Available online at www.sciencedirect.com

45 (2008) 641–661www.elsevier.com/locate/dss

Decision Support Systems

A multilingual knowledge management system:A case study of FAO and WAICENT

Daniel E. O'Leary

University of Southern California, Los Angeles, CA 90089-0441, United States

Available online 27 July 2007

Abstract

This paper provides a case study of a multilingual knowledge management system for a large organization. In so doing we elicitwhat it means for a system to be “multilingual” and how that changes some previous research on knowledge management. Someresearchers have viewed multilingual as meaning a multilingual user interface. However, that is only a small part of the story. Inthis case we find multilingual also refers to a broad range of “multilingual,” including multilingual knowledge resources,multilingual feedback from users, multilingual search, multilingual ontologies and other concerns.© 2007 Elsevier B.V. All rights reserved.

Keywords: Multilingual system life cycle; Knowledge management; Multilingual Ontologies; Controlled Vocabularies; Evolution; Multilingual Search

1. Introduction

In the early and middle 1990's the Internet's first webpages were virtually all in English, as were the searchengines [23]. However, that has changed as web hasusers from all over the world now access the Internet,and web sites are available in virtually every differentlanguage. In some cases specific organizations must, orsimply find it important and cost beneficial toaccommodate those multilingual users.

In order for different groups to use the Internet, andits far reaching access to use available knowledgeresources, the knowledge resources need to be availablein multiple languages. In particular, large, multinationalcorporations, and many governments and governmentalorganizations require the use of multilingual systems fortheir knowledge resources. For example, in Belgiumfour languages are in use: Dutch, French, German andEnglish (http://www.belgium.be/eportal/index.jsp). Fur-

E-mail address: oleary@usc.edu.

0167-9236/$ - see front matter © 2007 Elsevier B.V. All rights reserved.doi:10.1016/j.dss.2007.07.007

ther, important developments whether medical orgovernmental occur or are consumed in many languages[26]. As a result, knowledge resources must beaccommodated and promoted in multiple languages.

Unfortunately, there are few models or case studies inthe literature available to illustrate the use of multilin-gual knowledge management systems. Further, it is notclear what the emerging architectures are for thedevelopment of such multilingual systems. As a result,it is also not clear what are some of the key or emergingissues associated with developing, implementing ormaintaining multilingual systems.

1.1. Purpose

Accordingly, the purpose of this paper is to developa case study of a multilingual knowledge managementsystem. In so doing we are able to analyze some of theapproaches used in the development of a multilingualcapability. Further, such a case study allows us insight intowhat are some of the primary multilingual capabilities

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required or used in such systems and how thosecapabilities are implemented. In addition, such a casestudy can provide us with insights into some of theproblems and decisions associated with such systems.

An analysis of the literature reveals few such casestudies of “real world” organizations. To-date, much of theliterature is aimed at addressing specific problems (libraryresource overload), generally using a particular technol-ogy (e.g., portals) and does not provide a portfolio ofmultilingual solutions that are part of such real worldorganizations. In addition, this case study provides a benchmark, fromwhichwe can gauge the growth ofmultilingualcapabilities. Further, by analyzing what multilingualactivities are employed in a real world case study we canbetter understand what it means to provide a “multilin-gual” system. Finally, comparing multilingual knowledgemanagement capabilities to other knowledgemanagementsystems lets us note that previous investigations intoknowledge management have been “underspecified.”

1.2. This paper

This paper proceeds in the followingmanner. Section 2provides a review of some of the multilingual knowledgemanagement literature. Section 3 discusses the back-ground of the organization that is the source of thisanalysis, the FAO (Food and Agriculture Organization, anagency of the United Nations) and its technology sectionWAICENT (World Agriculture Information Centre), anddiscusses why FAO needs to have a multilingualcapability. Section 4 reviews the basic nature of FAO'smultilingual system. Section 5 provides an overview ofsome FAOmultilingual knowledge resources, including aparticular controlled vocabulary that is maintained byFAO in five different languages and some categorizationschemes used by FAO andWAICENT. Section 6 providesa brief analysis of FAO and WAICENT's architecture,reviewing the important role of XML. Section 7 discussesthe limitations of building multilingual systems. Section8 provides a model to summarize our findings andanalyzes. Finally, Section 9 briefly summarizes the paperand discusses some extensions.

2. Selected previous research in multilingual DSSand knowledge management

Multilingual systems have begun to find use in alarge number of settings, including government, medicalsystems and libraries. In addition, some of the mostimportant technical issues in multilingual systems areontologies, since they help facilitate communication,structure and search about knowledge issues. Peters and

Sheridan [23] provide a brief history of the integrationof multilingual resources into systems.

There has been limited research in multilingual DSS.For example, prior to 2006 there was a single paper inDecision Support Systems focusedonmultilingual systems[3]. That paper dealt with the issue of how to use groupdecision support systems in order to break down barriers tocommunication. Although there has been limited researchin multilingual DSS, there has been research in knowledgemanagement and multilingual systems, some of which isrelevant to case study discussed in this paper.

