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Pre-SMWCon Spring 2012 meetup (short)
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Pre-SMWCon Spring 2012 meetup (short)

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  • Nice overview. the Human Brain Project is brilliant use of this approach.
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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.
  • 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.

Transcript

  • 1. What is a Semantic Wiki Why should you want to know or care? Jesse Wang, Wil Smith 2012.04.11 For Semantic Web Meetup in San Diego
  • 2. Crowdsourcing for Better Knowledge Acquisition2
  • 3. A Key Feature of Wiki This distinguishes wikis from other publication tools3
  • 4. 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 effectively4
  • 5. 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 editors5
  • 6. Success of Wikis6
  • 7. Finding information…Wikipedia has articles about…• … all cities with info on their populations, locations and skyscrapers, etc. … all German cars with engine size, accelerating data…Can you find:Skyscrapers with 50+ floorsand built after 2000 inShanghai (or Chinese citieswith 1,000,000+ people)?Or German(Porsche) cars thataccelerate from 0-100km/h in5 seconds? 7
  • 8. Can Search Solve the Problem?8
  • 9. How Wikipedia Answers – List! http://en.wikipedia.org/wiki/List_of_fastest_ cars_by_acceleration9
  • 10. And Tables…10
  • 11. Answer is Hidden Deeply In11
  • 12. Look into List in Wikipedia http://en.wikipedia.org/wiki/List_of_German_cars12
  • 13. Editing Standard Wiki Article – Static List13
  • 14. Static List, Tables, …, Not Useable Enough http://en.wikipedia.org/wiki/List_of_lists_about_Oregon14
  • 15. To Find More Info • 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 • 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… • And many more15
  • 16. 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 Wiki16
  • 17. Two Perspectives Wikis for Metadata Metadata for Wikis17
  • 18. Characteristics of Semantic Wikis Semantic Wikis 18
  • 19. 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)19
  • 20. Why Semantic Wiki?  Annotation of existing structures with machine readable metadata links carry meaning, typing of links, typing of pages  Context dependent adaptation and presentation different domains have different ways of presenting content, personal preferences, etc.  Improved, “intelligent”, search and navigation queries to the structure, visualisation of structure, derived information  Improved interoperability between systems exchange of content, integration of different systems, agents, etc.20
  • 21. What is the Promise of Semantic Wikis?  Semantic Wikis facilitate 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 authoring21
  • 22. 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 wiki22
  • 23. 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 23
  • 24. Short History of Semantic MediaWiki (SMW)  Born at AIFB – Typed links and types and more – Export articles as RDF – Maximally flexible for the wiki user  SMW 0.1 released by AIFB in Sept 2005 – Parser/storage support for typed links – [[type::link | label]] – FactBox for semantic relations at end of article – Special:SearchSemantic, with basic auto-completion for link types – Simple query language (“ask”)  Vulcan kicks off Halo Extensions to SMW project in August 2007  SMW 1.0 released by AIFB in Dec 2007, Ontoprise releases Halo Extension 1.0 in parallel – “Property” instead of “Relation” and “Attribute” – Many new datatypes/special pages/UI features24
  • 25. Overview of Semantic MediaWiki (SMW)  Open source (GPL) – Well documented, active user forum  Active development – Commercial support (SMW+) available  World-wide community – International Conferences • Next SMWCon on 4/25-27, 2012 in Carlsbad, CA Very stable core, various extensions25
  • 26. Semantic MediaWiki (SMW) Markup Syntax Tsinghua is a university located in [[Has location::Beijing]], with [[Has population::27000|about 27 thousands]] students. In page "Property:Has location": In page "Property:Has population": [[Has type::Page]] [[Has type::number]]26
  • 27. Define Classes Beijing is a city in [[Has country::China]], with population [[Has population::2,200,000]]. [[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 country27
  • 28. Possible Database-style Query over Data Ex: 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]] … }}28
  • 29. Semantic MediaWiki Stack MediaWiki (XAMPP) Extension: Semantic MediaWiki More Extensions and Applications29
  • 30. Simple Example: Semantic Sci-Fi Movie Wiki  Demo30
  • 31. SMW Extensions – Help Build Great Things Data I/O • Halo Extensions, Semantic Forms, Semantic Notification, … Query and Browsing • Semantic Toolbar, Semantic Drilldown, Faceted Search, Full-text Retrieval… Visualization • Semantic Result Printers, Tree View, Exhibit, Flash charts… Other useful extensions • HaloACL, Wiki Admin Tool Triplestore Connector, Simple Rules… • Semantic WikiTags and Subversion Integration extensions • Linked Data Integration Framework with R2R and SILK from F.U.Berlin31
  • 32. Example: Ultrapedia – Semantic Wikipedia  Ultrapedia: An SMW demo built to explore general knowledge acquisition in a wiki  Wikipedia merged with the power of a database  Help Readers and Writers Be More Productive32
  • 33. Standard View of the Wiki Data http://wiking.vulcan.com/up/index.php/Porsche_996
  • 34. Dynamic View of the Acceleration Data
  • 35. Graph View of the Acceleration Data
  • 36. Dynamic Mapping and Charting
  • 37. Information Discovery via Visualization37
  • 38. 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 engineer38
  • 39. Semantic Seahawks Football Wiki39
  • 40. 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
  • 41. The Inspiration  We started with a  We could have an42
