=Paper=
{{Paper
|id=Vol-206/paper-4
|storemode=property
|title=Creating and using Semantic Web information with Makna
|pdfUrl=https://ceur-ws.org/Vol-206/paper4.pdf
|volume=Vol-206
|dblpUrl=https://dblp.org/rec/conf/semwiki/DelloST06
}}
==Creating and using Semantic Web information with Makna==
https://ceur-ws.org/Vol-206/paper4.pdf
Creating and using Semantic Web information
with Makna
Karsten Dello, Elena Paslaru Bontas Simperl, and Robert Tolksdorf
Freie Universität Berlin, Institut für Informatik,
AG Netzbasierte Informationssysteme, Takustr. 9, D-14195 Berlin, Germany
{dello,paslaru,tolk}@inf.fu-berlin.de
http://www.ag-nbi.de/
Abstract. Combining Wiki and Semantic Web technologies is consid-
ered by many members of the two communities as a promising alternative
to current approaches for collaboratively creating and using information
on the Web. The user-friendliness of the former as regarding multi-site
content generation and the power of semantic technologies as w.r.t. or-
ganizing and retrieving knowledge are likely to complement one another
towards a new generation of Web-based content management systems.
Our system Makna (stands for “knowledge” in Indonesian) elaborates
on this ideas by extending the Wiki engine JSPWiki with generic, easy-
to-use ontology-based components for authoring, querying and browsing
Semantic Web information.
1 Introduction
Combining Wiki and Semantic Web technologies is considered by many mem-
bers of the two communities as a promising alternative to current approaches for
collaboratively creating and retrieving information on the Web. The success of
the former is primarily due to their simplicity and user-friendliness; a Wiki is a
hypermedia system consisting of a collection of interconnected Web documents,
which can be accessed, revised and extended by arbitrary parties with the help of
a simplified hypertext syntax. However, while Wiki systems are targeted at col-
laborative authoring, they still need means to organize and retrieve the created
content. Though its importance is widely acknowledged among Wiki solution
providers, this issue is marginally addressed in current implementations, which
restrict to organizing Wiki articles/pages according to a manually defined (and
maintained) set of categories.
The Semantic Web provides the technological infrastructure to alleviate this
situation. RDF statements can be applied to enhance the semantics of Wiki
pages and of the links between them, while ontologies and associated reasoning
services are a valuable extension to currently employed plain topic classifications
and information retrieval capabilities. Figure 1 illustrates this idea with a simple
example: the relationship between the Wiki article introducing the American ac-
tor Humphrey Bogart and the one describing his home town New York is related
by the typed link livedIn, a property defined in a particular domain ontology.
2 Dello, Paslaru, Tolksdorf
The interconnected articles themselves are annotated with typing information,
according to which they are classified as an instance of the concept Actor and
City, respectively.
someOntology:Actor SomeOntology:City
http://en.wikipedia.org/wiki/Bogart http://en.wikipedia.org/wiki/NewYork
someOntology:livedIn
Fig. 1. Typed pages and links
Complementarily the Semantic Web can utilize Wikis as support tools in
various application scenarios, the most important being probably distributed
knowledge engineering and semantic content generation. The usage of Semantic
Web technologies is currently inconceivable without a high level of IT expertise,
with the consequence that the amount of Web information available in languages
like RDF(S) and OWL is minimal compared to the dimensions of the traditional
Web. In order for the Semantic Web to overcome this technical barrier of entry
there is a need for tools which allow humans to contribute to the creation of
Semantic Web content transparently from the underlying technologies.
In this paper we elaborate on these ideas by implementing Makna, a Wiki-
based tool for distributed knowledge engineering.1 Makna extends an existing
Wiki engine (in our case the Java-based JSPWiki system)2 with generic, easy-
to-use ontology-driven components for collaboratively authoring, querying and
browsing Semantic Web information. In contrast to similar attempts for combin-
ing the two fields of research, our system explicitly focuses on the immediate and
comfortable exploitation of the semantic content, while implementing many key
features of hypermedia systems targeted at supporting distributed knowledge
engineering processes [4, 14, 18, 21].
