ios press semantic wiki engines: a state of the art

Undefined 1 (2010) 1–5 1IOS Press

Semantic wiki engines: a state of the art

Thomas Meilendera,b,∗, Nicolas Jayb, Jean Lieberb and Fabien Palomaresaa A2ZI, 61 ter rue de Saint-Mihiel, 55200 CommercyFranceE-mail: {firstname.surname}@a2zi.frb UHP-Nancy 1 – LORIA (UMR 7503 CNRS-INPL-INRIA-Nancy 2-UHP)FranceE-mail: {firstname.surname}@loria.fr

Abstract. This paper is a survey about semantic wikis and the use of semantic Web technologies by wiki engines. First, itpresents the main notions related to semantic wikis. Then, twelve active semantic wiki projects are compared, according tovarious viewpoints such as knowledge representation philosophy, use of semantic Web standards and system usability. Finally,a formal concept analysis approach is carried out to provide a guideline for the choice of semantic wiki engine, given a set ofneeded features. In conclusion, the paper argues about semantic wiki issues such as the weaknesses of some semantic wiki engineinteroperability.

Keywords: Semantic Web, wiki engine, Semantic wiki

1. Introduction

Conceived in 1995 by Ward Cunningham, wikisare Websites for creating and collaborative editing ofcontent in a simple way [32]. Wikipedia’s popularitydemonstrates the importance of such systems. Mean-while, development of the semantic Web since theearly 2000s opened up new perspectives: it aims at cre-ating an intelligent internet where data are transformedinto knowledge usable by machines. Thus were bornsemantic wikis, whose characteristic is to formalize thecontent of articles, including typed relations betweenthem. Many semantic wiki engines have emerged since2003, with more or less follow-up and success. FrenchSemantic Web site [23] count 39 semantic wiki engineprojects, with 13 active projects.

The article purpose is to compare those differentsystems by studying their characteristics dealing withthe use of semantic Web technologies and the er-gonomics. Section 2 defines semantic wiki notions andthe two main approaches,wikis for ontologiesandon-tologies for wikis, and then gives applications from

* Corresponding author. E-mail:[email protected].

Fig. 1. Mediawiki’s wikitext and its result.

several domains. Section 3 introduces main semanticwiki engines and Section 4 compares them by using aFormal Concept Analysis (FCA) approach. Section 5summaries the survey and draws some conclusions.

2. What is a semantic wiki?

2.1. From wikis to semantic wikis

Traditional wikis are usually based on a set of ed-itable pages, organized into categories and connectedby hyperlinks. They became the symbol of interactivitypromoted through Web 2.0. One of the founding prin-ciples of wikis, which is also the principal vector oftheir popularity, is their ease of use. Wikis are created

0000-0000/10/$00.00c© 2010 – IOS Press and the authors. All rights reserved

2 T. Meilender et al. / Semantic wiki engines: a state of the art

and maintained through specific content managementsystems, the wiki engines. Many languages, known aswikitexts, have emerged to enable structuring, layout,and links between articles. Each system usually has itsown wikitext, as can be seen on Figure 1. At this point,an idea has emerged: to exploit stored pieces of knowl-edge automatically.

Indeed, a limit of exploitation of wikis is illustratedby the questioning of the data contained in these pages.The search is usually through word recognition bystrings, without considering their meanings. For exam-ple, the system cannot answer a query like: "Give listof all currently reigning kings." The solution used inWikipedia is a manual generation of lists. However, themanual generation of all the lists answering queries theusers may raise is, at very least, tedious, if not impossi-ble. This has motivated the introduction of a semanticlayer to wikis.

Since the early 2000s, the emergence of a new visionof the Web can be witnessed: the semantic Web. Thisconcept is described in [5], where the authors definethe semantic Web as an extension of the Web that aimsat structuring data in order to represent their meaning.In other words, the semantic Web relies on formalizedinformation and metadata that allow computer pro-grams or agents to reason about such pieces of knowl-edge. Users are able to find, share, and combine infor-mation more easily. New standards have emerged torepresent and manage knowledge, such as RDF(S) [28]and OWL [27].

Semantic wikis are born of the merging of wikis andthe semantic Web. A semantic wiki is similar to a tra-ditional one in the sense that it is a website where con-tents are added by users. This content is organized intoeditable and searchable pages, accessible to all users.However, unlike the traditional wiki, the semantic wikiis not limited to natural language text. It characterizesthe resources and links between them as shown in Fig-ure 2. This information is formalized and thus becomeusable by a machine, through processes of artificialreasoning.

2.2. Two approaches:Wikis for OntologiesandOntologies for Wikis

For [6], there are two different approaches in theconception of semantic wikis engines. A majority ofthese engines is based on the approach known aswikisfor ontologiesor Wikitology.