2.1. Knowledge management

While providing appropriate knowledge “content,”some of the key functions of a knowledge management(KM) system include “converting” and “connecting”knowledge ([19,20] and others). Content includes abroad range of resources, such as knowledge about howto solve particular problems (“things gone right”) orknowledge about how to not solve problems (“things gonewrong”). Other critical content can include ontologiesused to structure and search and to facilitate communica-tion [20]. Individual knowledge needs to be converted togroup available knowledge, and data and text need to beconverted to usable knowledge, not to be lost in the pilesand piles of data and text that are available. Although notdiscussed at the time of that research, in a multilingualsystem, knowledge resources also need to be convertedfrom one language to others, as we see in the case study inthis paper. As a result, the need for multilingualcapabilities broadens the base and requirements ofknowledge management in general.

Further, individuals need to be connected to knowledgeresources and people. Knowledge resources need to besearchable and links between appropriate knowledgeislands need to be established. In [19] and others, the needfor consideration of multiple languages was not consid-ered in the case of “connection.” Again multilingualrequirements need to be considered since the connectionneeds to be among those ofmatching languages, otherwisethe connections will not be helpful. Search needs toprovide useful connections in the language(s) appropriatefor the user. Further, connecting knowledge to otherknowledge also must consider language, since in general,knowledge in different languages cannot be consumed byindividual users. As a result, from a connection andconversion perspective, some characterizations of knowl-edge management have been historically underspecified.Section 8 presents a model based on these extensions andcategorizes FAO and some other systems based on thesystem information discussed later in this paper.

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2.2. Multilingual support in government

Multilingual systems can play an important role ingovernment activity. As we noted above, governmentsmay havemultilingual consumers of knowledge resources.

Beyond general interaction with the populace,emerging areas of government multilingual interestinclude terrorism and crime analysis. For example, Lastet al. [13] and Qin et al. [24] have investigated the use ofmultilingual approaches to discover the presence ofterrorists groups on the Internet. Terrorists use multiplelanguages, so the systems that are used to find themneed to consider and understand multiple languages.Similarly, crime does not limit itself to a single lan-guage. Thus, Yang and Li [30] discuss how to extractmultilingual information for crime analysis focusing onChinese and English documents.

2.3. Multilingual medical systems

Sevinc [26] and others have stressed the need formedical research to be available in multiple languages.Further, there have been some multilingual DSS devel-oped for support of medical problems. For example,Ohmann et al. [21] developed a decision support systemfor the diagnosis of abdominal pain. The system involvesparticipants in 18 different countries, primarily fromEasternEurope.One of the primary concerns of the systemis the data dictionary which defines an ontology ofmedical terms. In addition, the system contains those datadictionary terms in multiple languages, including Polish,Romanian, Estonian and others. In another DSS, Gobleet al. [6] create multilingual terminology server designedto provide an ontology to a broad range of medicalapplications. As another example, Zhou, Qin and Chen[31] focused on facilitating the search for Chinese medicalinformation.

2.4. Personalized library portals

Since knowledge management systems provide accessto multiple resources, one comparable source are libraries.Extending personalized portals such as “My Yahoo!,”there has been a sequence of research related to thedevelopment of personalized library portals. Starting withMorgan [17] and Cohen et al. [5] libraries have allowedusers to create personal web pages to capture and storefrequently used electronic library resources. There havebeen a number of updates to that original concept andviews of the future (e.g., [4]). In addition, there have beenmultilingual views of the MyLibrary concept. Forexample, as noted by Rozic-Hristovski et al. [[25],

p. 157], “One of the most important needs of visitorsfrom … abroad is multilingual support, which means thatthe users can select a language inwhich the portal interfaceis presented to them.”

2.5. Ontologies in multilingual knowledge managementsystems

There are many design considerations associatedwith multilingual systems (e.g., Starr [27]). One of themost important design considerations is the design,development and use of ontologies.

Ontologies have been defined as explicit specifica-tions of conceptualizations (Gruber [7]). Ontologiesprovide a shared vocabulary and a common languagethat can be used for many purposes, including indexing,search and retrieval (e.g., [20]). Ontologies facilitatereuse of knowledge resources. However, because theyare based in language, there are a number of impedi-ments to their usage, such as changing meaning overtime (e.g., [18]). Unfortunately, in that analysis ofimpediments of ontologies, the multilingual nature ofontologies was not addressed. As a result, we can seelimitations in previous knowledge management modelsbecause of a lack of consideration of multilingualfactors. Additional factors come into play, as ontologiesare likely to be generated in the particular language ofconcern (e.g., English). However, there may or may notbe a particularly good match in other languages or theremay be multiple terms, rather than a single term.

