DSpace at VNU: Trust-Based Consensus for Collaborative Ontology Building

A trust-based consensus is proposed to support an efficient solution for conflicts among different viewpoints of participants in the collaborative ontology CoO building process.. In ever

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b Wroclaw University of Technology , Wroclaw , Polandc

University of Information Technology , Vietnam NationalUniversity , Ho Chi Minh , Vietnam

d Universiti Teknologi Malaysia (UTM) , Johor Bahru , MalyasiaPublished online: 12 Mar 2014

To cite this article: Trong Hai Duong , Ngoc Thanh Nguyen , Duc Cuong Nguyen , Thi Phuong Trang

Nguyen & Ali Selamat (2014) Trust-Based Consensus for Collaborative Ontology Building, Cyberneticsand Systems: An International Journal, 45:2, 146-164, DOI: 10.1080/01969722.2014.874815

To link to this article: http://dx.doi.org/10.1080/01969722.2014.874815

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1International University, Vietnam National University, Ho Chi Minh, Vietnam

2Wroclaw University of Technology, Wroclaw, Poland

3University of Information Technology, Vietnam National University, Ho Chi Minh, Vietnam

4Universiti Teknologi Malaysia (UTM), Johor Bahru, Malyasia

Ontologies are widely considered to be the backbone of the Semantic Web Its importance is being recognized in a multiplicity of research fields and application areas Ontology building is crucial for the aforementioned issues The main goal of this research is to investigate an effective methodology for collaborative ontology building A trust-based consensus is proposed to support

an efficient solution for conflicts among different viewpoints of participants in the collaborative ontology (CoO) building process In every cycle of the iterative collaborative process, the ontology is refined and evolved by reaching a trust- based consensus among the participants’ viewpoints The proposed method is applied for collaborative Vietnamese WordNet building The result is significant

in comparison with previous approaches.

KEYWORDS collaborative ontology, collective ontology, ontology, ontology engineering, ontology integration

Address correspondence to Ngoc Thanh Nguyen, Institute of Informatics (I-32), Wroclaw University of Technology, Wyb Wyspianskiego 27, 50-370, Wroclaw, Poland E-mail: Ngoc-Thanh.Nguyen@pwr.edu.pl

Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/ucbs.

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building project, which is commonly used as a Web directory in many Internetresources A Web directory contains a large reference library and is arranged fromgeneral to specific subjects Experts contribute to this directory and all of the resources

in the directory are maintained by editors who might belong to a single largecommunity This community will evaluate all of the submissions regarding the subjectmanner

Ontology has become a buzzword in the Semantic Web and semantic data

processing fields (Berners-Lee et al 2001), and its importance is being recognized in

a multiplicity of research fields and application areas, such as knowledge engineering(Gruber 1993), database design and integration, and information retrieval andextraction (Noy and McGuiness 2001; Castillo et al 2003) Ontology is the science

of what is, of the kinds and structures of objects, properties, events, processes, andrelations in every area of reality (Smith and Welty 2001) For an information system, anontology is a representation of some preexisting domain of reality that (1) reflects theproperties of the objects within its domain such that there is a systematic correlationbetween reality and the representation itself, (2) is intelligible to a domain expert, and(3) is formalized in a manner supporting automatic information processing Ontologiesplay a central role in facilitating data exchange between several sources Ontologyengineering has recently attracted considerable interest Most research has focused onontology languages (Smith and Welty 2001; Cao et al 2013), inference mechanisms,ontology editing environments, and ontology integration (Doan 2004)

Most ontologies are developed via an engineering-oriented method (Protg): asmall group of knowledge engineers carefully builds and maintains a representation oftheir view of the world Maintaining such large ontologies in an engineering-orientedmanner is a highly complex process: developers need to regularly merge and reconciletheir modifications to ensure that the ontology captures a consistent and unified view

of the reality One example of these tools is Protege (Protg), which is used by StanfordUniversity for knowledge acquisition It provides a graphical and interactive ontologydesign and knowledge base development environment Ontology developers can accessrelevant information quickly and navigate and manipulate the ontology