The first approach,wikis for ontologies, considerspages as concepts and links as properties. This is the

Fig. 2. Representation differences between a wiki and a semanticwiki.

development of the wiki that leads to the developmentof an ontology that can be further refined. In such anapproach, flexibility and user freedom are favoured,but usability of resulting ontologies is not guaranteed.Indeed, the user should have in mind the already ex-isting concepts and properties in order to avoid dupli-cates. For example, nothing prevents a user to createtwo relations, “has-for-monarch” and “has-for-king”having the same semantics. This can burden the knowl-edge base and have negative consequences for its ho-mogeneity.

The second approach,ontologies for wikis, needs apre-existing ontology. The goal of the wiki engine isto provide tools for populating the ontology with in-stances or, sometimes, new classes. These tools consistmost of the time in multiple choices forms and makeuse of auto-completion. On one hand, this approachlimits user freedom by, for example, reducing the pos-sibility to create new type of links. On the other hand,this approach ensures the coherence of the final ontol-ogy. In this, the wiki can be seen as a meta-data edi-tor allowing the population of the ontology. Thus, thistype of wiki engines is more often dedicated to specificdomains that can be formalized.

T. Meilender et al. / Semantic wiki engines: a state of the art 3

2.3. Outstanding features of semantic wikis

The success of semantic wikis depends on theirability to provide advanced features, aside from fea-tures found in standard wikis. For example, seman-tics should support navigation. This is the case forsome systems featuring faceted navigation that guideusers by recommending relevant resources. Moreover,a semantic wiki should be able to answer advancedqueries. This implies that the engine is able to makesemantic search and not only full text search. Mostof the systems can generate lists of answers thanks toan inference engine. However, the syntax of advancedqueries can be difficult for non expert users.

Semantic wikis should fully integrate the land-scape of semantic Web. For achieving that aim, de-velopments must be compatible with its norms andstandards. Thus, most of the time, annotations aremade with RDF [29] triples, written in different syn-taxes depending on the system. This allows to cre-ate RDF(S) or OWL ontologies that can be reusedby other applications. Accordingly, semantic wikismust propose import/export functionalities. Ontolo-gies can also be consulted with extern query engines,such as SPARQL [30] if an endpoint has been thoughtout. Knowledge can be stored in specialized systemsknown asRDF stores. Meanwhile, some progress arestill to be made in terms of interoperability: most ofthe current systems only offer the possibility to start asemantic wikiex-nihilo or from an existing ontology,despite the growing number of traditional wikis andthe success of some semantic wiki engines. It couldbe interesting to develop methods allowing to integrateinformation stored in well-known and rather completesystems such as Wikipedia. A starting point could beto transform theDBpedia[12] system which includesdata extraction tools for Wikipedia.

Among other uses, semantic wikis are appreciatedas annotation tools. Although editing can be complex,this is much more an ergonomic problem and manywikis offer user friendly characteristics to facilitate theacquisition of RDF triples : forms, WYSIWYG (WhatYou See Is What You Get) editors, auto-completion.

From a more technical point of view, wiki systemsare based on a centralized architecture, with a singledatabase. This means developing strategies to manageconcurrent updates,i.e. simultaneous updates holdingdifferent contents. Peer-to-peer wikis are a solution tothis problem, but few of them consider the semanticaspects.

Finally, wikis are the core of communities of con-tributors. That is why specialized wikis are often builtby communities of specialists. As all contributors donot reach the same level of expertise, or do not have thesame skills using wiki systems, it could be interestingto work on right management tools for semantic wikis.

2.4. Use cases

Semantic wikis have already been tested in manyapplication domains. Among them, the education fieldhas been studied by [17]. In the context of a lessonon formal languages and automates, a classroom hasbeen divided into a few groups, each of whom havingto summarize the previous lesson into a semantic wiki.The teacher interacted with groups using the discus-sions pages. For the authors, the experience was suc-cessful as the semantic wiki became a complementarycourse material and as the student showed better com-mitment.

In another context, Wikitaaable [8] is a semanticwiki used in cooking recipes management. The goal ofthe wiki is to build a shared database of recipes, en-riched by a community of contributors. These latterscan consult, modify, and add formalized recipes, re-lating them with a hierarchy of ingredients, types offood, geographical informations (e.g. Chinese food),etc. The recipes can be annotated and indexed. Theycan further be processed by a case-based reasoning in-ference engine to propose adaptations of recipes.

Semantic wikis also play an important role in indus-try as shown in [19]. The system described in this pa-per has been deployed at EDF R&D, the research de-partment of the French national company of electricity.It aims at capitalizing knowledge about firms and theirsector of activity. This semantic wiki has been built byaround twenty contributors, all new to the domain ofwikis. The system has provided advanced services, inparticular for the classification of firms thanks to ad-vanced queries.

Another use case is OpenDrugWiki [13], a seman-tic wiki in production environments in the field of pro-fessional pharmacological information in psychiatry.About 15,000 articles were generated from PsiacOn-line11, a drug interaction database for psychiatry inGerman. All articles have data-type information andsemantic properties which results in about 150k RDFtriples. A useful application for the staff in the lab

1http://www.psiac.de


is described: given a list of drugs or brand names, itshows all drug interactions, the biological pathways in-volved, and the citations on which the displayed infor-mation is based.

