Tutorial semantic wikis and applications

Tutorial semantic wikis and applications - Presentation Transcript

Tutorialon Semantic Wikis and Applications
Mark Greaves
Vulcan Inc.
[email protected]
Daniel Hansch
Ontoprise GmbH
[email protected]
Denny Vrandecic
Karlsruhe Institue of Technology
[email protected]
Jesse Wang
Vulcan Inc.
[email protected]

2
Outline
Tutorial Introduction and Structure (Mark)
Introduction to Semantic MediaWiki (Denny)
Dive into Semantic MediaWiki (Denny)
Applications for Semantic Wikis (Mark)
Extensions for Semantic MediaWiki (Denny, Daniel, Jesse)
Connecting Semantic MediaWiki with MS Office (Jesse)
Augmenting Semantic MediaWiki with a Triple Store (Daniel)
Future Development (Denny, Daniel, Jesse)
Wrap Up and Q&A (Mark)
Break (30 mins)

3
Outline
Break (30 mins)

Context: Social Web, Semantic Web, and Semantic Wikis
4
SoftwareAgents
Expert Systems
Freebase
Schema Integration
Facebook
OpenGraph
Linked Data
Ontologies
SemanticWikis
Semantic
Desktops
Evri
Thesauri
Twine/T2
Prediction Markets
Increasing Data Interconnection
PIMs
Ning
Databases
FaceBook
SearchEngines
Amazon Reviews
Content Portals
Web sites
Wikipedia
File servers
Blogs
Twitter
Increasing Social Interconnection
Based on a diagram by Nova Spivak, Radar Networks

A Range of Semantic Wiki Platforms
KiWi – Knowledge in a Wiki
Knoodl – Semantic Collaboration tool and application platform
Freebase - Collaborative platform for almanac data by Metaweb
OntoWiki
PhpWiki
Semantic MediaWiki - an extension toMediaWikithat turns it into a semantic wiki (and SMW extensions)
TikiWiki - CMS/Groupware integrates Semantic links as a core feature
Wikidsmart - adds semantics to Confluence (from zAgile)
5
5

6
Outline
Break (30 mins)

Semantic MediaWiki
Denny Vrandečić, KIT / ISI, USC
June 22 2010, San Francisco

Wikis are great
Enable new scale of human collaboration
Everyone can read
Everyone can write
Everyone gets aggregated
Everyone is accountable for everything
But some things are better left to machines…
8

edit
wow. I can change the web.
let’s write an encycolpedia!

Wiki Clock
http://pageoftext.com/wikiclock

Wikis are great
Enable new scale of human collaboration
Everyone can read
Everyone can write
Everyone gets aggregated
Everyone is accountable for everything
But how are semantic wikis different?
Semantic
+ computer
v
12

edit
edit
edit
Country
City
Population = 745,514
Area = 39 km2
capital
mayor
edit
edit
Birthdate =
1 April 1946

edit
edit
edit
edit
edit
edit
May 27 1994, Tim Berners-Lee, Keynote at WWW1

edit
edit

What humans are good at
What machines are good at
Understanding
“Why”
Tacit knowledge
Stories
Following hunches
Checking external refs
Executing
Facts and figures
Explicit knowledge
Keeping track and logs
Analyzing big style
Calling web services

Universal Access to
All Knowledge

19
What Wikipedia knows
Wikipedia has articles about…
… all cities
… their populations
… their mayors
So can I ask for a list of the world’s ten largest cities with a female mayor?