  • 42. Application 1: 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 integration43
  • 43. Vulcan Project Management Wiki (Story)
  • 44. Vulcan Project Management Wiki (Task)45
  • 45. Vulcan Project Management Wiki (Visualizations)46
  • 46. Screenshot of a Sprint page Data automatically generated via template queries on page http://wiking.vulcan.com/dev/index.php/Sprint_10102047
  • 47. 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.48
  • 48. 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 SharePoint49
  • 49. Application 2: Human Brain Map• Open, public online access• A detailed, interactive three-dimensional anatomic atlas of the "normal" human brain• Data from multiple human brains• Genomic analysis of every brain structure, providing a quantitative inventory of which genes are turned on where• High-resolution atlases of key brain structures, pinpointing where selected genes are expressed down to the cellular level• Navigation and analysis tools for accessing and mining the data
  • 50. Biological Linked Data Map• Open, public online access• Data from multiple RDF data stores• Complete import pipeline using LDIF framework• Outlines of each imported instance embedding inline wiki properties and providing views of imported properties from original RDF datasets• Charting tools that „pivot‟ SPARQL queries providing several views of each query• Navigation and composition tools for accessing and mining the data
  • 51. Where did we get the data? KEGG : Kyoto Encyclopedia of Genes and Genomes – “KEGG GENES is a collection of gene catalogs for all complete genomes generated from publicly available resources, mostly NCBI RefSeq.” Diseasome – “The Diseasome website is a disease/disorder relationships explorer and a sample of an innovative map-oriented scientific work. Built by a team of researchers and engineers, it uses the Human Disease Network dataset.” DrugBank – “The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug data with comprehensive drug target information.” SIDER – “SIDER contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts.”
  • 52. Wiki Ontology Map • Genes • DrugBank : 4,553 • Diseasome : 3,919 • KEGG : 9,841 • Diseases • Diseasome : 4,213 • KEGG : 459 • Drugs • DrugBank : 4,772 • KEGG : 2,482 • SIDER : 924 • Effects • SIDER : 1,737 • Pathways • KEGG : 28,442 61,342 Instances Available for Import We chose to intentionally simplify the ontology due to disagreements between researchers about entity relationships and subclasses.
  • 53. Embedding SPARQL Semantic Results Formatters Every piece of content on every instance page is generated by Semantic Result Formatters interpreting SPARQL results. Most inline properties are embedded in templates returned by SPARQL formatters. All 3 dynamic graph types are interpreting results of SPARQL queries and injecting a JavaScript template into the head of the page. The outline template takes selected predicates and objects from a SPARQL query, defined in the query embedding, and generates an HTML template for the page.
  • 54. Four Initial Templates for Each Instance by Category 1. Custom infobox within outline template • Visible inline properties 2. Outline template providing instance information 3. Widget template displaying dynamic charts or third party services • Donut charts and disease Twitter feed 4. Broad table SPARQL queries showing instance relationships 5. Hidden inline properties for other extensions
  • 55. Demo Links http://neurowiki.alleninstitute.org/index.php/Main_Page http://neurowiki.alleninstitute.org/index.php/AR http://neurowiki.alleninstitute.org/index.php/Propofol http://neurowiki.alleninstitute.org/index.php/AIBS:Main_Page http://neurowiki.alleninstitute.org/index.php/AIBS:AR http://neurowiki.alleninstitute.org/index.php/Frontal_Lobe http://neurowiki.alleninstitute.org/index.php/NEUROLEX:Main_Page http://neurowiki.alleninstitute.org/index.php/Adrenoleukodystrophy
  • 56. Neurowiki in Action! Which drugs are used in Chemotherapy? What are the dangers of Propofol? How are base entities like Calcium represented? How are new inline properties added to entities? – Can these be searched? – Can these be queried using ASK? Do existing extensions work with the framework?
  • 57. Openness of SMW as a Platform58
  • 58. Semantic MediaWiki Enables Collaboration Create and Manage Real Knowledge Build Social Semantic Web Applications In an Efficient and Cost- Effective Way59
  • 59. 60
  • 60. Tutorial: Wednesday 4/25  MediaWiki – How to Edit, Format Text, Use Template – Infoboxes, Parser Functions, Extensions…  Semantic MediaWiki – Features, usage, queries, patterns – Extensions: data i/o, forms, maps, visualizations…  SMW+ – Usability Enhancement, Wiki Admin Tools, Installation Packages – Enterprise Wiki, Microsoft Office Integration, Triple-store support…  Edithon – Supervised individual and group collaboration time62
  • 61. Conference Days (4/26-4/27)  Two Keynote Talks – Semantics and Wikis: from Genomes to X Games by Tom Marsh – Text, Data, Structure, Semantics and Knowledge by Mark Greaves  Variety of Presentations – Open and closed data, including talks on wikidata – Social and semantics, mash-ups – R&D: life science, neuroscience, biology, finance… – News, updates, demos and apps – Lightning Talks  Plenty of Group Social Time – Breakfast, Coffee breaks, Lunch and Dinner63 – Movie screening, restaurant and bars, …
  • 62. Social and Semantic Web at a Great Value   Thanks to our sponsor ai-one and local organizers  We‟d be able to provide – Quality lunch – Drinks and pastry/snacks for coffee breaks (breakfast) – Conference dinner – Business relation breakfast on Friday 4/27  Opportunity to meet a variety of people – Achievers – Hackers – Bar-hoppers  Register Now! http://bit.ly/scs1264
  • 63. Acknowledgement 65
  • 64. (End of Slides) Backups start here66