3. Main semantic wiki engines

The objective of this section is to present the seman-tic wiki engines that are the most popular and/or themore innovative. Since this survey is focused on thecollaborative approach of these systems, the systemsdesigned for a sole user, such as Artificial Memory2 orSemperWiki [18], have not been taken into account inthis study.

In the first part (Section 3.1), some projects cur-rently inactive are presented in a chronological order,together with a presentation of their main contribu-tions to the domain of semantic wiki engines. In thesecond part (Section 3.2), currently active projects arepresented: first the projects based on the ontologies forwiki approach, then the projects based on the wikis forontologies approach.

3.1. Early projects

Platypus wiki [7] implements the wikis for ontolo-gies approach and is one of the oldest semantic wikis.It relies on the separation of the text of the wiki pagesfrom the annotations, and uses to distinct editors forthis purpose. The annotations can be made in OWL orin RDF(S) in so-called “‘wiki metadata pages”. It en-ables the edition of ontologies but no test for their con-sistencies, since it does not incorporate an inferenceengine. Furthermore, it only permits simple queries onthe text, not on the ontology. In this context, the goalof the annotation is to improve navigation.

The main difference betweenRhizome [25] and theother systems is the originality of its technical ap-proach. It uses some applications of XLST to RDFsuch as RxSLT for text formatting and RxPath for thequery language. From a conceptual point of view, Itrelies on ZML, a specific wikitext which is closed toRDF and permits to simply identify the properties inthe page. However, its implementation lacks some fea-tures. Indeed, the pages are stored in RDF and thus canbe edited by another system, but there is no system forcontrolling the consistency of the ontology. Moreover,it does not permit advanced queries. Nevertheless, Rhi-

2http://wissensforschung.de/

zome proposes a complex management of user rights,with mechanisms of authorization and validation.

WikSAR [3] proposes an interesting contributionabout the editing mode. Indeed, it permits to edit RDFtriples with a wikitext language easily understandableby the users. From such a text in this wikitext for-mat, it extracts an ontology in which the user can nav-igate thanks to as specific tool (but it does not guarran-tee the consistency of this ontology). It uses metadatasfor proposing a faceted navigation and uses advancedqueries such as “Who is the author ofHamlet?” Previ-ous versions of this system were known asSHAWN.

Kaukulo [11] implements theWikis for Ontologiesapproach in its simplest vision. It contains an editorof RDF triples including an interesting autocompletionmechanism. One can note that this system is the firstone to propose to import RDF(S) ontologies, which isstill relatively rare.

COW [9] follows a similar approach. It proposes astorage of texts separated from the ontology and in-cludes a version management. It also uses the conceptof query model, which enables to automatically list theelements of a page thanks to a query inserted duringthe editing phase.

Several wikis implement the ontologies for wikisapproach.Sweetwiki [6] is one of them. This wikienables to create and to annotate collectively pagesthat may contain different types of resources, suchas texts, photos, or videos. It differs from the wikiscited above on several features. First, the developersof this system has chosen to use standards of the Web(XHTML, XML) and of the semantic Web (RDFa3,RDF(S), OWL, SPARQL). Second, Sweetwiki tries toidentify community by identifying user’s favourite do-main. Thus, it builds a bridge towards the social Web.Finally, it proposes numerous editing tools such as aWYSIWYG editor, an auto-completion system and alite ontology editor.

3.2. Current engines

IkeWiki [20] is often taken as a prototypical ex-ample of the ontologies for wiki approach. It is atool for collaborative knowledge management. It re-quires a preexisting ontology. The knowledge manage-ment uses the Jena framework, in particular its RDFstore and its SPARQL engine. The system offers dif-ferent level of interactions with the user: there are

3http://www.w3.org/TR/xhtml-rdfa-primer/


Fig. 3. Wikitext in Semantic Mediawiki and its result.

functionnalities for novices as well as functionnali-ties for advanced users, that are well-aware of seman-tic Web technologies. Another useful functionnalityis the import from Wikipedia: pages from Wikipediaare imported and can be annotated afterwards thanksto IkeWiki. Its interface is based on Ajax technolo-gies, which enables complex interactions with the user.Two editors are proposed. The first one is used forediting metadata and benefits from an autocomple-tion mechanism. The second one is used for managingthe content and is based on a WYSIWYG approach.Recently, IkeWiki has been extended into theKiWIproject (Knowledge in WIki[21]). Its new goal is to putto the test this vision of wikis in an industrial context,including the issue of project management (manage-ment of teams, of competences, of schedules, etc.).