20
Let’s see what happens…

Wikipedia’s answer: lists
21

26

27

28

29

30

32

Computers are stupid
34

35
What humans see

What humans see
Karlsruhe
... has a population of 285,812
... is located inGermany
... was founded in 1715
... has mayor Heinz Fenrich
36

What computers see

What computers see
Karlsruhe
... 285,812
... Germany
... 1715
... Heinz Fenrich
38

Computers don‘t make connections
39

Computers need our help
40

Karlsruhe
Karlsruhe is a city in
[[Germany]].
[[Country::Germany]].
Germany
Country
Karlsruhe
Country
Germany
Karlsruhe
Mayor
Heinz Fenrich
Heinz Fenrich
Gender
Male
41

{{#ask:
[[Category:City]]
[[located in::
Baden-Württermberg]]
| format=barchart
| ?population
}}

External data reuse
Export formats
RDF/XML
SPARQL
RDFa
CSV
JSON
iCal
vCard
Bibtex
44

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Outline
Break (30 mins)

External data reuse
Computer understands wiki content
Knowledge based applications
A number of export formats
RDF/XML, SPARQL, RDFa, CSV, JSON, iCal, vCard, Bibtex, ...
RDF APIs in programming languages
Java, JavaScript, C/C++, Python, Ruby, Haskell, .Net, PHP, Common Lisp, Prolog, …
Standards based
URIs, XML, RDF, OWL, SPARQL, …

importSemanticMediaWikias smw
wiki = smw.SMW("http://semanticweb.org/")
denny = wiki.load(“DennyVrandecic")
printdenny.affiliation

Test wiki
Go to http://scratchpat.referata.com
Click on log in and then on “Create an account”
Suggestion: use your name as your login
Enter your eMail (for forgotten passwords)

Editing the wiki
Go to your own page (page with your name)
Click on “edit”
Try to add or change text
You can cancel anytime, preview (just for you), or save the changes so that everyone can see them

Quick overview of wiki markup
'''three apostrophes''' will make text bold
''two apostrophes''' will make text italic
[[Text in double square brackets]] will be links to the page named as the text in the brackets
[[Link target|link text]] will display a link that looks like link textbut links to link target
The wiki is case sensitve – but not on the first letter of a link
The wiki is Unicode

Slide 53
Overview of semantic markup
To add a page P to category C type [[Category:C]] on page P
To make a typed link of type R from page P1 to page P2 type [[R::P2]] on page P1
To state the value V of an attribute A on page P type [[A::V]] on page P
Example:

Data values and types
Attributes like [[birthdate::February 27 1978]] or [[population::3,635,389]] must know the type of the value
This is done by adding [[has type::T]] on the page of the attribute
Available, predefined types:
Telephone number
Record
URL
Email
Annotation URI
Geographiccoordinate (S Maps)
Enumeration
Customunits
Page
String
Number
Boolean
Date
Text
Code
Temperature

Add your own information
Now add information about yourself
For example: nationality, affiliation, age, birthday, hair color, likes…
Save or preview to see if and how the information has been understood
Blue links mean there is a page about it
Red link means there is no page about it

Collaborative ontology engineering
There are pages describing categories and properties
Informal description
Can be discussed
Can be edited
Extensional descript.
List of all instances
But: only direct ones
Supercategories

Slide 57
Social aspects
Task: come up with a vocabulary and the relation between the vocabularies for the whole group, using the wiki
How to decide which properties and categories are important?
How to define the properties or categories?
How to ensure high quality data? What does it mean?
How to control the wiki knowledge base and its growth?
Browse the wiki to see the results and connections

Querying the knowledge
Go to Special:Ask
Enter a query
Queries look like this:
Conditions on a category: [[Category:X]]
Conditions on a property: [[R::X]]
Property conditions can be ranges, [[R::>X]], [[R::<X]]
Property conditions: any value [[R::+]]
Print statements: ?R
Examples follow
See also online docs

Query examples
[[population::>1,000,000]] anything with a population of over a Million
[[located in::Korea]] anything that is located in Korea
[[affiliation::+]] anything that has any stated affiliation
[[Category:Tutor]] all tutors
[[Category:Tutor||Student]] all tutors or students (logical or)
[[Category:Tutor]] [[Category:Student]] everyone who is both

Querying and social aspects
Querying can only be done on aligned vocabularies
If half of the people use “affiliation” and the other half “works for” you cannot query the knowledge easily
Inside SMW, information integration usually happens with social tools, not with technology
Gardening tools can help with aligning vocabularies, but not replace them
Tools that allow you to rename a property throughout the wiki
Or to join two different names