In addition, it is this later notion of multilingual forwhich ontologies are so important since they facilitateuse of multiple languages. Mayer [16] provides sometools to facilitate terminological databases for multilin-gual ontologies. Jarrar et al. [8] discuss an ontology-based complaint system where they use the complaintontology to capture the core knowledge in the domainand show how the multilingual complaint environmentcan be simplified using an ontology based approach.Vouros et al. [29] use an ontology-based approach toprovide the basis of search and navigation of informa-tion in a multilingual knowledge management system.

2.6. Complexity of “multilingual” systems

As we have seen in this literature review, “multilin-gual” seems to have many gradations. As noted byRozic-Hristovski et al. [25], at one extreme, multilingualmeans being able to select a web portal interfacelanguage. At the other end of the spectrum, not only theinterface but also the resources are available in multiplelanguages. For example, Peters and Sheridan ([23],

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p.52) refer to “…accessing, querying and retrievinginformation from collections in any language ….”

Further, the system or approach can be either activeor passive in its conversion of multilingual resources. Ina passive approach, the knowledge resources taken arethe knowledge resources used. In an active approach,knowledge resources would need to be translated to theother languages. Resources in multiple languages needto be organized, indexed and searched, typically inmultiple languages. As a result, movement to multiplelanguages increases the complexity of the knowledgemanagement system.

3. Case study background

Throughout this paper we analyze key characteristicsand emerging issues using the multilingual knowledgemanagement system of the Food and Agriculture Organi-zation (FAO) and their information group, World Agri-culture Information Centre (WAICENT) [11]. Theseorganizations were chosen for a number of reasons.First, because these are public organizations, there isinformation about these groups and it is publicly available.Since information is publicly available, it is not consideredcontrary to the organization to discuss this information.Second, these and other public organizations have manyconstituents, from different cultural and language back-grounds. Unlike multinational corporations, these organi-zations cannot dictate a particular language be used, andthus must have multilingual systems. Third, I have foundthat the organization is a good single source to discuss thiswide range of issues.

3.1. FAO

Prior to the end of World War II, in 1943, 44 differentcountries came together in a meeting in Virginia,committing to an international organization for food andagriculture (http://www.fao.org/docrep/meeting/010/j6285e/j6285e04.htm). Ultimately, a report was issuedin 1945 on behalf of the UnitedNations that resulted in thefounding of FAO. Since its founding, it was agreed thatFAO should be “concerned with that large sectorrepresented by the world's farms, forests, and fisheries,and by the needs of human beings for their products."

Now, FAO (Food and Agriculture Organization) isan agency of the United Nations, headquartered inRome, Italy. It has offices in more than 80 countries,with a staff of about 4000 people. FAO has itsown governing body and it has a core budget of roughly$ 640 million, with almost an equal amount of outsidefunding.

The purpose of FAO as captured in the first article ofthe FAO Constitution is that “The Organization shallcollect, analyze, interpret and disseminate informationrelating to nutrition, food and agriculture.” FAO alsomakes recommendations on national and internationalaction in a variety of arenas, such as scientific researchin agriculture and improvement of processing, market-ing and distribution of food and agricultural products.FAO's reach is broader than just food. For example, oneof their major concerns at the writing of this paper is theAvian Flu and its ramifications.

3.2. WAICENT

WAICENT's (World Agriculture Information Cen-tre) is FAO's strategic program on information man-agement dissemination (e.g.,http://www.un.org.pk/library/unirr_waicent.html). WAICENT provides elec-tronic access to FAO's information resources through itsportal. In particular, WAICENT makes FAO's knowl-edge on all fields of food security and agriculturaldevelopment widely available to users around the world,through the Internet as part of a large knowledge man-agement system.

WAICENT's scope includes organizing and linkinginformation in order to facilitate user access; providingvisualization systems; and providing decision-supportsystems at national levels in order to help achieve foodsecurity through use of information. In countries wherethere is limited Internet access, they provide high speedInternet connections to access their information.

3.3. “Digital inclusion” and “digital divide”

An increasingly important issue, particularly toorganizations such FAO is the notion of “digital inclusion”(e.g., Verdu et al. [28]). “Digital inclusion” relates to thefact that different countries and thus different cultures andlanguages have different access to digital technology andresources. Digital inclusion can be a driving force thatinfluences an organization's strategy and, ultimately, theextent to which they provide multilingual resources.

Perhaps, the most visible digital inclusion issue is thatof the Internet and access to knowledge resources.Unfortunately, some countries do not have the level ofaccess as others. For example, the so-called MedaCountries (Algeria, Egypt, Jordon, Palestine, Moroccoand Turkey) generally have Internet penetration levels ofless than 10% of their populations, resulting in a “digitaldivide.” Internet access, computers and even electricity canbe stumbling blocks to “digital inclusion” in the use ofknowledge management resources. In addition, the lack of

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available multilingual knowledge resources can limit thepush for use of resources from an Internet environment.

Although digital inclusion was not an issue at thetime of FAO's founding, digital inclusion is anincreasingly important issue and embedded in therationale for multilingual systems. In order to try andlimit differentials in access to digital resources,multilingual systems for infrequent users can be anissue that needs to be addressed.