The remainder of this paper is organized as follows. Section 2 specifies a
set of core requirements to be fulfilled by the Semantic Wiki implementation.
Building upon these we discuss the design principles and the architecture of the
Makna system in Sections 3 and 4, respectively. Details on the implementation
are presented in Section 5. We compare our solution with related approaches
in Section 6 and conclude with a summary of future research and development
directions in Section 7.
1
http://makna.ag-nbi.de
2
http://www.jspWiki.org/
Creating and using Semantic Web information with Makna 3
2 Requirements analysis
A Wiki system can be understood as a collection of simplified hypertext docu-
ments which are read and edited by a community of Wiki users[5].
In relation to the rapid growth of the amount of information available within
a Wiki system, its users need means to locate the relevant content, prior to ac-
cessing, creating or modifying it in any form. This task is commonly approached
with the help of keyword-based information retrieval mechanisms. Mainstream
Wiki implementations maintain a full-text index of their contents and provide
users with the possibility of formulating unstructured queries in a simple query
interface.3
The limitations of this simplistic approach become visible when Wiki users
necessitate very specific information on a particular topic or information which
is distributed over multiple pages. These use cases can not be successfully real-
ized using keyword-based search algorithms executed on a plain set of textual
documents; in turn they require heuristics which take into account the semantics
of the underlying domain and of the links between individual Wiki contents. We
illustrate these issues by means of two simple examples in the movies domain. A
query like Who was the actor Humphrey Bogart married to? by Wikipedia
delivers—if formulated properly—a list of movies starring the actor, as well as
the Wiki article containing his biography. Though the encyclopedia contains a
page dedicated to the prominent wife of Humphrey Bogart, the actress Lauren
Bacall, this information can not be exploited without human intervention, in
the absence of machine-processable domain knowledge and of an adequate link
mechanisms between the two pages. Further on, a search for American actors
in the same information repository returns a set of Wiki entries containing actor
biographical information, but also dozens of movies or other types of articles.
In order to improve the precision of such general queries, Wiki systems need to
implement mechanisms for typing Wiki pages according to pre-defined schemes
(such as ontologies).
To summarize, typing Wiki articles and the links interrelating them by means
of ontologies enables the implementation of advanced content- and structure-
oriented retrieval facilities.
Another aspect to consider is context-based navigation. Wiki systems rapidly
tend to contain an impressive number of internal links.4 If the relation between
Wiki pages would be represented in a precise and formal way—and that is ex-
actly what Semantic Web technologies provide—the Wiki engine could provide
facilities to semantically navigate between meaningfully related resources, such
as the articles dedicated to the aforementioned actors.
Besides domain-focused search heuristics and semantic navigation, ontology-
driven technologies provide additional advantages to organizing and retrieving
3
Often users are re-directed to a page by search engines like Google who have spidered
the Wiki contents, integrating it into their own index.
4
As stated at http://stats.Wikimedia.org/DE/TablesWikipediaEN.htm the Eng-
lish Wikipedia contained 19.3 million internal links to 922.000 articles as of Novem-
ber 2005. This is a rate of approximately 21 out- and in-links per article.
4 Dello, Paslaru, Tolksdorf
knowledge in a Wiki system. If Wiki contents were classified according to an on-
tology, this could be utilized as a commonly agreed query vocabulary, enabling
users to formulate more precise and structured queries. Further on, formally rep-
resented ontologies in correlation with reasoning services are an ideal means to
operationalize various quality assurance procedures, which become indispensable
in any loosely coupled collaborative content authoring endeavor [1]. A third use
case is the automatic link computation; given a semantic classification of Wiki
articles, the system could consult the ontological content in order to automati-
cally detect links to semantically related resources. According to a recent study
by [1] the lack of adequate support for link creation and management is one of
the key usability problems encountered within Wiki systems.