Querying the wiki
{{#ask:
[[Category:City]]
[[Mayor.Gender::Female]]
| sort=Population
}}

Querying the wiki
{{#ask:
[[Category:Country]]
[[Continent::North America]]
|?Population
}}

Result rendering

Querying the wiki
{{#ask:
|?Population
|format=piechart
}}

Pie chart

Querying the wiki
{{#ask:
|?Population
|format=barchart
}}

Bar chart

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Outline
Break (30 mins)

SNPedia

HL7 Healthcare Terminology Management
70

Taaable
71

Chickipedia
72

Football Indexing Wiki

Non-Wikipedia Look/Feel
Play-by-play video search
Highlight reel generation
Search on crowd-defined patterns (“touchdowns with big hits”)
Tree-based navigation widget

Metacafe Video Indexing and Tagging Wiki

SMW+ with Automatic Document Annotation
75

Collaborative Proposal Management at BT with SMW+
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Active Bid Viewer
Service Desk Selector

Lightweight Project Management with SMW+
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Automatically populate tables
Just the data you want, at the level you want
Calendars and timelines
Workflows
Custom Reports
Form-oriented inputs
Notifications via email/RSS
MS Office integration

Shared Documentation in SMW+

Wiki-based Communities of Interest with SMW+
79

Employee Skill Registries with SMW+
80

Employee Home Pages in SMW+
81

Community Maintained Resource Portals
82

Timelines in the LiDAR Portal
83

Social Networks in the LiDAR Portal
84

Google Maps

SMW+ Extended Example: An Analytic Encyclopedia
Ultrapedia: An SMW demo built to explore data and text 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, mapping
87

Title
Description
Languages
Further Down
Web Links
Categorization
Domain specific
Data
Images
Infobox
Properties
Sources of Structured Data in Ultrapedia

Ultrapedia Data from Wikipedia Tables
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Table
Data

Ultrapedia: An Analytic Encyclopedia
Goal: Prototype a small semantic encyclopedia
Create an semantic version of a part of Wikipedia
Software is SMW+, Ontobrokertriplestore, DBpedia
Show what a data-aware encyclopedia might look like
Ultrapedia Prototype Details
Test domain is German cars
~2500 Wikipedia pages, ~40000 triples
Features
Similar look and feel to Wikipedia
Dynamic tables and charts
Powerful queries
Navigation beyond search
Edit, discuss and rate data
SPARQL-based queries
Derived assertions (via OntoBroker)

Wikipedia for Porsches (Acceleration Data Example)

Information Need: All Porsche models that accelerate 0-100kph in under 5, 6, and 7 seconds

More Porsche Acceleration Data in Wikipedia

Main Page
Ultrapedia Main Page

Tree View Control
Abstract/Summary quick preview
Semantics for Improved Wiki Navigation

The Porsche 996 Acceleration Table In Ultrapedia

Same Table as a Query

Which Porsches accelerate fast?
Dynamically-Generated Tables for Queries

Information Need: All Porsche models that accelerate 0-100kph in under 5, 6, and 7 seconds

Graph Views of the Acceleration Data

External Data via a Live Ebay Query

Linking to External Ebay Data

Mercedes-Benz E-class W212 Gallery Section
Photos in Wiki Articles as Data

Volkswagen Production Timeline View
Timelines from Data

Dynamic Mapping and Charting

Editing Wiki Data In Place

105
Wrap-Up Part 1: Managing Data in the 21st Century
A New Kind of Knowledge Management
Structured and unstructured data together in one tool
Built with Semantic Web standards, and with web energy
Empower users with lightweight, web-friendly tools
Data sharing from the start: not just another silo
Built for collaboration on the web
Example: Semantic MediaWikiand SMW+
Open-source semantic wiki software
Wiki-style text/article authorship based on MediaWiki
Lightweight enterprise-scale data publishing
Collaborative, user-governed structured and unstructured data curation
A comfortable tool users to own their data
A variety of applications and uses