3.4. Need for multilingual capabilities

FAO and WAICENT require a multilingual Internetpresence for a number of reasons, including

• A single voice to many users• FAO is a frequently visited web site• FAO is visited by a broad base of users• Their constitution basically requires it.

3.4.1. A single voice to many usersFirst, they represent over 180 different countries, thus

suggesting a broad based set of users. Internally, FAO is ahighly decentralized organization, with data from over 200different groups, generated by different developmentgroups within FAO. However, they need to showexternally a single “voice to the world,” but that voiceneeds to be expressed in the five official languages(English, French, Spanish, Chinese, and Arabic) as well asRussian and other local variations. Ideally, the samequestion has the same answer, independent of the language.

3.4.2. FAO is a frequently visited web siteSecond, FAO is a very frequently visited site. Thus,

multilingual capabilities can be leveraged to many users.FAO is a web site that receives hundreds of millions ofvisitors each year. Their site gets hundreds of millions ofhits and millions of visits each year. (A hit is a request to aserver for a file. Avisit is ameasure of the number of uniqueusers who visited a web site during a certain time period.)

Table 1User sessions

Source Percent

North America 57Europe 30Latin America 5Asia 4South Pacific 2Africa 2

Source: [9].

3.4.3. FAO is visited by a broad base of usersThird, FAO's web sites get visited by users from

all over the world. The broad based use of FAO andWAICENT is apparent with an analysis of the usersessions. North America recorded the largest numberof user sessions. However, user sessions were alsocaptured from all over the world, as seen in Table 1.Accordingly, the need for multilingual knowledgemanagement capabilities permeates WAICENT's Inter-net presence.

3.4.4. Their constitution basically requires itAs noted above, one of the key purposes of FAO is to

collect, analyze, interpret and disseminate information.Since they represent many different countries, in order toperform those activities, FAO must build a multilingualcapability.

4. FAO's multilingual Internet presence

How does FAO provide the information that theyneed to in order to meet their scope requirements? Anumber of their key efforts have multilingual aspects.

4.1. FAO home page

FAO's homepage provides a multilingual capacity ofArabic, Chinese, English, French, and Spanish. Fig. 1contains an English version. More than just multiplelanguages are required. For example, in the Arabic page,the layout of information is different than in the Englishversion. For example, when information is presented inArabic, it is presented right to left, rather than left to right.However, with the “reversed” layout, the same icons areused, so that users likely get a page experience that isgeared toward their specific language, but with manysimilarities to other languages. As a result, there is no“preference” given to any particular language.

4.2. WAICENT home page — portal

The WAICENT portal is more compact, and less“grabbing” (e.g., there are no photos, and the colors aresubdued greens and blues) than the FAO page since it ismore focused on presenting a broader base of resources.A screen print illustrating the home page is in Fig. 2.

The WAICENT portal provides links to over 250sites. In addition, it has access to search engine“WAICENT Information Finder,” to help users findthe information for which they are looking. The FAOWeb site is a large site, having approximately 500,000web pages and over 100 databases [11].

Fig. 1. FAO homepage (English).

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WAICENT has enabled the portal home page to beavailable in five languages: Arabic, Chinese, English,French and Spanish. Simply by clicking the language inthe blue tool bar enables the user to choose the languagethat they prefer to use.

4.3. Available resources

FAO provides their users with a number of differenttypes of information and knowledge resources, includ-ing web pages, press releases, pictures, documents,

Fig. 2. WAICENT portal.

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databases and controlled vocabularies. On the Internetthese items need to be searched and indexed. Multi-lingual aspects of some of these resources are discussedfurther below in Section 5.

4.4. Search (WAICENT Information Finder)

Search across the FAO and WAICENT knowledgemanagement resources is done using a number ofmechanisms. However, the most prominent approach istheWAICENT Information Finder [2]. Information Finderallows for web-based information to be located using anumber of approaches, including, free text, indexed text,

subject categories, type of resource and FAO organizationunit [10]. That information finder uses the open sourcesearch engine “Nutch.” Nutch uses a similarity metric torank hits satisfying a query, returning a similarity scorewith each hit.

Search needs to be provided across multiple languages.As a result, the search page (Fig. 3) is available in fivedifferent languages. However, the results of a search arenot limited to the findings in that language. As seen inFig. 3, a search for “Katz” finds Chinese, Arabic andEnglish citations in the first ten that it finds, from a Frenchlanguage search. Accordingly, search findings are inte-grated across multilingual documents. Further, the same

Fig. 3. Search results in WAICENT.

648 D.E. O'Leary / Decision Support Systems 45 (2008) 641–661

search for “Katz” in each of the five available languagesfound the same number of items returned each time. Thusthe same “picture” (or view) is painted for each user,independent of language. The system might be extendedby allowing the user to choose the language in which thesearch results are returned, rather than returning results inarbitrary languages.