Semantic Mediawiki [26] is taken as prototypicalexample of the wikis for ontologies approach and is theclosest one to the wiki philosophy. It is an extensionof Mediawiki, the engine used by Wikipedia. For thesake of simplicity for the user, it integrates the RDFtriples editing in its wikitext (see figure 3). In this way,it enables to create typed links that are also useful forindicating the attributes of the page under edition. An-other interest of Semantic MediaWiki is linked with itspopularity: there is a large community of developersaround it, and this community produces many exten-sions, such as editing forms, the integration of an in-ference engine, etc. There are31 such extensions listedon the official site of Semantic Mediawiki4. For in-stance, the Halo extension5 proposes forms, autocom-pletion, a WYSIWYG editor, the integration of audiosand videos files, and the integration of a SPARQL end-point.

SWOOKI [24] is an extension of Semantic Medi-aWiki. Its main originality is that it is intended to solvethe wiki problems that are linked to the centralizationof data. For this purpose, it integrates a peer-to-peerarchitecture and an algorithm for managing concurrentmodifications.

4http://www.mediawiki.org5http://www.projecthalo.com/

SMW+6 is a commercial and extended version ofSemantic Mediawiki. It integrates several extensions,making SMW+ probably the most complete semanticwiki engine. All these extensions are under the licenceGPL and can be integrated to Semantic Mediawiki.

Some systems aim at improving the semantic wikiergonomy by simplifying the knowledge edition. Thisis the goal ofAceWiki [14] which proposes an alter-native to RDF triples. For this purpose, it uses ACE(Attempto Controlled English) that is a sublanguage ofEnglish that can be easily parsed and translated intoFOL (first order logic). Then, these FOL formulas aretranslated into OWL (or SWRL [31] when needed)in order to populate the ontology. So that the syntaxand the lexic of the edited sentences follow the rulesof ACE, Acewiki proposes a predictive editor help-ing the building of the sentence (cf. Figure 4). Eachtime a modification is performed, a consistency test ofthe ontology is carried out, thanks to the inference en-gine Pellet7. Moreover, ACE is also used as a querylanguage. Therefore, the system can answer online toqueries such that “What are the countries having a bor-der with Spain?” in a language close to natural lan-guage.

The main goal ofOntoWiki [2] is also to make theacquisition and the presentation of data easier but itrealizes this goal in a different way: it proposes effi-cient forms and integrate RDF triples directly into thetext in wikitext with the concern of not making it moredifficult to apprehend. Furthermore, it uses interestingfunctionalities such that faceted navigation, advancesstatistics on users, and the integration of Web services(iCal, GoogleMap). Finally, it proposes a managementof user communities.

Some semantic wikis specialized in some appli-cation domains have also been developed, such asBOWiki and SWiM.

The objective ofBOWiki [4] is to propose a tool forcollaborative design of biomedical ontologies. Eachtime a new piece of knowledge is added to the ontol-ogy, BOWiki checks the consistency and rejects it incase of inconsistency. Therefore, the expert work is as-sisted by this consistency checking. The inference en-gine is also used to answer advanced queries.

SWiM [16] is a semantic wiki dedicated to the defi-nition of mathematical notions. It is based on IkeWikiand on the language OpenMath, which is an XML lan-

6http://wiki.ontoprise.de7http://clarkparsia.com/pellet


Fig. 4. AceWiki predictive editor.

guage for specifying the meaning of mathematical for-mulas.

Some wiki engines, such as Subleme and TaOPis,use a different way of representing knowledge.

Subleme8 is an application for information sharing,with a very little documentation. Everything in this ap-plication (text documents, users, access levels, etc.) isrepresented by pages connected by typed links. It doesnot differentiate classes from instances but manage therelation type “is instance of”.

Much more complete and documented,TaOPis [22]proposes tools for editing ontologies based on anobject-oriented formalism. For this purpose, instead ofusing description logics or RDF(S), it uses F-Logic(also known as frame logic), a decidable logic reusingnotions from object-based representation formalismsand of first-order logic. TaOPis integrates Flora-2, aspecific inference engine9, using a syntax of its ownfor advanced queries.

A few commercial systems related to semantic wikishave appeared, such as Knoodl and Wikidsmart. Themost original functionalities of these systems are notfree and the companies developing them do not com-municate with details on the technologies they use.

Knoodl10 can be described as a tool for develop-ment of OWL ontologies and other knowledge basesby communities of users. It incorporates functionnal-ities of import and expert of ontologies, proposes amanagement of advanced queries and a SPARQL end-point. The idea of community is key to this system;each community has its own wiki, integrating its spe-cific vocabulary.

8http://code.google.com/p/subleme/9Actually Flora-2 is the name of an inference engine as well as

the name of a logic extending F-Logic.10http://knoodl.com

Wikidsmart11 is a part of a more complex semanticWeb application whose goal is to propose services forcommercial and human management of companies. Itproposes the same type of solutions as Knoodl.

4. Comparison of semantic wiki engines

4.1. Comparison Criteria

To compare the various active projects, we have re-lied on several criteria, divided into four categories.The first category is about the conceptual approach.We specify which approach is used by the engine, ei-ther wikis for ontologies or ontologies for wikis.