The aforementioned issues correspond to well-established requirements for
so-called “forth-generation hypermedia systems”. As stated in [4, 21] advanced
Web-based hypermedia systems—including Wikis—can take benefit from imple-
menting features such as5
– typed annotated nodes
– typed attributed links
– computed links
– personalized links
– content- and structure-based search
– content- and structure-based navigation
– multiple view presentation
On the other hand, while extending Wiki technologies with semantics defi-
nitely contributes to the realization of advanced search and browse facilities, it
also imposes several additional system requirements at both functionality and
usability level. First, the system should provide a concept for the consistent
authoring and manipulation of semantic information. This issue relates to the
usage of the system ontologies, but also to the development of the ontologies
themselves. The former primarily requires means to reference ontological prim-
itives within content generation tasks. The latter, however, induces the need
for methodological and technological support for collaborative knowledge engi-
neering tasks. This non-trivial research question, recently tackled in approaches
such as [9, 14, 18] solely at methodological level, is still in its infancy in the Se-
mantic Web community. Usability requirements mainly refer to transparency
and performance issues, as semantic technologies are not necessarily popular for
seriously addressing any of them yet.
3 System design
Accounting for the results of the requirements analysis the realization of Makna
system was influenced by two categories of design decisions, which are introduced
in the remainder of this section.
5
Hypermedia systems differentiate between nodes and links. Nodes denote information
objects (e.g. documents, or document fragments) which are connected to each other
by means of links.
Creating and using Semantic Web information with Makna 5
3.1 Minimally invasive Wiki extensions
The first category of design decisions has the objective to preserve the advantages
provided by conventional Wiki technology while enriching its capabilities.
The new engine should support the same usage patterns as traditional ap-
proaches. In particular this applies for the hypertext syntax employed, which
need to extended with dedicated keywords. Further on, the system should pro-
vide an easy-to-use concept for the creation and management of semantic data
[1]. This should allow Wiki users to annotate plain Wiki content in terms of
adding, deleting or modifying RDF statements. However, as our system is not
targeted at collaborative ontology engineering yet, it is not reasonable to permit
arbitrary users to perform changes at ontological level. Without an adequate
methodological support an uncontrolled ontology evolution might have consid-
erable implications on the way Wiki data is classified and subsequently retrieved
[8, 14, 17, 18, 20]. The manipulation of the employed ontologies as well as the
import of semantic instance data are therefore currently limited to a particular
group of users e.g. administrators (cf. Figure 3).
Technologically the minimal invasive character of Makna is reflected in the
decision to build upon existing Wiki systems instead of an implementation from
scratch (as for example in [2, 15, 19]). The benefits of this decision are twofold.
First re-using established implementations has clear costs and quality advantages
[7, 11]. Another motivation is related to the philosophy that “the Semantic Web
is not a separate Web but an extension of the current one.”[3]. Following this
idea it should also be possible to turn an existing Web application like a Wiki
engine into an Semantic application by plugging in the necessary extensions.
3.2 Versatile use of semantic technologies
A Semantic Wiki should provide facilities for flexibly integrate and use arbitrary
Semantic Web ontologies available on the Web. This implies the possibility to
refer to multiple ontologies at Wiki syntax level and their seamless usage in
classification, retrieval and navigation tasks.
Wiki users should be able to comfortably access available ontologies in order
to suitably annotate Wiki articles. This can be achieved by providing dedicated
components to facilitate the interaction with the ontological content (cf. Section
5).
Inference is another important point to consider. Reasoning services can be
applied on Wiki contents in order to enhance the retrieval capabilities of the
system or to exercise consistency checking in relation to specific quality assurance
procedures. However, it might be necessary to restrict this feature to a carefully
defined set of ontologies, as inferencing on arbitrary ontologies on the Web could
under circumstances lead to serious performance problems.
Complementarily to the integration of multiple Web ontologies the engine
should provide means to import and export data formalized using Semantic
Web representation languages.