Multilingual search capabilities could be treateddifferently. For example, documents listed as “found”could be constrained to those of the language requested.However, many users are not interested only in documentsin a certain language, but instead are interested in docu-ments across all languages. Further, unfortunately, with thatapproach, different “pictures” would be painted for userswith different languages. Potentially some documents, etc.would not be included with the different languages.

4.5. Keyword search (“Browse by Topic”)

Keyword search is also available on the FAO andWAICENT sites. On the WAICENT search engine,there is a choice to “Browse by Topic.” That choiceprovides the user with the ability to browse through anumber of keywords, paging through each letter of thealphabet. As with the other pages, multiple languagesare allowed.

An example keyword search is presented in Fig. 4.Continuing the search example, “Katz” is not among thekeywords beginning with “K.” As a result, the keywordsearches are using different information than InformationFinder searches.

Unfortunately, with keywords, it is difficult to getthe same “view” or “picture” for users across different

Fig. 4. Keyword search ("Browsing by Topic").

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languages, for a number of reasons. First, as discussedbelow, keywords are typically provided by humanindexers. Words are chosen for a document and then

Fig. 5. EMP

translated. This can result in keywords that do not “fit”the document equally well in each language. Second,words in one language do not necessarily begin with the

RES.

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same letter in another language. As a result, the pagingthrough particular letters of the alphabet in differentlanguages will not yield the same set of concepts.Accordingly, it is difficult to get the same view for eachlanguage.

4.6. User surveys

Periodically, WAICENT needs to understand howwell the users think that the knowledge managementsystem is working and to seek feedback. As a result,they have done Internet-based surveys of their users.This has been done by developing and circulatingmultilingual versions of the same survey.

Even user surveys also must be considered in multiplelanguages. For example, one example that was reviewedindicated that those completing the survey will reap one ofthree different benefits in the form of FAO gifts. Thatstatement of available gifts and the survey also was avail-able in multiple languages of Arabic, English, French andSpanish.

Fig. 6. Ontology

5. Multilingual knowledge resources

Not all resources are available in all five languages, allof the time. As two examples, “Emergency Alerts,” and“E-Learning” are available in fewer different languages.Resources and countries affected by the informationinfluence those countries for which languages materialsare developed. However, others are available in more thanfive, such as AGROVOC.

5.1. Emergency alerts (Emergency Prevention System)

In 1994, FAO established an Emergency Preven-tion System (EMPRES) for problems that cut acrossmultiple countries boundaries, to try to minimize therisk associated with those emergencies. Currentconcerns include the “Avian Influenza,” and “Footand Mouth Disease.” Currently, as seen in Fig. 5 thereare alerts issued regarding particular world events thatcan impact the food supply in English, French, Spanishand Arabic.

in English.

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However, the drill down associated with those alerts isnot provided in all of the languages apparently unless theyare necessary. For example, in a branch off of that page,“Locust Watch,” the languages of Arabic, French andEnglish are presented. Spanish was not included, sinceapparently the Locust Watch did not affect any Spanishspeaking countries in the situation update.

5.2. E-Learning

FAO is partnering with another group to generate someE-Learning capabilities (http://www.imarkgroup.org/). Forexample, as can be seen in Fig. 2 earlier, one of the E-Learningmodules became available in Spanish on January20, 2006. Currently, those resources are being generated inthree languages, English, French and Spanish. As new

Fig. 7. Ontology

resources are developed they are released, whether or notthey are available in all languages.

5.3. Controlled vocabularies at FAO: AGROVOC

As noted on the FAO web site, “AGROVOC is amultilingual, structured and controlled vocabularydesigned to cover the terminology of all subject fieldsin agriculture, forestry, fisheries, food and relateddomains.” Lauser et al. [14] discuss some of the issuesinvolved with development of an ontology that isultimately used in a multilingual environment, focusingon an ontology used for biosecurity, in particular, a“Food Safety Ontology.” The process first developed theontology in English. Then the ontology was translatedmanually into other languages.

in Chinese.

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Multilingual domain ontologies, also referred to byFAO as “Controlled Vocabularies,” facilitate knowl-edge disbursement and communication [1]. They canbe used to index documents, etc. to facilitate search.

“AGROVOC” illustrates some of the issues associ-ated with multilingual knowledge management sites. Asseen in Fig. 6 there are five different languages (Arabic,Chinese, English, French and Spanish) for which theweb page description “around” the ontology is available.However, there are fourteen different language versionsof the ontology, either on the FAO site, other sites or inprocess.

Fig. 6 presents a screen shot of the ontology in English.On that page, the description on the page “around” theontology is in English, the ontology is in English and thedescription within the ontology is in English. Similarly, thesame ontology is available in Spanish, with all threeelements also in Spanish. However, for some languages,although the description around the ontology is in thatlanguage, and the ontology is in that language, the descrip-tor within the ontology is in English. Further that thealphabetic order in each case corresponds to the appro-priate ordering for the particular language and does notfollow the order in English. Fig. 7 presents the Agrovocpage for the Chinese version of the ontology, however, theontology is not in Chinese. The Chinese version of theontology has the description around the ontology inEnglish. Note that for this version, thewebpage around theontology is in English, the descriptors are in English.