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Break

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Outline
Break (30 mins)

Extensions
Halo
S Forms
S Result Formats
S Layers
S Tasks
S Calendar
MokiWiki
External Data
Maps and S Maps
S Drilldown
Woogle
Innsbruck Ontology Editor
P2P Extension
RDFaExporter
and others

Extension architecture
Built firmly on top of MediaWiki
Core SMW to be small
Provide extension hooks of its own
Allow apps on top of it

The suite of halo extensions for Semantic MediaWiki
Daniel Hansch, „Semantic Wikis and Applications“ tutorial, semtech 2010
[email protected]

Agenda
Who is ontoprise?
The halo extensions
Vision
Benefits
How to get it?

ontoprise: leader in semantic technologies and solutions

+50 employees in Karlsruhe, Germany
software vendor (more about us on: http://www.ontoprise.com)
flagship product: rdf-store with reasoning capabilities (OntoBroker)
selected customers
selected partners

Building the best Semantic Wiki in project halo[1]
SMW+
halo extensions
1. http://wiki.ontoprise.com/wiki/index.php/Faq/project_halo

halo extensions - vision
Leverage adoption of Semantic MediaWiki by
domain experts in scientific and commercial environments
by improving key product features.
Usability
Retrieval
Security
SemanticMediaWiki
Data
processing
Data re-use
and
consistency
Administration

Improve usability
Enable a non-tech savvy Wiki community to efficiently use
Wiki- and semantic features with minimal training time.

Improve usability
Ontology browser

Improve usability
Graphical query interface

Improve usability
Ontology browser

Improve usability
Annotation mode

Improve usability
Annotation mode
Ontology browser

Improve usability
WYSIWYG editor

Improve usability
Annotation mode
Ontology browser
WYSIWYG editor

Get better search results
Augmented search results
Path search
Semantic tree view
SMW blends text and data; this requires augmenting classic retrieval
and navigation features with semantic data.

Enforce security policies for text and data
Protection of content and data
Protection of annotations and queries
User group management
Commercial environments require integration with central directory
services and fine grained access rights to semantic data and content.

Leverage data re-use and improve consistency
2. Select available webservices
Import legacy data and tab data from web services to embed the Wiki
into a team’s data-environment. Data inconsistencies are automatically
detected to improve data quality.
3. Embedding webservices in articles
1. Attach webservices using GUI

Powerful data processing
Enhanced data model
Professional Wiki communities request the ability to formulate complex
relationships in the Wiki (e.g. rules), which are processed automatically.
Form based rule editor

Reduced administration overhead
Reduce the efforts for checking for compatible upgrades to a
SMW installation and for downloading and installing new
extensions.

Where to get it?
Get a copy: http://sourceforge.net/projects/halo-extension/
User forum: http://smwforum.ontoprise.com
It‘s all for free and GPL!*
*) Except OntoBroker and Triple store connector which are ontoprise licenses.

too complicated?
then get all these features within 5 minutes:
Product home page: http://wiki.ontoprise.com

Semantic Forms
Utilizing the semantics
Facilitating data input

Benefits of Semantic Forms
To make MediaWiki templatesbetter to use
To provide a form-like User Interfaces for inexperienced users to input data
To associate forms with a category
Have a helper form to help wiki admins or advanced userscreate forms
Variations to provide further usability enhancements

Image: Using a (basic) Form

Image: Using a (long) form

Image: Form with a (simple) style
http://www.thethirdturn.com/w/index.php?title=Form:Driver&action=edit

Image: Form with auto-completion
Advanced Auto-Completion on Customized Query Results
Basic Auto-Completion on Static Permitted Values

Remember Special Properties?
“Has type” is a special property
a pre-defined property for meta-data
Example: [[Has type::Type:Date]]
“Allows value” is another special property
To specify the permitted values for the property
Example:
[[Allows value::Low]]
[[Allows value::Medium]]
[[Allows value::High]]

