DataWiki Semantic Enterprise Wiki v1.7.1

PRODUCT PRESENTATION
VERSION 1.7.X 11/2012

DIQA Projektmanagement GmbH
Pfinztalstraße 90
76227 Karlsruhe
info@diqa-pm.com

Contents

1. DataWiki: Semantic Enterprise Wiki

2. Why are Semantic Wikis Better?

3. Feature Tour of DataWiki
• Creating and Formatting Articles
• Tagging Data
• Querying Data
• Modeling Data
• Finding Content
• Using External Data (“linked data”)

4. Users and Use Cases

5. Getting Started
• Downloads and Contact

DataWiki Product Presentation, 21.11.12 © 2012 DIQA Projektmanagement GmbH | www.diqa-pm.com | Slide 2

DataWiki in a Nutshell

DataWiki is a Semantic Enterprise Wiki for
agile collaboration on rich text and data

It is a wiki Platform for web-based collaboration and quick
authoring and provisioning of content.

It is a database Users embed data in the text that can be
retrieved with powerful yet easy to use query
mechanisms.
It is a data integration tool Integrate various internal and external linked data
sources and make them accessible on a single,
shared platform.
It is enterprise-ready Installs in 15 minutes and comes with business-
critical features. Extendible and scalable.


Contents



• Tagging Data
• Querying Data
• Modeling Data
• Finding Content


5. Getting Started


Text and Data in a Single Tool

• Consensus building process is applied to text and
data
Expert A comes to a different estimate of the
expected work effort than expert B.

• Context of data is given in natural language text
The risk of failure in this project is 50% because
we have never done this before.

• Powerful query language
All employees having worked abroad for at least
2 years and having web development skills?


Visualise Your Data

The integration of text and data allows for easier exploration,
better search results, more meaningful navigation and intuitive
access through visualization.

Charts and Graphs... ...Geo Coordinates... ...and many more


Integrate Linked Data

DataWiki integrates linked data from heterogeneous data-
sources, like enterprise databases, MS-Excel-files.
End-Users can create reports in DataWiki on this data* - by
themselves!

Applications

Enterprise systems,
Legacy DBs Web of Data
*) requires additional software


Contents



• Tagging Data
• Querying Data
• Modeling Data
• Finding Content


5. Getting Started


Feature Tour of DataWiki
-
Creating and Formatting Articles

Create new articles
by clicking this
button. Available
on every page for
quick and easy
access

Feature Creating & Formatting Articles > Tagging Data > Querying Data > Modeling Data > Finding Content
Tour info@diqa-pm.com

Visual feedback in
case an article
already exists

Predefine your own
article types (e.g.
“Report”, “Task”),
which will be
available here

Feature Creating & Formatting Articles > Tagging Data > Querying2012 DIQA Modeling Data > Finding Content
DataWiki Product Presentation, 21.11.12 © Data > Projektmanagement GmbH | www.diqa-pm.com | Slide 11

The WYSIWYG editor
provides all the
functionality
required to create
appealing articles


For example, you
can add tables…


...or images,
supported by
automatic
suggestions based
on existing images
and a preview.


Creating links is
supported by
automatic suggestions
that facilitate
searching and help
avoiding typos.


It has never been
that easy to create
appealing articles in
a wiki!


-
Tagging Data

Next, we will look at
how you can enrich
your articles with
data.


The Data toolbar
helps you with
categorizing an
article and adding
useful data to it.


First, let‘s categorize this
new page.
Upon typing, you are
supported by
automatic suggestions


Based on the
category, the data
toolbar suggests
additional data
that should be
tagged.

The editor instantly
shows that the
article has been
categorized.


By selecting some
text and clicking
this button, you can
add new
annotations.


Again, the editor
gives you direct
feedback that data
has been
annotated.


This is our article
with all the
suggested
annotations.
We‘re done!


The Factbox at the
bottom of each
article gives you a
quick overview of
all the annotations.


-
Querying Data

After tagging data,
we would like to
add a query to see
the results. Click this
button to open the
Query Interface.


This is the Query
Interface. Let‘s start
by asking for a
category.


As usual, DataWiki
supports you with
suggestions


After adding a
category, we can
instantly see the
results of our query in
the preview section.


We can enhace our
result table by
adding properties


The Query Outline
shows us all the parts
of the query.


An icon in the
editor shows us that
there is a query
embedded . It also
allows us to go
back to editing it.