The progression in these exhibits illustrates a “lifecycle” associatedwithmultilingual systems. First, the page“around” the ontology is easier to change to differentlanguages, than the ontology or the description of theontology. Second, the translated ontology itself is morelikely to be ready sooner than the documentation sup-porting the ontology. Third, in some cases there is noequivalent concept for the ontology in the target language.In those cases, where there is no concept match, the

Table 2Number of items in different ontology versions

Version Number of items

Arabic 25,883Chinese 36,399Czech 38,663English 39,095French 38,261Japanese 38,651Portuguese 36,325Spanish 41,534Thai 25,411

English version is used. Fourth, the documentation insupport of the ontology is likely to be the last developed.As a result, we see the documentation inEnglish in some ofthe translations.

5.3.1. Number of items in AGROVOC for differentlanguages

The number of items in each version of the ontologyapparently is different as seen in Table 2. There is not aone-to-one translation between the versions of theontology. There are a number of potential reasons forthis. First, differences between the languages could resultin differences in ontologies. Aword in one language doesnot necessarily have a direct counterpart in some otherlanguage. Second, the translations were made by people.The quality of the translator can influence the extent towhich there is the appropriate set of matches betweenontology versions in different languages. Third, since thetranslations aremade by people there can easily be errors inthe translated ontologies.

A translated version of a controlled vocabulary can beanalogous to an island in terms of Darwin evolution. If thevocabulary is left to develop on its own in that language, itis likely to take on changes that are different than the sameontology in another language also left to develop on itsown. Accordingly, there needs to be a coordinated effort toensure an “equivalent” similar view is provided in eachlanguage.

5.3.2. Adding to AGROVOC's multilingual capabilitiesTwo features of AGROVOC can provide increased

multilingual capabilities (e.g., [15]). First, as seen in Fig. 8,there is the ability to suggest new terms that should beadded to AGROVOC. As part of that addition feature, theuser can recommend a term or concept in multiple differentlanguages.

Second, additional languages can be added to AGRO-VOC with communication with FAO, as seen in Fig. 9, atthe bottom. An excerpt from an AGROVOC pageprovides contact information for a potential contributorto provide vocabulary information to FAO in a number ofsubject areas, including (not in this screen shot) agricul-ture, geography and history, administration and legislation,economics, and sociology, and other areas.

5.3.3. Categorization schemes: AGRIS and CARISFAO's WAICENT also employs multilingual cate-

gorization schemes that facilitate search throughsets of documents. One such scheme is “AGRIS.”AGRIS is the international information system, createdby FAO in 1974, for the agricultural sciences andtechnology. AGRIS was designed to facilitate

Fig. 8. Suggest terms.

Fig. 9. Excerpt from AGROVOC page “Contribute with Another Language”.

653D.E. O'Leary / Decision Support Systems 45 (2008) 641–661

Fig. 10. AGRIS and CARIS partial key word list.

654 D.E. O'Leary / Decision Support Systems 45 (2008) 641–661

information exchange, in order to bring together thedisparate literature dealing with the many differentaspects of agriculture. AGRIS is a system in whichthe different participating countries are responsiblefor inputting references to the literature they produce.Then the 240 different participants can draw on all theinformation placed in the system.

Fig. 10 illustrates some of the multilingual capabilitiesdeveloped to-date for “AGRIS.” The basic home page forAGRIS can be seen in English, French or Spanish.

5.3.4. Search in AGRISAs seen in Fig. 10, AGRIS supports multilingual

search. AGRIS searches for requested keywords in docu-ments. Further descriptors in English, French and Spanish

can be used to find documents. Further, the user can thenchoose which languages in which the information is foundcan be displayed.

However, in the current system, the search does notsupport accented letters. As an example from the FAOwebpage, “When searching for terms, please enter the letterwithout the accent, e.g. to search for the Spanish word‘maíz,’ you must enter ‘maiz’.”

5.3.5. CARISA closely related database to AGRIS is the Current

Agricultural Research Information System (CARIS).Within CARIS keyword search includes a single list ofkeywords, rather than one list of keywords for eachlanguage, although either approach could be used. As an

Fig. 11. Publication work flow.

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example, Fig. 10 provides a page of keywords thatincludes keywords from multiple languages.

6. WAICENTmultilingual work flow and architecture

In order to facilitate multiple languages, WAICENTemploys a web services model using XML to exchangedata in a multilingual environment, using both SOAP andRDF [11].

6.1. Work flow

WAICENT is a large scale operation that produces andadds many digital documents daily. As part of theinfrastructure to support the production of documents forWAICENT, work flow is created. At the most basic level,documents are created, indexed by people and added to therepository. The documents are provided in multiplelanguages or are translated to multiple languages.Accordingly, the indexing and editorial activity needs toaccommodate the multiple languages. A summary of theFAO andWAICENTwork flow is given in Fig. 11 [e.g., 10and 11]. Document Type Definitions (DTD) in the form ofmeeting proceedings, books, etc., in Word format arechanged to XML (Extensible Mark-up Language) and

indexed using keywords by human indexers. That indexinformation provides meta data about the particulardocuments. The data is then managed in its XML formatand disseminated using a number of different environ-ments, including HTML.