The second category allows to judge the use of se-mantic Web technologies, relying primarily on lan-guage knowledge representation use. The next crite-ria are boolean: whether or not the semantic wiki en-gine has the functionalities of import and export ofontologies. Then, we focus on methods of reasoningand opportunities for internal queries (query type ac-cepted) and external (availability of a SPARQL end-point). Most of the semantic wikis (but not all) use ad-vanced queries, which means queries requiring a rea-soning to be answered.

The third category deals with the usability of thesystem, based on criteria specific to wikis. Annotationmode, editing modes (WYSIWYG editor, forms, etc.),user right management and version management areidentified.

The last section includes information on projects,such as the programming language used, the license,the agency that supports its development, and the sta-bility of the system.

11http://www.zagile.com/products/wikidsmart.html


Table 1

Functionalities of the main semantic wiki engines.


Table 1 compares the systems with the above-mentioned criteria:• shows the presence of the toolwhile ◦ indicates that the tool is not available or notdocumented. It is interesting to note that from a globalperspective, SMW +, KiWI, and Knoodl seem to be themost complete. The first two are references of the con-ceptual approach they implement. We also note thatthe main features expected in a wiki are met by mostsystems and the implementation of semantic web stan-dards is important. However it is regrettable that someinteresting systems such as AceWiki and TaOPis sufferof the experimental nature of their integration in thistype of comparison.

4.2. Classifying Semantic Wikis

4.2.1. Introducing Formal Concept AnalysisFormal concept analysis(FCA) [10] is a mathemati-

cal formalism allowing to derive a concept lattice froma formal contextK constituted of a set of objectsG, aset of attributesM , and a binary relationI defined onthe Cartesian productG×M (in the binary table repre-sentingG×M , the rows correspond to objects and thecolumns to attributes or properties). FCA can be usedfor a number of purposes among which knowledgeformalization and acquisition, lattice and ontology de-sign, and data-mining. The concept lattice is composedof formal concepts, or simplyconcepts, organized intoa hierarchy by a partial ordering (a subsumption rela-tion allowing to compare concepts). Formally, a con-cept is a pair(A,B) whereA ⊆ G, B ⊆ M , andA is the set of all the objects sharing the whole set ofattributes inB. The concepts in a concept lattice arecomputed on the basis of a Galois connection definedby two derivation operators denoted by′:

′ : 2G → 2M

A → A′ = {m ∈ M |∀g ∈ A : (g,m) ∈ I}

′ : 2M → 2G

B → B′ = {g ∈ G|∀m ∈ B : (g,m) ∈ I}

Formally, a concept(A,B) verifiesA′ = B andB′ = A. The setA is called theextent and the setB theintent of the concept(A,B). The subsumption(or subconcept–superconcept) relation between con-cepts is defined as follows:(A1, B1) ⊑ (A2, B2) ⇔

A1 ⊆ A2 (12). Relying on this subsumption relation⊑, the set of all concepts extracted from a contextK = (G,M, I) is organized within a complete lat-tice, called theconcept latticeof K and denoted byB(G,M, I).

Using the information contained in Table 1, twocontextsK1 andK2 dealing with two thematic havebeen built: the first one is about specific tools of se-mantic wiki and the second one is about the use oftechnologies of semantic Web.

In the contextK1 = (G,M1, I1), G is the set ofthe wiki engines,M1 is the set of attributes represent-ing the specific tools of the semantic wiki, and the bi-nary relationI1(g,m1) means that the objectg has thefunctionalitym1. Table 5 describes the lattice13 result-ing from the contextK1. The navigation in this lat-tice allows to select the semantic wiki that matches tothe functionality needs of the users. For example, ifan inference engine, forms and advanced queries areneeded, we can easily identify a concept that has theseattributes and see that it contains four objects: KiWI,KnowWE, Semantic Mediawiki and Wikidsmart.

We can also extract some knowledge from these lat-tices by finding association rules.

Following the original definition by Agrawal etal. [1] the problem of association rule mining is de-fined as: LetG be a set of objects andM the set ofattributes. An association rule is defined as an impli-cation of the formX −→ Y whereX,Y ⊆ M andX ∩ Y = ∅. X −→ Y means that the objects have theattributesX then these objects have the attributesY inthe dataset.

Because the number of possible association rulesthat may be generated from a dataset is huge, it is im-portant to restrict the interest to those that occur of-ten and that predict with a high confidence. These twoproperties that describe the interestingness of a rule arecalled support (s) and confidence (c). The support ofa rule is defined as the proportion of objects that havethe considered attributes. The confidence of a rule isthe number of time that the left hand side and the righthand side of the rule appear together divided by thenumber of times that the left hand side of the rule ap-pears in the dataset.

12or B2 ⊆ B1, which is equivalent: it can be shown that if(A1, B1) and (A2, B2) are two concepts thenA1 ⊆ A2 if andonly if B2 ⊆ B1.