Form Field Input Types
String, Page, Number – text entry
Text – TextArea
Boolean – checkbox
Date – date input or Javascriptdatepicker
“Enumeration” (Page or String with “allowed values”) - DropDown list or RadioButton
List of "Enumerations" - ListBoxor CheckBoxes

Creating Forms: on Form Page

More On Auto-Completion
Basic auto-completion is on “Allowed values”
Current standard is on either category or property
Advanced auto-completion is based on queries
{{{field|story|autocomplete on query=[[Category:Project stories]]
[[Project sprint::<q>
[[Sprint start date::<{{CURRENTYEAR}}/{{CURRENTMONTH}}/{{CURRENTDAY}}]]
[[Sprint end date::>{{CURRENTYEAR}}/{{CURRENTMONTH}}/{{CURRENTDAY}}]]
</q>]]}}}

Helper Forms

Helper Form : Create a Template

Helper Form: Create a Form

Helper Form: Create a Class

Special Pages:
Special:CreateForm - lets a user create a new form for adding/editing data. (See example of page)
Special:CreateTemplate - lets a user create a new template. (See example of page)
Special:CreateProperty - lets a user create a new property. (See example of page)
Special:CreateCategory - lets a user create a new category. (See example of page)
Special:CreateClass - a page that creates all the elements for a single "class" at the same time - properties, template, form and category (See example of page). Access to this page is dictated by the 'createclass' MediaWiki permission; by default, it is available to all logged-in users.
Special:FormEdit - lets a user either create or edit a page using a user-defined form. (See example of page.) (This page was, until version 1.9, two separate pages: "Special:AddData" and "Special:EditData".)
Special:FormStart - used to route a user to either 'FormEdit' or the relevant page's "edit with form" tab. This page should not be accessed directly by users. (This page was known until version 1.9 as "Special:AddPage".)
Special:Forms - lists all form pages on the site. (See example of page)
Special:RunQuery - lets a user run a query, using a form (See example of page)
Special:Templates - lists all templates on the site. (See example of page)
Special:UploadWindow - lets a user upload a file; very similar to the standard Special:Upload page, but without the skin. This page is called from within a form, and should not be accessed directly by users.

More Info
On MediaWiki.org
http://www.mediawiki.org/wiki/Extension:Semantic_Forms
SMW User Forum (ontoprise GmbH) http://smwforum.ontoprise.com/smwforum/index.php?title=Help:Creating_Semantic_Forms&context=Help%3ASMW%2B+1.5.0

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Outline
Break (30 mins)

SMW:: powerful tools and contents
Semantic MediaWiki and related extensions have more potential power

Need Release ::The (more) Power
Be used by morepeople
Content in moreplaces
Accessible via moreapplications
Enhanced with moresemantics
The more users
The better

Need ::Workflow Integration + Usability Enhancements
InfrequentWiki users frequentlyforget where the wiki pages are located
Search is a break from current workflow
Search result can be noisyorirrelevant
Usability:
Wiki/Template/SF markup syntax is not extremely hard, but enough to turn off many users
To locate and consume info in SMW is just not easy enough, need something better
Why don’t we leverage Microsoft Office suite?

Microsoft Office ::The Most Popular Productivity Suite

WikiTags:: How It Works
Leverage Microsoft SmartTags technology
Bring SMW info to Office applications on-demand
API for semantic data I/O
Utilize semantics to improve relevance
Smart actions for semantic properties
SmartTag
Add-ins
API
API
Connections
Smarts

Some Semantic Wikis
Before the demo, let’s look at
For more info, go to
http://wiking.vulcan.com/dev/

Wiki:: Semantic Sci-Fi Movie
Familiar content just like another wiki
Semantic markups shown in fact box

Wiki:: NGT - Proposal Handling

Wiki :: Agile Project Management

Project Wiki for Milestones, User Stories, Developer Tasks, etc.
Page is form- based, with queries and semantics built-in