6.2. Architecture

FAO and WAICENT have adopted an architecturebased on SOAP (Simple Object Access Protocol), RDF(Resource Description Framework) and XML, as seen inFig. 12 (e.g., [11]). RDF provides the grammar (RDFSchema) and the syntax (RDF) to define declarativerelations.

From a multilingual perspective, in the cached XMLontology, the variable “lang” is used to mark whether thedata is in “EN” (English), “ES” (Spanish) or “FR”(French).

AGRIS's search engine is based onXML-based as seenin Fig. 13 (e.g., [10]). Databases of documents and othermaterials are indexed using XML so that search enginescan performXML-based queries. This approach allows thesimultaneous search across multiple databases on theInternet in real-time, yet also presents the user with a singleset of results [15].

Fig. 12. Architecture.

656 D.E. O'Leary / Decision Support Systems 45 (2008) 641–661

Although XML provides the technology for vocabu-laries and ontologies, until recently, search and othercapabilities were limited because various countries thatprovided content did not use the same structures. As aresult, recently, AGRIS has adopted an “exchange layer”approach to the problem of having multiple documentstandards and to avoid requiring that information be put ina single format (Onyancha et al. [22]). Using thisapproach, FAO recently made the entire AGRIS repos-itory of over 3million records, available in the specificallydeveloped “AGRIS AP Exchange Format.” This ap-proach is based on using agreed on meta data to facilitatedata exchange [22]. However, the primary difficultyassociated with getting this exchange layer to work isgetting stakeholders to agree on the underlying ontologiesand vocabularies (e.g., Keizer [12]). If ontology develop-ment is difficult in a single language environment [18],those difficulties are compounded in a multilingual andmulti cultural environment.

6.3. Implementation of web services in AGROVOC

Web services have been implemented across FAOand WAICENT applications. Web services provide anefficient way to approach providing multilingualcapabilities. Particular web services can be designed tomeet specific multilingual capabilities. A summary ofsome the web services available are provided in Fig. 14(e.g., [15]).

Although page information is provided in multiplelanguages, it is interesting to note from a multilingualperspective that the web services names are in English.Accordingly, the names themselves can loose contextwhen put into other language settings, such as the one inFig. 14, depending on the user. Alternatively, webservices names could also be translated, but refer to thesame web service through the appropriate links or otherapproaches. If they need a new language, they would notnecessarily need a new site, they typically could justneed another column as part of a table look-up.

7. Multilingual knowledge management systems:FAO and WAICENT

This case study has brought out some issues relatedto multilingual knowledge management over theInternet. The purpose of this section is summarize andintegrate the findings of this paper.

First, as we have seen and can anticipate, suchmultilingual development requires substantial resourcesto both develop and ensure that the translation of adocument is appropriate. As a result, development ofmultilingual knowledge management capabilities can becostly and time consuming because of the replication ofknowledge and the complexity added to the system fromthe need to bemultilingual. Development of a multilingualcapability requires establishing workflows and integratingappropriate technologies as seen in Fig. 11. Although

Fig. 13. AGRIS XML-based search.

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outside of the scope of this paper, it potentially meansreengineering and redesigning flows to accommodate newtechnologies over time.

Second, different language versions of documents arenot all available simultaneously. As a result, translationsare published on theweb as they are developed, rather thanwaiting for all translations of a given document to becompleted, before allowing any to be published. Unfor-tunately, this can lead to the appearance (but not fact) ofapparent development priorities. Strategies need to beestablished to determine resource allocations. If a plagueappears headed for a particular area of the world, resourcesneed to be made available to facilitate that area, potentiallydriving the decision as to multilingual developmentsequence.

Third, when resources are developed in one language,but not another, it is not clear how that information shouldbe communicated to the users. One approach is to let theuser chose a “back-up” language where the resources areavailable. Then resources are listed in the primary andback-up language. Another approach is to allow formachine translation, which unfortunately, is often not a

good alternative. This issue also leads to an importantsearch issue.

Fourth, in the case of searching multilingual resources,there are a number of potential choice issues. Allowing theuser to choose an interface language is critical to lettingthem initiate a search.However, it may also be important toallow the user to target particular languages in their search,or be able to translate resources found in other languages.

Fifth, some of the greatest poverty exists in Africa.Unfortunately, Africa is home to hundreds of languages.The sheer number of languages makes catering to each ofthe individual languages virtually impossible. However,issues such as the digital divide and providing digitalresources to problem areas may drive development ofdigital resources to a relatively small number of users.