Currently, there are several tools oriented toward collaborative building(Tudorache et al 2008; Gabel et al 2004; Auer et al 2006; Karapiperis and Apostolou2006; Ruiz et al 2009a,b): a consensus-building mechanism that allows a large group

of people to contribute to or annotate a common ontology in a collaborative manner.Tudorache et al (2008) have developed Collaborative Protege as an extension to theclient server Protege Collaborative Protégé allows entire groups of developers who arecollaboratively building an ontology to hold discussions, chat, and make annotationsand changes as a part of the ontology development process OntoWiki in Auer et

al (2006) is a Web-based ontology that focuses on an instance editor that providesonly rudimentary capabilities such as the history of changes and ratings of ontologycomponents OntoEdit in Sure (2002) is a collaborative ontology (CoO) editingenvironment that integrates numerous aspects of ontology engineering and allowsmultiple users to develop ontologies KAON (Gabel et al 2004) focuses on changes

in ontology that can cause inconsistencies and proposes deriving evolution strategies

in order to maintain consistencies

This article aims at investigating an effective methodology for collaborativeontology building in which a trust-based consensus is proposed to support an efficientsolution for conflicts among different viewpoints of participants We learned thatconsensus techniques are the core of collaboration The Delphi technique (Gallagher

et al 1993) was applied to collaborative ontology building in order to allow anentire group to reach a consensus by sharing their understanding of ontologicalperspective Trust-based consensus for solutions to conflict profiles involves generation

of a reconciled ontology from conflicts between participants’ versions of an ontology

We applied the proposed method for Vietnamese WordNet building for demonstrationand evaluation

The remainder of this article is organized as follows The following section reviewsrelated works The trust-based consensus methodology is presented next The trust-based consensus for collaborative ontology building is discussed next, followed by

a description of the experiments performed by applying the proposed methods forVietnamese WordNet building In the last section we provide our conclusions

• The anchoring phase, which includes development of the initial version of theontology that will feed the next phase (evaluation phase) based on the compliancewith the design criteria

• The iterative improvement phase, which enhances the ontology until all participants’viewpoints reach a consensus through a collaborative building technique In thisphase, the ontology will be revised and its structure will evolve due to collaboration

of the participants At each iterative improvement, the ontology is evaluated by theaforementioned standards and conditions

• The application phase, which demonstrates the use of CoO by applying it in variousways

In agreement with Holsapple and Joshi (2002), Karapiperis and Apostolou (2006)follow the above phases in which they start by defining the criteria for ontologydesign by applying the ontology building steps described in Noy and McGuiness(2001) to design the initial ontologies Their collaborative methodology for ontologybuilding supports a team effort to iteratively revise and evolve the initial ontology untilall participants’ understanding of the ontology reaches consensus The consensus isachieved through voting in a nominal group technique (NGT; Gallagher et al 1993)

The Collaborative ONTology ENgineering Tool (ContentCVS) is a system that

is available for download as a Protege plugin (Ruiz et al 2009a) The tool supportingcollaboration provides the means for (1) keeping track of changes in ontology versions,(2) identifying conflicts between the versions of the ontology, (3) constructing areconciled ontology from conflicting versions and identifying errors, and (4) suggestingpossible ways to repair the identified errors with minimal impact on the ontology.The aforementioned methods agree that CoO involves a group of peoplecontributing to an ontology in a specific domain of interest CoO allows an entiregroup to participate in the process of ontology building by reaching a consensusand usually aims at completeness CoO building involves individuals contributing tounderstanding of their ontological perspective, but everybody works together to buildthe ontology The purpose of CoO is to generate the best representative ontologyfrom various versions of an ontology The collaborative ontology must best reflect theconflicting versions of the ontology in a compromise Therefore, the above approachesfocus on human collaboration to build a common ontology

Differing from the previous approaches, the main goal of our previous research(Duong and Jo 2010) was to investigate the techniques that support a solution toconflicts among different participants’ viewpoints in the CoO process A machine isconsidered as a leader of the collaborative group, via which conflicts among the versions

of the ontology are identified and a reconciled version that best reflects the conflictingversions in a compromise is generated automatically The main contributions of thisresearch are as follows:

• We analyzed techniques supporting CoO such as ontology integration andconsensus We learned that consensus techniques are the core of CoO (Holsapple andJoshi 2002; Karapiperis and Apostolou 2006; Ruiz et al 2009b) We distinguishedconsensus into three cases, including consensus for human collaboration, consensusfor decision making (Pill 1971; Gallagher et al 1993), and consensus for a solution

to a conflict profile (Nguyen 2008) The nominal group technique (Gallagher et al.1993) is applied for CoO to allow an entire group to reach a consensus by sharingtheir understanding of ontological perspectives Consensus for solutions to conflictprofiles involves generating a reconciled ontology from participants’ conflictingversions of the ontology In every cycle of the iterative process, participants’contributed versions tracked changes and identified conflicts automatically Unlessall versions of the ontology reach consensus, the ontology is revised and evolved by

a CoO algorithm (see Algorithms 1 and 2 in Duong and Jo 2010)

• Two criteria for CoO (identity and type of concept) for core, domain, andapplication ontology design and eight criteria for the CoO process (inclusive,egalitarian, interactive, representative, reconcilable, trust, proof, and quality) areproposed The criteria are aimed at guiding and evaluating the CoO process

• A process of CoO building was identified Different from previous approaches(Tudorache et al 2003; Karapiperis and Apostolou 2006; Ruiz et al 2009a,b), weconsider machine collaboration in the CoO building process

TRUST-BASED CONSENSUS METHODOLOGYConsensus Theory

Consensus is a collaborative process allowing an entire group to participate in decision

making in which everyone consents to the decisions of the group (Danilowicz andNguyen 1988; Hernes and Nguyen 2007) The goal of consensus decision making is

to find common ideas and explore these issues until everyone’s viewpoint has beenrecognized and understood by the group Discussions leading to consensus aim toachieve mutual agreement by addressing all concerns Consensus does not requireunanimity, but people must make a commitment to honest cooperation in order

to make final decisions Consensus is not for individualists or people who want todominate or coerce others; rather, discussion continues until consensus is achieved.Consensus is not a process for determining whose ideas are best; rather, it is for searchingtogether for the solution that is best for the group Everyone must agree to live with thedecision There are many areas of medicine in which decision making and practice varybetween clinicians Consensus is used to obtain a majority viewpoint where a range

of opinions about specific issues is likely to exist Two of the methods are the Delphiand the nominal group technique (Pill 1971; Gallagher et al 1993) These have beenused in a variety of health care settings Most studies in this field use a two-roundprocedure, with feedback between the first and second rounds, to deal with areas ofdisagreement

NGT (Gallagher et al 1993) is a well-known method for decision making Ithas been used to get the final result among a group, regardless of whether it is large

or small, while considering all opinions and votes from group members NGT takesinto account the participants who join the discussion in order to choose the result

It is successful when everybody participates and understands the manners and formssolutions or opinions on their own without influencing those around them NGT is

a process where everyone is clearly involved and is aware of all of the information andthe solution is obtained without excluding anyone from the discussion There are fivestages to NGT:

1 Introduction and explanation: It begins when every participant is in attendance inthe meeting room and a facilitator welcomes them Then, the facilitator starts theintroduction by briefly explaining what they are going to do and what procedurethey should follow in the meeting

2 Private generation of ideas: In this stage, after explanation, the facilitator willdistribute a paper for all participants and they must give a solution or idea to solvethe given question In accordance with the rules, they are not allowed to discusstheir solution with other members

3 Sharing ideas: After generation of all of the ideas, the facilitator will ask participants

to share their ideas among themselves Everyone shares their own ideas and whilesomeone is presenting their own idea, someone else should consider and contributeanother idea if they think the idea presented by the speaker is good If someone

thinks of an idea while the presenter is speaking, they can write it down In thismanner, the facilitator will record the ideas presented by every participant Becausethis stage is only for sharing ideas, there is no discussion.