6 Dello, Paslaru, Tolksdorf
Finally we consider the relations between pages which are not naturally rep-
resented as hyperlinks. This can be solved in the same way in which links between
non-existent pages can be created. If it is not required that statements are exclu-
sively formulated in the Wiki syntax the problem resolves, thus making available
RDF data representable as Wiki instance.
4 System architecture
The architecture of the Makna system is depicted in Figure 2. It consists of the
Wiki engine JSPWiki, extended with several components for the manipulation
of semantic data, and the underlying persistent storage mechanisms. We chose
JSPWiki, because it is written entirely in Java and has a clear design structure
(i.e based on the Model-View-Controller-Pattern) facilitating system extensions.
The Jena API was used as de facto standard Semantic Web framework for cre-
ating, managing and querying RDF data.
Additionally we used a relational database for the persistent storage of the
semantic model. The persistent storage of the Wiki pages and attachments can be
provided through any of the versioning storage provider modules for JSPWiki.6
JspWiki Wikipages and
Attachments-Storage
(Filesystem,Database,
CVS,SVN,...)
Semantic Wiki
Additions
SemWeb
-Storage
Jena (MySQL,PostgreSQL
or Oracle)
Fig. 2. Makna architecture
Due to the fact that our system currently does not include any mechanisms
for collaboratively constructing ontologies, we differentiate between two types of
semantic data: the ontology data and the instance data. This distinction is simi-
lar to the common terminology in Description Logics (or OWL) and corresponds
to different ways of creating and manipulating the data within the system. On-
tologies are expected to be imported to the Wiki instance by administrators.
These can revise or extend them using external tools (such as conventional on-
tology editors). The instance data is the sum of
– the RDF statements formulated in Wiki syntax by the users
6
http://www.jspWiki.org/Wiki/PageProvider
Creating and using Semantic Web information with Makna 7
– the statements manually added by the user (using assistants, see below)
– and the (external) instance data imported by the administrators
This separation is reflected in the restriction that the ontology data can be
modified solely in the administrator interface, while the instance data can be
manipulated in diverse ways in the Web interface by arbitrary users (cf. Figure
3).
modifies
Wiki Administrator Ontology
import Data
Reasoner Inference
Model
Instance
uses Data
Wiki User
modifies
uses
reads
reads External
Information Provider
Fig. 3. Separation between ontology and instance data
The administration interface is responsible for the ontology- and configuration-
related functionality:
– specify the ontology/ontologies used within the system
– import external RDF data
– define shortcuts for a more comfortable usage of ontological primitives
– configure inference engines and persistent storage systems.
The user interface embeds facilities for creating and using Semantic Web
information on the basis of the imported ontologies:
– refer to ontological primitives for annotating Wiki content or defining link
types
– formulate and execute content- and structure-based queries
– browse the Wiki contents on a content- or structure basis
– export semantically represented data as RDF or N3.
Details about the implementation of these features are discussed in the next
section.
8 Dello, Paslaru, Tolksdorf
5 Implementation
5.1 Authoring semantic content
Wiki users are able to create semantic content (in form of RDF statements
referencing pre-configured ontologies) in the classical Wiki manner. They are
provided with an extended Wiki syntax and with assistant tools simplifying the
interface to the ontologies employed. Further on, users can create, modify and
delete RDF statements associated with Wiki pages.
Extended Wiki syntax In JSPWiki’s syntax a link is represented by []
where is either an absolute URL or another page in the Wiki.
Fig. 4. Makna syntax
We extended this syntax to [!] to support semantic link-
ing.7 This extended link element creates a semantic statement, in which the URI
of the edited page is the subject, is the predicate and is the ob-
ject. Figure 4 presents the edit-page corresponding to the Wiki article on Ingrid
7
The exclamation mark was selected because it has no other function in links in
JSPWiki syntax.
Creating and using Semantic Web information with Makna 9
Bergman, which is depicted in Figure 7 below. can be an URI, but more
likely either a shortcut or a namespace:predicate combination from the resources
configured in the Wiki instance. In order to support statements with literals, the
range of was extended too. If is enclosed in hyphens, the
system recognizes it as an literal and creates the statement accordingly.