13Lattices were built with ConExp [33]


Wik

isfo

ron

tolo

gies

Ont

olog

ies

for

wik

is

Adv

ance

dqu

ery

Ann

otat

ions

inth

ete

xt

Ann

otat

ions

sepa

rate

d

For

ms

Infe

renc

een

gine

AceWiki × × × ×

BoWiki × × ×

KiWI × × × × ×

Knoodl × × ×

KnowWE × × × × ×

OntoWiki × × × ×

SMW × × × × ×

Subleme × × ×

SWim × × ×

TaOPis × × × ×

Wikidsmart × × × × ×

Table 2

The context of semantic wiki engines and their functionalities.

4.2.2. Observations about semantic wikifunctionalities

The first FCA classification focuses on engine func-tionalities that are specific to semantic wikis. In thecontextK1, the approach (either wikis for ontologiesor ontologies for wikis), the ability to do advancedqueries, the annotation type (either in the text or sep-arated), and the presence of forms and an inferenceengine are used as attributes. The resulting lattice isshown in Figure 5.

Some interesting association rules can be extracted.For example, the rules "Annotations in the text−→Wikis for ontologies" and "Annotations separated−→Ontologies for wikis", which both have a confidenceof 75%, allow to distinguish how the difference be-tween wikis for ontologies approach and ontologies forwikis approach is highlighted in the creation of anno-tations. Indeed, the ontologies for wikis approach ismore focused on the underlying ontology building andwants to surely identify added knowledge, while thewikis for ontologies approach is more closed to thetext meaning, as in traditional wikis. The distinction isalso shown by the rule "Ontologies for wikis−→ ad-vanced queries" (confidence: 100%). The presence ofadvanced queries means that the engine is conceivedfor the exploitation of ontology, that inducts in mostof the cases the use of inference engine, as shown bythe rule "inference engine−→ advanced query" (con-fidence: 88%). However, the rule "Wikis for ontolo-gies−→ inference engine" (confidence: 100%) showsthat engines which use this approach do not neglectexploitation of knowledge .

Wik

isfo

ron

tolo

gies

Ont

olog

ies

for

wik

is

OW

L

Impo

rt

Exp

ort

Rdf

stor

e

SP

AR

QL

endp

oint

Infe

renc

een

gine

AceWiki × × ×

BoWiki × × × × ×

KiWI × × × × × ×

Knoodl × × × ×

KnowWE × × × × ×

OntoWiki × × × × × ×

SMW × × × × × ×

Subleme ×

SWim × × × ×

TaOPis × × ×

Wikidsmart × × ×

Table 3

The context of semantic wiki engines and their use of semantictechnologies.

4.2.3. Observations about interoperabilityThe second classification examines the potential of

wiki engines in the use of semantic Web technologiesand standards. This use is important because it will en-sure the interoperability of the system. It is thereforeinteresting to link interoperability with the selected ap-proach. In addition, the use of standard OWL and aninference engine, the presence of SPARQL endpointand an RDF store, and the possibilities of export andimport permit to highlight the integration capabilitiessystem in the semantic Web. All these attributes arenoted in the contextK2 (Table 3) and the resulting lat-tice (Figure 6).

From this point of view, the rules "import−→OWL,Ontologies for wikis"(confidence: 100%), "Ontologiesfor wikis −→ Export"(confidence: 83%) and "OWL,Ontologies for wikis−→ Export"(confidence: 100%)show the great importance for engines that use the on-tologies for wikis to integrate standard and allow theuse of results by other systems. Navigating the latticeallows us to note that no system of wikis for ontolo-gies approach allow import ontologies. However, Thisremark has to be qualified since Semantic MediaWikiis currently experimenting with an extension to bridgethis gap [15].

The rules "OWL, SPARQL endpoint, RDF store−→ Export, Inference engine" and "RDF store−→SPARQL endpoint" are indicative of the use of frame-work dedicated to semantic Web. Indeed, frameworkssuch as Sesame or Jena allow the integration of RDFstore and SPARQL endpoint and manage the OWLstandard.


Fig. 5. Concept lattice of semantic wiki engines and their functionalities.

Fig. 6. Concept lattice of semantic wiki engines and their useof semantic technologies.


4.3. Some other arguments for choosing

In the construction of a semantic wiki, the choiceof engine is not necessarily trivial. The first questionto ask is about its use and the available resources. Ifthere is a pre-existing ontology, then an engine thatimplements the approach ontologies for wikis shouldbe used. Engines using wikis for ontologies approachis rather intended the emergence of ontologies. Inthe case of using a controlled vocabulary, AceWikiand Semantic MediaWiki coupled Halo extension pro-vide interesting possibilities. One might also note thatsome systems are dedicated to a specific area, such asBOWiki for bio-medicine and Swim for mathematics.From a functional standpoint, some systems have in-teresting technologies for the semantic Web, such asSPARQL endpoints and RDF store.