4 Group discussion: This is an important stage where everyone will be involved in thediscussion about certain ideas that they do not clearly understand The participantscan also propose any ideas that might make an original idea stronger However,criticism or any rejection of ideas is avoided as much as possible, because thisdiscussion needs to be fair and balanced To avoid any negativity, the discussionfinishes after 30 to 45 minutes, even if every idea was not discussed during thattime In addiiton, in this stage, all of the participants in the group are encouraged

to give any new ideas that can be classified into categories Even when there are newideas, original ideas from participants should not be eliminated or rejected

5 Voting and ranking: This is the final stage where every idea related to the questions isprioritized The results are obtained after following the voting and ranking process,and participants learn the results at the end of the meeting The process is successfulwhen the goal of the meeting is reached

One of the popular consensus-building techniques is the Delphi method (Pill1971) This method is used for normal discussion that does not need complexcommunication between experts, such as meeting face to face or having a meetingaround a table This method can be implemented using technology such as e-mail orany other electronic technologies for communication where each question can be sentdirectly to every group expert Even when there is a complex problem that needs to besolved, this method can be used to find the solution by sending a series of questionnairesvia multiple iterations and getting a solution (data) from experts The Delphi method

is commonly used in education, to estimate forecasts, and in other fields The Delphitechnique can be done in four steps:

1 The moderator forms a group of experts that participate in the process to solve theproblem However, all of the experts are unidentified

2 A person will send a questionnaire to the participants via mail or e-mail

3 Once the person gets the return answer from a participant, the person will analyzethe results

4 In the last step, if there is no consensus reached, a combination of previousquestionnaires and results will be used as a new version of the questionnaire, andthe moderator will send this new version again to the participants Step 2 is repeateduntil consensus is reached or the moderator ends the process and makes a finalreport

There are some differences between these two aforementioned methods It is wellknown that the Delphi method is commonly used without experts needing to meeteach other In the NGT method, all participants or experts need to be in one placeand working together The main point of the NGT method is that all participantsare required to meet face to face in order to reach the solution It is thought that the

NGT method will lead to every idea or opinion being strongly endorsed if experts

or participants present their ideas in a formal manner in front of their peers Thismeans that in the NGT method, consensus can be reached if there is real discussion Incontrast to the Delphi methods, it is thought that without experts meeting each otherand based on the views of anonymous experts, the result of consensus is more accurate.Without influencing other experts, an individual expert can find the ideas and solutionbased on expert knowledge, so consensus results are more reliable when they are based

on individual expertise Consensus theory results are in some sense consistent withthose of paraconsistent logic (Nakamatsu and Abe 2014)

Trust-Based Consensus

The current consensus theory considers conflict participants at the same level Here, theparticipants in a collaborative group are distinguished by their contribution measuring

means that the system absolutely trusts the participant When a new participant joins

to the system, his or her trust value is Const specified by the system We denote U being a set of participants The trust function t is defined as follows:

this element In the specific case of this article, P is the set of senses and relations of one

sense or specific relation to other ones of this word or phrase Other participants have aright to express their agreement for each element by giving a value from 0 to 1 denoted

she can change this value later The agreement of each participant for each element isdefined as follows:

The function a(u j,e i ) returns the value of participant u j for an element e idenoted by

a (u4,e) = 09

Formula (3) to determine the strength of each element:

iis the number of participants in u e

i,t(u j) is the trust of participant

u j ∈ u e i , a (umax,e i ): is the agreement of the participant umax for the element e i, and

a

u j,e i



TABLE 1 Example values of parameters, e, a, and T

e i = 09 + 0∗ 08 + (−04) ∗ 02 + (−05) ∗ 06 + (−04) ∗ 0708 + 02 + 06 + 07 = 061 (5)

of the participants expressing their agreement for this element but also the reliability

phrase, the system will update the trust of participant proposed this element using thefollowing formula:

where t (u i ): is the trust of participant u i,E u iis the number of elements in E u i, and

e k is the strength of element e k ∈ E u i

TRUST-BASED CONSENSUS FOR COLLABORATIVE ONTOLOGY