Interactive Assistants In order to support the user formulating accurate se-
mantic links in the proposed Wiki-syntax we integrated several interactive as-
sistants based AJAX[6]. We will limit our description here to those two assistants
which have been integrated into the edit-page of the Wiki: the predicate assis-
tant and the page assistant. The former guides the user in finding a predicate in
the configured ontologies. The latter assists the user in seeking for the names of
other pages in the Wiki.
Figure 5 illustrates the functionality of the predicate assistant. The user
enters the term mail and a drop down list with the matching predicates is
automatically created. After selecting a predicate from the list, the text area
below is updated with detailed information about the selected predicate.
Fig. 5. Predicate assistant
As soon as the user starts typing into the input field, an asynchronous request
is sent from the client-browser to the server in the background, which returns an
XML-document with the matching terms. These terms are compared on a lexical
basis to the natural language labels of the corresponding items (predicates and
Wiki pages, respectively).
Our system also supports statements which do not appear in the Wiki pages
themselves. This means that meta-statements can be expressed, and links be-
tween two non-existent pages and/or from external resources can be formulated.
10 Dello, Paslaru, Tolksdorf
The associated assistant provides a simple interface which allows users to access
the content of available ontologies in order to specify subjects, predicates and
objects of new statements. Figure 6 depicts this functionality: after selecting the
FOAF-ontology, the assistant updates the predicate form with the corresponding
information (top part of Figure 6); depending on these two parameters the as-
sistant further computes appropriate object resources (bottom part of the same
figure)
Consistency of the semantic model The consistency of the semantic model
can be guaranteed by our implementation. To achieve this we implemented two
functions. If a statement is submitted by the user with the syntax-external as-
sistant (cf. Figure 6) we check its validity immediately; in case the statement is
found to be invalid according to the semantic model it is rejected and the user
gets notified. The same happens if the statement is found to cause inconsisten-
cies in the model. The other function is the verification of statements which are
formulated in the Wiki syntax. After the edited page is submitted the system
extracts all semantic statements and checks if they are consistent with the se-
mantic model. If statements are found which cause inconsistencies, the user is
returned to the edit page, gets informed about the details of the problem de-
tected and is asked to correct his input. By doing so we assure that the semantic
model is always consistent, as there is no possibility to add statements that cause
inconsistencies.
This behavior is currently being refined in order to support application sce-
narios with loose consistency requirements. In conjunction to the extension of
our system towards advanced collaborative ontology engineering support (cf.
Section 7) we are examining ways to ensure local consistency on personal on-
tologies, while the global shared ontology does not have to satisfy this (sometimes
unfeasible) constraint.
5.2 Context-based presentation and navigation
When a call to a Wiki page is issued the Wiki engine extracts a subgraph of
the semantic model which contains all statements which have the current page
either as their subject or their object—no matter if they were formulated in the
Wiki syntax or elsewhere.
In Figure 7 we illustrate the Wiki article about the actress Ingrid Bergman
in a fictive Makna movie instance. The navigation block on the right side of
the screen consists of two parts: the summary of the semantic relations of the
current page (on the top) and the list of the prepared search requests for related
resources (on the bottom).
The summary of the semantic relations can help the user to quickly navigate
to a related topic in one step (i.e. one click). The customized links to searches
for related pages are created through the following scheme: for each property of
a page a search link is provided to find other resources with the same property.
This is true for incoming links as well, which means that is is possible to navigate
Creating and using Semantic Web information with Makna 11
Fig. 6. Statement assistant
12 Dello, Paslaru, Tolksdorf
Fig. 7. Makna article on Ingrid Bergman
quickly to other resources which have the same relation to the current page. Both
functions work with inference (which can for convenience be switched on and off
by the user), thus enabling the user to navigate the Wiki contents conducted by
semantic relations.
5.3 Content- and structure-based retrieval
Makna implements a search interface resorting to form-based search patterns,
which allow users to use the ontology in formulating structure-based queries and
the underlying inference engines for enabling semantic search.