Live actions
Now see the demo
http://wiking.vulcan.com/dev/

Backstage::WikiTags Extension
Wiki Validation
Authentication
To get the categories
And descriptions
To get the article titles
To get the semantic properties
To get page info
Get all available forms
Save page as a form
Save page with dataset
Set form of a page
Create form templates
To upload into the Wiki
http://wiking.vulcan.com/dev/index.php/SMW_Webservice_APIs

Extension to facilitate semantic data exchange
Web UI to make semantic schema mapping for semantic wiki templates and forms
Web service APIs to do the same
http://wiking.vulcan.com/dev/index.php/SemanticConnector_extension
Backstage::Semantic Connector

Special:ApiTest :: Results in JSON

Recap of demo
What to take away from the demo
http://wiking.vulcan.com/wikitags/

Semantic Info::Across Office Apps
Dynamic Query Results from the article page
Outlook
Multiple Wiki Sites supported
Excel
Via SmartTags
WikiTags recognizes smartly the keywords or phrases relevant to you

Semantic Info::In Real-time
Explore related real-time semantic info across the links in article
See articles in categories live

WikiTags::Semantic Actions
Semantic actions are based on semantic services of properties

Wiki Forms::In Microsoft Office
View Semantic Content in familiar forms
Contribute into Wiki articles back

Screenshots::WikiMail

Upload Emails into Wiki
Manual upload
Automatic upload by folder mapping
Conflict handling
Heuristic category
Use recipients, folders and text

Shortcut to create wiki articles
Customize Categories
Conflict Resolution

Screenshot::Email in Wiki
Attachments automatically uploaded too

Screenshots::Settings
Option to choose categories of interest
and more

WikiTags::Smart Connections

Consume relevant, targeted information
With the tools you are already familiar with
In the context – better relevance and productivity
Only when you need it – no information overload
In place – no search overhead to break workflow
In real time – data from wiki is live
Let you contribute to Wiki
Without knowing where the content is
Without learning wiki/template syntax

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Break (30 mins)

Making SMW smarter - Agenda
RDF and Semantic MediaWiki (SMW)
Current limitations of SMW
What is a triple store?
What is the Triple Store Connector?
Examples
Derived properties
Semantic data integration (demo!)
Where to get it?
Wrap up

RDF and Semantic MediaWiki
RDF (Resource Description Framework) is the underlying data model of the Semantic Web and essentially also for SMW.
RDF is a graph-base datamodel, i.e. all data is represented in the form or nodes that are connected via directed, labeled arcs. Two nodes connected by a arc should be interpreted as a subject-predicate-object statement (triple).
Examples of three triples.
SMW stores such triples in the underlying relational database

Current limitations of SMW
SMW is a great semantic Web application, in the sweet spot between feature richness and engineering complexity.
Limitations:
Triple stores overcome these limitations.

What is a triple store?
A triple store is a dedicated database for storing and retrieving RDF data.
Features:
Ontoprise’s “Triple store connector" creates a bridge between SMW and a triple store.

What is the Triple Store Connector?
Triple Store Connector
Semantic MediaWiki
halo Extension
Triple Store
The Triple Store Connector[1] is a ready-to-use product from ontoprise which is installed along with SMW and attaches it to Jena[2] or OntoBroker[3].
[1] http://smwforum.ontoprise.com/smwforum/index.php/Triple_store_connector
[2] Open source triple store with reasoning capabilities, http://www.openjena.org/
[3] Highly scalable semantic Web middleware, http://www.ontoprise.de/en/home/products/ontobroker/

Examples
Derived properties
We formulate a rule in the Wiki to derive a property value from other properties (e.g. calculation).
Advantage: reduced amount of annotations, improved data consistency and enriched knowledge.
Semantic data integration
An enterprise integrates sources of legacy data into one single source and publishes this data in the Wiki.
Advantage: data from rigid legacy systems is available for highly collaborative and flexible workflows.