Here we can see the final
result. We can sort by
column, and as soon as
data is added or
changed, the query
results will be updated
automatically


-
Modeling Data

The Data Explorer
provides an overview of
the data that exists in
DataWiki and also allows
to edit it


There are three columns
that show categories,
articles that belong to a
category, and properties
of articles


Each column allows to
add or edit its content via
a microform. Here, we
add a new subcategory.


Changes are instantly
reflected in the UI so you
get direct feedback to
your actions.


By adding a propertie to
a domain (i.e. category),
we can model the
ontology of the wiki.

There are many
predefined data types
for properties, e.g.
number, date, url or geo
coordinate


We can also add new
articles, which will be
automatically annotated
with the selected
category


A context menu provides
quick access for opening,
editing and deleting
categories, articles and
properties


Properties that belong to
the same domain as an
article are automatically
recommended and can
be added quickly


After saving an article...


...changes are available
instantly in the Data
Explorer


-
Finding Content

DataWiki also comes with
a powerful and fast
search feature


On the right, detailed
search results are
presented.

On the left, you can refine
your search results by
selecting available facets


The triangle icons indicate
that you can drill down
further to refine your
search


You can also view all
annotations of an article
by clicking “Show
properties”


-
Using Linked Data

Create queries to visualize
External Data from any
SPARQL 1.1 compliant
endpoint.


Visualise the External Data
and combine it with data
generated by Wiki-users.


Contents



• Tagging Data
• Querying Data
• Modeling Data
• Finding Content


5. Getting Started


Users and Use Cases

• Enterprise Content Management
Technologies to manage an organization‘s
unstructured information, e.g. content- and document
management

• Integrated Collaborative Environments
Technologies where virtual teams do their work, e.g.
project management.

• Linked Data Integration
Integrate heterogeneous data sources and generate
reports on enterprise data that can be shared and
authored collaboratively.


Enterprise Content Management

• Online encyclopedia
and training center
about marine data and
oceanic knowledge
• Authors create
teaching materials in
private sections, and
get them reviewed by
editors before they are
published
• Target-appropriated
presentation of learning
contents based on
semantic metadata


Enterprise Content Management

Benefits of using DataWiki:

1. Increased efficiency of content production
by aggregating content using queries.

2. Ontology of the domain leads to more
adequate metadata (that goes beyond
technical metadata and simple tags).

3. Improved user experience by advanced
navigation, exploration and search tools
that are based on domain data.


Integrated Collaborative Environment

• DataWiki as knowledge
platform for Communities
of Practice
• Captures structured
knowledge about
projects, persons, topics,
organizations etc.
• Discover experts and
related resources for a
certain topic
• Flexible navigation,
semantic search and
multiple entrance points
• Dynamic aggregations
(e.g. lists of projects)


Integrated Collaborative Environment

Benefits of using DataWiki :

1. Ontology of the domain leads to more
adequate metadata (that goes beyond
technical metadata and simple tags).

2. Better support of the individual needs of
project teams by flexible metadata
creation.

3. Better support of knowledge formalization
and consensus building processes


Semantic Data Integration

• Internal self service
portal for R&D staff
• Integration of
Databases containing
information about
production lots,
ingredients of individual
products, results from
tolerance tests, etc.
• Ability to track the
genealogy of each
brand
• Generate reports for
R&D by querying
integrated databases


Semantic Data Integration

Benefits of using DataWiki:

1. The wiki provides an integrated view on the
data using a common ontology. Semantic
queries enable dynamic, customized reports
and visualizations.

2. Legacy data can be complemented with
socially curated data in the wiki. Data models
can be extended easily as required.

3. The wiki foundation fosters collaboration while
the semantic features improve searchability
and ensure compliance.

Contents



• Tagging Data
• Querying Data
• Modeling Data
• Finding Content


5. Getting Started


Get Started Now!

• More information on DataWiki:
http://www.diqa-pm.com/de/DataWiki

• Product Downloads:
http://www.diqa-pm.com/de/Lizensierung_und_Download

• Contact DIQA:
mail: info@diqa-pm.com
phone: +49 (0) 721 609 517 25


Feature Tour and Use Cases

Visit us on http://www.diqa-pm.com

DIQA Projektmanagement GmbH
Pfinztalstraße 90
76227 Karlsruhe
info@diqa-pm.com

DataWiki Semantic Enterprise Wiki v1.7.1

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