y pictures and z lines of text…<br />
    85. 85. Case Study and Demo: Project Management with SMW+<br />62<br /><ul><li>Automatically populate tables
    86. 86. Just the data you want,
    87. 87. At the level you want
    88. 88. Calendars and timelines
    89. 89. Workflows
    90. 90. Personal menus
    91. 91. Form-oriented inputs
    92. 92. Notifications via email/RSS
    93. 93. MS Office integration
    94. 94. SVN integration</li></li></ul><li>Vulcan Project Management Wiki (Story)<br />Template and style sheet customizations<br />Related content automatically included<br />
    95. 95. Vulcan Project Management Wiki (Task)<br />64<br />Color codes to indicate types and status<br />SVN Integration automatically “Completed” task and relate to repository<br />
    96. 96. Vulcan Project Management Wiki (Visualizations)<br />65<br />Demo<br />
    97. 97. Screenshot of a Sprint page<br />66<br />Data automatically generated via template queries on page<br />http://wiking.vulcan.com/dev/index.php/Sprint_101020<br />
    98. 98. Requirements for Wiki “Developers”<br />67<br />One need not<br />Write code like a hardcore programmer<br />Design, setup RDBMS or make frequent schema changes<br />Possess knowledge of a senior system admin<br />Instead one need<br />Configure the wiki with desired extensions<br />Design and evolve the data model (schema)<br />Design Content<br />Customize templates, forms, styles, skin, etc.<br />
    99. 99. Effectiveness of SMW as a Platform Choice<br />SMW + Extensions<br />Packaged Software<br />Custom Development<br />☺ Still quick to program<br />☺ Easy to customize<br />☺ Low-moderate cost<br />Vulcan Project Wiki<br />B.L.S.<br />RPI map<br />☺Very quick to obtain<br />N Hard to customize<br />N Expensive<br />Microsoft Project<br />Version One<br />Microsoft SharePoint<br />N Slow to develop<br />☺Extremely flexible<br />N High cost to develop and maintain<br />.NET Framework<br />J2EE, …<br />Ruby on rails<br />68<br />
    100. 100. Openness of SMW as a Platform<br />69<br />Open Source<br />Open Content<br />Open Metadata<br />
    101. 101. Other SMW+ use?<br />Collaboration applications were conceived as desktop apps<br />Then wikis made the web collaborative<br />Now the action is in mobile apps<br />70<br />
    102. 102. Potential to Build Many More Apps<br />Why are there 300,000+ apps in the iPhone App Store?<br />UI limitations drive specificity in apps<br />People personalize their phones<br />But better browser technologies are shrinking the gap between native apps and web pages<br />HTML5, JavaScript, etc.<br />SMW is a tool to build apps!<br />Collaborative: social semantic in nature<br />Data flow and report driven<br />Cheap to customize and rapidly deployable<br />High signal-to-noise ratio for the users<br />Vulcan is investigating this concept<br />71<br />
    103. 103. Summary: Application Platform by SMW+ Extensions<br />Semantic MediaWiki + wide range of extensions make it a potential application development platform for social semantic web<br />SMW + extensions provide a choice that fits into cost-effective sweet spot <br />SMW + extensions could become a great platform for social semantic web application development, with more<br />Extensions, Widgets and Applications<br />72<br />There is an app for it!<br />
    104. 104. 73<br />Conclusions: Semantic MediaWiki is a Powerful Tool<br />Semantic MediaWiki+ (http://smwforum.ontoprise.com) <br />Open-source, growing semantic wiki software system<br />Wiki-style text + semantic markups<br />Collaborative, user-governed subject models and data curation<br />Simple and extensible data models with easy import/export<br />SMW+ has many government and industry users<br />People built applications with it <br />Knowledge Management viacrowds can work<br />A way to leverage and exploit web-collected data<br />A lightweight collaborative knowledge management tool<br />A new platform for lightweight <br /> web application development<br />Now<br />Future<br />
    105. 105. Acknowledgement<br />Thank you!<br />74<br />
    106. 106. 75<br />(End of Slides)<br />Backups starts here<br />
    107. 107. Case Study: Battle-space Luminary System <br />Discover when New Information represents a change in understanding of entities<br />Discovery of explicit entity links, implicit relationships<br />Large Volumes of Data in various formats<br />Unstructured news articles<br />Tactical Reports, Field Intelligence<br />Structured Database Information<br />Use Wiki Pages to represent current knowledge about an entity – “what we know”<br />Domain Ontology to represent domain of information – “what we want to know”<br />Issue Alerts when Significant Events occur<br />New information according to category<br />Changing information on topics of interest<br />Need to send information to various devices – cell phones, email, etc.<br />76<br />
    108. 108. System Design<br />Wiki Configuration<br />Semantic MediaWiki: Large developer community, active development, open source. Wikipedia uses MediaWiki, so scalability and performance are important.<br />Semantic Results Format: Provides various rich media displays of semantic information, including graphs, timelines, maps<br />Semantic Forms: Provides convenient user interface for entering semantic data into wiki, avoiding cumbersome wikitext<br />Semantic Notifications: Enables sending of notifications when results of semantic query change.<br />Domain Ontology<br />Created OWL Ontology for Terrorism<br />Semantic Parsing, Extraction, Reasoning<br />Java Process using various Open-Source Toolkits<br />Rapid plugin of new technologies<br />Multiple Data Sources supported<br />77<br />
    109. 109. Sample Content Page<br />78<br />
    110. 110. Wiki Content Design<br />Use Templates to Ensure Consistent Look-and-Feel<br />Templates Correspond to Ontology Classes<br />Fields within Templates correspond to Properties within Ontology<br />Rich Content Visualizations derived in consistent way<br />Hierarchical Categories match Class Hierarchy within Ontology<br />Ensures Validity for Properties<br />Category included on each Template page to ensure consistency<br />FormsProvide ability for users to enter data directly into wiki without knowing Wiki Text<br />Each form corresponds to a Template<br />Fields within forms correspond to the fields/properties within the Template<br />GUI can include auto-completion<br />Created Page immediately linked semantically to rest of Wiki<br />79<br />
    111. 111. Sample Visualizations<br />80<br />UI enables notifications based on results of query – message sent when visualization changes<br />Visualizations automatically created w/o user edit<br />(tables, timelines, maps, social networks…)<br />
    112. 112. Wikipedia for Porsches (Acceleration Data Example)<br /><ul><li>Information Need: All Porsche models that accelerate 0-100kph in under 5, 6, and 7 seconds</li></li></ul><li>More Porsche Acceleration Data in Wikipedia<br />
    113. 113. Main Page<br />Ultrapedia Main Page<br />
    114. 114. Tree View Control<br />Abstract/Summary quick preview<br />Semantics for Improved Wiki Navigation<br />
    115. 115. The Porsche 996 Acceleration Table In Ultrapedia<br />
    116. 116. Same Table as a Query<br />
    117. 117. Which Porsches accelerate fast?<br />Dynamically-Generated Tables for Queries<br /><ul><li>Information Need: All Porsche models that accelerate 0-100kph in under 5, 6, and 7 seconds</li></li></ul><li>Graph Views of the Acceleration Data<br />
    118. 118. External Data via a Live Ebay Query<br />
    119. 119. Linking to External Ebay Data<br />
    120. 120. Mercedes-Benz E-class W212 Gallery Section<br />Photos in Wiki Articles as Data<br />
    121. 121. Volkswagen Production Timeline View<br />Timelines from Data<br />
    122. 122. Dynamic Mapping and Charting<br />
    123. 123. Editing Wiki Data In Place<br />Return<br />

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