First example – derived properties
We have a Wiki which is used for generating bids; the project team wants to calculate the estimated costs of each task from the estimated work efforts which are given in person days.
Want to try out this example by yourself?
Go to our online demo installation and create an account:
http://smwdemo.ontoprise.com

Preparing the ontology

Formulating the calculation rule

Applying the rule

Benefits
We learn from this example:
Authoring rules in a triple store connector-backed Wiki is making it a powerful data processing tool.

Second example: semantic data integration
Large corporations have to deal with data silos making integrated views onto data hard to achieve.
Resulting problems:
We require a Wiki which is giving access to semantically integrated legacy data.

Architecture (draft)
Ontology engineering application (OntoStudio)
Semantic MediaWiki
Triple Store Connector
OntoBroker
Web
services
RDBMS
RDBMS
RDBMS
RDBMS

Demonstration: Workflow
We want to provide a Wiki community with legacy data about book titles[1], the community queries the data in the Wiki and enriches it with socially curated metadata.
Steps:
Integrate relational data: the knowledge manager uses the ontology engineering tool „OntoStudio“ to attach the RDBMS to OntoBroker and to generate the ontology integrating the data about book titles into the Wiki.
Query the integrated data: the user queries the Wiki for the book titles to generate a personalized views which can be embedded into articles.
Curate the integrated data: the user tags (“annotates”) individual book titles with new meta data which can be used in queries again.
[1] http://msdn.microsoft.com/en-us/library/aa238305(SQL.80).aspx

Demonstration

Benefits from integrating legacy data into the Wiki
We learn from this example:
Data from rigid legacy systems are available in highly collaborative and flexible workflows.

Where to get it?
Option 1: You are a beginner and just want to give it a try:

study examples online in the smwforum: ref. [1]
try them out in the online demo system: ref. [2]

Option 2: You want to make your SMW installation smarter:

get the halo extension for free: ref. [3]
get the Triple store connector basic for free: ref. [4]

Option 3: You require a smart Wiki for your team or department:

get SMW+, the Semantic Enterprise Wiki: ref. [5]
get the Triple store connector basic for free: ref. [4]

Option 4: You to go enterprise level?

get SMW+, the Semantic Enterprise Wiki: ref. [5]
get the Triple store connector professional: [email protected]

[1] http://smwforum.ontoprise.com/smwforum/index.php?title=Help:Creating_rules&context=Help%3ARule+Knowledge+Extension+1.1.0
[2]http://smwdemo.ontoprise.com
[3]http://smwforum.ontoprise.com/smwforum/index.php/Help:Halo_Extension_User_Manual
[4]http://smwforum.ontoprise.com/smwforum/index.php/Help:Installing_the_Basic_Triplestore_1.2_with_Installer
[5]http://smwforum.ontoprise.com/smwforum/index.php/Download

Take home message

Semantic MediaWiki is a great tool! But it has limitations with regard to the query language, data processing and data integration capabilities.
SMW can be improved by further semantic extensions, such as the HALO extensions.
SMW becomes versatile and smarter by using a triple store with reasoning capabilities, e.g. for reasoning and semantic data integration*
Interconnect an entry-level triple store or an enterprise-level triple store to SMW with ontoprise‘s Triple store connector.
Read more here: http://wiki.ontoprise.com

*) With OntoBroker.

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Break (30 mins)

Better Wiki I/O
Better workflow integration
On-demand client UI using wiki data
Smarter WikiTags matching (IR tricks)
Subversion and other tools integration
Multi-model authentication support (NTLM etc.)
Automatic and more powerful forms
For more info, visit http://wiking.vulcan.com/dev/Wiking

SMW+ and the halo extensions
We make SMW a citizen of the Web of Data
import (or remote query) and map linked data sources in the Wiki
use data in queries
publish data
Jesse Wang & Daniel Hansch - SemTech 2010

Usability improvements
Renovated graphical query interface
Faceted browsing
Notifications on semantic data

Easier knowledge formulation
Tabular forms
Easier semantic forms
Generating forms automatically
..and much much more!

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Questions?