We have developed several templates for comfortably formulating typical
content- and structure-based query patterns. Figure 8 shows the implementation
of a template returning instances of a user-defined class in a knowledge base.
After choosing a vocabulary from the left drop-down list, the right list is filled
up with all concepts from the chosen ontology.
6 Related Work
A multitude of promising approaches for combining Semantic Web and Wiki
technologies are currently under development (cf., for example, [2, 15, 16, 19, 22]).
Creating and using Semantic Web information with Makna 13
Fig. 8. Form for a simple semantic search
However, while these proposals share the declared common goal of realizing a
Semantic Wiki system, a closer investigation of their—planed or implemented—
features evidences that they are oriented at slightly divergent application sce-
narios.
Approaches such as [16, 19] develop Wiki engines which support the genera-
tion of RDF data. However, they clearly distinguish between semantic and plain
Wiki contents and their usage in Semantic Web context requires technical ex-
pertise on RDF. Acknowledging for this limitations more recent proposals focus
on the minimal invasive usage of semantic technologies within Wiki systems[2,
15, 22]. Makna differs from these approaches from a multitude of viewpoints. In
contrast to WikSAR [2] our system is oriented at non-technical users exercising
collaborative knowledge engineering. This focus motivated a different design of
the user interfaces. Further on, the present implementation of Makna restricts
the access to ontological knowledge (as opposed to instance knowledge) to a pre-
defined set of Wiki users. While this might be considered as a limitation of our
system as compared to other approaches (such as IkeWiki [15]), we argue that
implementing such functionality without adequate process-level support might
have uncontrolled consequences on the operation of the overall Wiki system.
This was confirmed by recent advances in the area of distributed ontology engi-
neering[14, 18]. The Semantic MediaWiki project has come up with a different
approach [10, 22]. Their development aims at turning the hugest existing tradi-
tional Wiki-based information repository—the Wikipedia encyclopedia—into a
semantic Wiki. Similar to our own requirements analysis, the authors identified
the need for typed annotated links and articles in Wikipedia (cf. Section 2). The
current release of the Semantic MediaWiki system shares many commonalities
with the functionality of Makna. In contrast to our implementation it does not
support consistency checking mechanisms and the usage of multiple ontologies.
In turn, it allows for an unrestricted access to both ontological and instance
data, an option which we consider disputable for arbitrary settings without an
14 Dello, Paslaru, Tolksdorf
adequate process support.8 Because Makna focuses on small to mid-size Wikis
we can utilize some performance critical mechanism like real-time inference, en-
abling features like guaranteed consistence of the model and context-based nav-
igation based on real-time state of the semantic model. Furthermore Makna’s
separation of instance and ontology data—accompanied by the user and ad-
ministrator interfaces (cf. Section 4)—enables predictable response times and
memory usage which are the foundation for an efficient Semantic Wiki system.
Finally we mention the SemperWiki approach [12], which introduces Wikis as
enabling technology for personal information management. Unlike conventional
Wiki and Semantic Wiki solutions—including Makna—it is targeted at single
user environments.
7 Outlook
A feasible combination of Wiki and Semantic Web technologies should preserve
the key advantages of both technologies: the simplicity of Wiki systems as re-
garding shared content authoring, as well as the power of Semantic Web tech-
nologies w.r.t. structuring and retrieving knowledge. Building upon an analysis
of the requirements induced by a collaborative knowledge engineering scenario
to Wiki implementations we have introduced our concept of a Semantic Wiki
engine addressing this problem.
We are currently extending the functionality of the current release of Makna
w.r.t. methodological and technological support for knowledge engineering. In
particular we are investigating means to automatically extract ontological struc-
tures from existing domain-focused Wiki instances (following the approach in
[13]) and are implementing a component for collaborative ontology engineering
based on [14].
Acknowledgements
This work has been partially supported by the EU Network of Excellence “Knowl-
edgeWeb” (FP6-507482).
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