In addition, we must also take into account the de-gree of system stability. Thus, only those being ratedas stable can be put into production.

Finally, the size of the community around theproject provides a good indicator of project monitor-ing. From this point of view, Semantic MediaWiki andKiWI seem to be best placed.

5. Conclusion and discussion

This paper is a survey about semantic wiki engines.It has presented the context of semantic wikis and thenhas defined them as tools for knowledge management,which may become the backbone of the semantic Web.These systems have already been put to the test in var-ious domains, such as education, cooking, and humanresource management. From now on, they are con-fronted to several challenges: the complexity of the an-notation, the interoperability, the data migration fromexisting systems, the centralization of data, the integra-tion of communities, etc.

The systems presented above propose parts of an-swers to these issues. The adaptation of wikitext inSemantic MediaWiki and OntoWiki, the forms andthe auto-completion in IkeWiki/KiWI and the con-trolled language in AceWiki make easier the knowl-edge editing. Furthermore, the use of semantic Webstandards, such as OWL or SPARQL, tends to becomewidespread and some alternative architectures are de-veloped (e.g., SWOOKI). IkeWiki proposes the importof pages from Wikipedia, which constitutes a progressfor the issue of data migration, whereas OntoWiki pro-vides a system for community management.

However, there are some remaining limitations ofcurrent semantic wiki engines. For example, one canregret the lack of import functionnalities of OWL on-tologies or RDF(S) knowledge bases, which is harm-ful to the integration with other semantic Web systems.Another limitation is the fact that the wikitexts followdifferent syntaxes, from a system to another one. Thisis also the case for most of the query systems, stillcomplex to handle by non expert users. Finally, it canbe noticed that the wikis for ontologies approach doesno guarrantee the homogeneity of the knowledge base,since this one may contain different resources with thesame semantics. Currently, the only solution to this is-sue seems to be the manual control of resource addi-tions by a knowledge engineer.

References

[1] Rakesh Agrawal, Tomasz Imielinski, and Arun N. Swami.Mining association rules between sets of items in largedatabases. In Peter Buneman and Sushil Jajodia, editors,Pro-ceedings of the 1993 ACM SIGMOD International Conferenceon Management of Data, Washington, D.C., May 26-28, 1993,pages 207–216. ACM Press, 1993.

[2] Sören Auer, Sebastian Dietzold, and Thomas Riechert. On-towiki - a tool for social, semantic collaboration. In IsabelF.Cruz, Stefan Decker, Dean Allemang, Chris Preist, DanielSchwabe, Peter Mika, Michael Uschold, and Lora Aroyo,editors, 5th International Semantic Web Conference, ISWC2006, Athens, GA, USA, November 5-9, 2006, pages 736–749.Springer, 2006.

[3] David Aumüller and Sören Auer. Towards a semantic wiki ex-perience - desktop integration and interactivity in wiksar. In1st Workshop on The Semantic Desktop, Next Generation Per-sonal Information Management and Collaboration Infrastruc-ture, Galway, Ireland, pages 388–396, 2005.

[4] Joshua Bacher, Robert Hoehndorf, and Janet Kelso. Bowiki:Ontology-based semantic wiki with abox reasoning. In3rdSemantic Wiki Workshop, 2008.

[5] Tim Berners-Lee, James Hendler, and Ora Lassila. The seman-tic web. InScientific American Magazine, pages 29–37, 2001.

[6] Michel Buffa, Fabien L. Gandon, Guillaume Erétéo, PeterSander, and Catherine Faron. Sweetwiki: A semantic wiki.volume 6, pages 84–97, 2008.

[7] Stefano E. Campanini, Paolo Castagna, and Roberto Tazzoli.Platypus wiki: a semantic wiki wiki web. InSemantic Web Ap-plications and Perspectives, Proceedings of 1st Italian Seman-tic Web Workshop, 2004.

[8] A. Cordier, J. Lieber, P. Molli, E. Nauer, H. Skaf-Molli,andY. Toussaint. WikiTaaable: A semantic wiki as a blackboardfor a textual case-based reasoning system. InSemWiki 2009 –4th Semantic Wiki Workshop, Heraklion, Greece, May 2009.

[9] Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt,and Lars Schmidt-Thieme. Ideas and improvements for seman-tic wikis. In York Sure and John Domingue, editors,3rd Eu-ropean Semantic Web Conference, ESWC 2006, Budva, Mon-tenegro, June 11-14, 2006, pages 650–663. Springer, 2006.


[10] B. Ganter and R. Wille.Formal Concept Analysis: Mathemat-ical Foundations. Springer, 1999. Translation of:Formale Be-griffsanalyse: Mathematische Grundlagen.Springer, Heidel-berg 1996.

[11] Malte Kiesel. Kaukolu: Hub of the semantic corporate intranet.In Max Völkel and Sebastian Schaffert, editors,SemWiki2006,First Workshop on Semantic Wikis - From Wiki to Semantics,Proceedings, co-located with the ESWC2006, Budva, Mon-tenegro, June 12, 2006. CEUR-WS.org, 2006.

[12] Georgi Kobilarov, Tom Scott, Yves Raimond, Silver Oliver,Chris Sizemore, Michael Smethurst, Christian Bizer, andRobert Lee. Media meets semantic web - how the bbc usesdbpedia and linked data to make connections. 5554:723–737,2009.

[13] Anton Köstlbacher, Jonas Maurus, Rainer Hammwöhner,Alexander Haas, Ekkehard Haen, and Christoph Hiemke.Semwiki-2010, 5th workshop on semantic wikis - linking dataand people, proceedings of the 5th workshop on semantic wikishersonissos, heraklion, crete, greece, may 31st, 2010. CEUR-WS.org, 2010.

[14] Tobias Kuhn. How controlled english can improve semanticwikis. In Proceedings of the Fourth Workshop on SemanticWikis, European Semantic Web Conference 2009, CEUR Work-shop Proceedings, 2009, 2009.

[15] Samuel Lampa. General rdf export/import functionalityfor semantic mediawiki. last consultation: October, 2010.http://www.mediawiki.org/wiki/User:SHL/GSoC2010.

[16] Christoph Lange. Mathematical semantic markup in a wiki:The roles of symbols and notations. In3rd Semantic WikiWorkshop, 2008.

[17] Germana Nòbrega, Fernanda Lima, and Dayane Freire. Inte-grating the semantic wiki approach to face to face courses. InWorld Conference on Computers in Education 2009, Bento-Gonçalves, Brazil, 27-31 juillet 2009, 2009.

[18] Eyal Oren. Semperwiki: a semantic personal wiki. InProc.of 1st Workshop on The Semantic Desktop - Next GenerationPersonal Information Management and Collaboration Infras-tructure, Galway, Ireland.

[19] Alexandre Passant and Philippe Laublet. Wikis sémantiques :le peuplement d’ontologies pour tous ? InAtelier (IC 2.0) des19e Journées Francophones d’Ingénierie des connaissances2008, Nancy, France, 18-20 Juin 2008, 2008.

[20] Sebastian Schaffert. Ikewiki: A semantic wiki for collaborativeknowledge management. In15th IEEE International Work-

shops on Enabling Technologies: Infrastructures for Collabo-rative Enterprises (WETICE 2006), 26-28 June 2006, Manch-ester, United Kingdom, pages 388–396. IEEE Computer Soci-ety, 2006.

[21] Sebastian Schaffert, Julia Eder, Matthias Samwald, andAn-dreas Blumauer. Kiwi - knowledge in a wiki. InEuropeanSemantic Web Conference 2008, 2008.

[22] Markus Schatten, MirkoCubrilo, and JuricaSeva. A seman-tic wiki system based on f-logic. In19th Central EuropeanConference on Information and Intelligent Systems, Varazdin,Croatia, 2009.

[23] SemanticWeb.org. Semantic web. last consultation: October,2010.http://semanticweb.org/.

[24] Hala Skaf-Molli, Charbel Rahhal, and Pascal Molli. Peer-to-peer semantic wikis. In Sourav S. Bhowmick, Josef Küng, andRoland Wagner, editors,DEXA, volume 5690 ofLecture Notesin Computer Science, pages 196–213. Springer, 2009.

[25] Adam Souzis. Semwiki2006, first workshop on semantic wikis- from wiki to semantics, proceedings, co-located with theeswc2006, budva, montenegro, june 12, 2006. pages 222–229.CEUR-WS.org, 2006.

[26] Max Völkel, Markus Krötzsch, Denny Vrandecic, HeikoHaller, and Rudi Studer. Semantic wikipedia. In15th interna-tional conference on World Wide Web, WWW 2006, Edinburgh,Scotland, May 23-26, 2006, 2006.

[27] W3C. OWL Web Ontology Language Ref-erence. last consultation: October, 2010.http://www.w3.org/TR/owl-ref/.

[28] W3C. RDF Vocabulary Description Language 1.0:RDF Schema. last consultation: October, 2010.http://www.w3.org/TR/rdf-schema/.

[29] W3C. Resource Description Framework (RDF). last consulta-tion: October, 2010.http://www.w3.org/RDF/.

[30] W3C. SPARQL Query Language forRDF. last consultation: October, 2010.http://www.w3.org/TR/rdf-sparql-query/.

[31] W3C. SWRL: A Semantic Web Rule Language Combin-ing OWL and RuleML. last consultation: October, 2010.http://www.w3.org/Submission/SWRL/.

[32] Wikipedia. Wiki. last consultation: October, 2010.http://en.wikipedia.org/wiki/Wiki.

[33] Serhiy Yevtushenko. Conexp. last consultation: October, 2010.http://conexp.sourceforge.net/.

ios press semantic wiki engines: a state of the art

Documents