Sixth, although information can be critical to alleviatinghunger and malnutrition, ultimately, distribution ofinformation over the Internet is limited to those locationswith basic infrastructure, including electricity. Thus, it isimportant in those settings for FAO and WAICENT toprovide the facilities for users in such settings to accessFAOmaterials. This is seen in the provision of a number of

Fig. 14. AGROVOC web services.

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Internet— supported facilities around the world that theyprovide in order to try and mitigate the digital divide.

Seventh, developers of multilingual systems mustaddress the issue of connecting multilingual resources.Do they capture and present related knowledge resourcesin different languages, even though users may not be ableto understand linked and connected resources? Potentially,this could be an issue that frustrates users if they cannot“consume” the resources. However, the lack of awareness

of related resources in other languages could also havenegative consequences.

Eighth, personalized portals, used so heavily inlibrary settings can be used to facilitate the user's view,access and control of a broad range of multilingualresources. A future application at WAICENT can bedetermined the extent to which such capabilities areultimately provided to a growing and more sophisticateduser.

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Ninth, multilingual ontologies are not a one-to-oneissue. There is not always a unique term that correspondsto terms in other languages. Accordingly, as seen above,ontologies in different languages have different numbersof components. Similarly, keyword searches are notperfectly parallel in multilingual systems.

8. A model of multilingual KM systems

We present a model based on extending the approachof [19,20] to facilitate a categorization of multilingualapproaches used by different firms and to facilitate ourdiscussion of FAO and WAICENT. The model has threedimensions: “Conversion,” “Content” and “Connection.”In the case of multilingual systems, organizations can besomewhere along the spectrum of being completelypassive in the “conversion” of knowledge resources tomultilingual knowledge resources or actively convertingknowledge resources to multiple languages. Similarly,knowledge resource “content” can be in a single language(“the official language is English”) or there can be contentin multiple languages. If there are multiple languages,that content can be at the user interface or it can extendbeyond the user interface to broad-based multilingualcontent. “Connections” between people and resources orresources and other resources, for example searchor established links, can be based on a single languageor reach out to multiple languages. These threedimensional considerations are summarized below inthe diagram about multilingual knowledge managementsystems (Fig. 15).

Fig. 15. Three Dimensions of Multilingual Knowledge ManagementSystems.

As an example, consider FAO andWAICENT in termsof this model. Clearly, FAO and WAICENT is an “active”converter. Knowledge resources are churned into multiplelanguages, depending on who needs the resources anddeveloper capabilities. The multilingual content goes farbeyond just a multilingual interface to include a broadrange ofmultilingual resources as discussed above, such asontologies and alerts. Connection, at FAO andWAICENTuses both single andmultilingual approaches. In the case ofsearch, as seen above, WAICENT provides multilingualconnections. On the other hand, WAICENT InformationFinder provides language specific connections betweenknowledge content. Based on this information we wouldcategorize FAO WAICENT as being an active converter,multiple multilingual resources, and multilingualconnections.

Themodel is quite robust and other systems also can becategorized according to this model. For example, Rozic-Hristovski et al. [25] apparently is multilingual along the“multilingual content” dimension, probably at the interfacelevel. However, there is no reference to conversion orconnection. As a result it would be on the multilingualcontent axis, somewhere in the middle. Sevinc [26] andothers have stressed the need for medical research to beavailable inmultiple languages. As a result, their notions ofmultilingual would likely be along the two dimensions ofcontent and possibly conversion, with active conversionand available multilingual resources. As another example,Peters and Sheridan ([23], p.52) refer to “…accessing,querying and retrieving information from collections inany language ….” This would place their results along thetwo dimensions of multilingual resource content andmultilingual connection.

The model might also be extended to other dimensions.For example, from our discussion here, we could considermultilingual search and other additional dimensions. Forexample, can search be focused on a single particularlanguage or portfolio of languages or language indepen-dent search? As with content, this dimension becomesmore important as we move to multilingual systems.However, the advantage of the current three dimensionalapproach is its visibility and simplicity, while focusing onkey concepts.

9. Conclusion and contributions

This paper provides an analysis of a case of anorganization that employs a multilingual knowledgemanagement system. Initial analysis led to changes inthe view of knowledge management: changing the need to“convert” knowledge resources and “connect” multilin-gual resources. As a result, this paper provides an analysis

660 D.E. O'Leary / Decision Support Systems 45 (2008) 641–661

of the key capabilities of a multilingual system actuallyused bymillions of users. It is apparent thatmuch planningand substantial resources have been put into play in orderto have these systems work.

However, beyond the case study this paper providesinsights into a number of other multilingual issues, includ-ing the following:

• User surveys can be developed using multiplelanguages in order to get feedback from a broadrange of appropriate users.

• Multilingual can focus on the languages of on thosecountries affected (EMPRES), rather than just all thepotential set of languages, in the case of limitedresources.

• Multilingual ontologies or controlled vocabularies willnot match up concepts one to one in different lan-guages. Different numbers of concepts in each of tendifferent languages were found for the same controlledvocabulary (AGROVOC).

• In the analysis of the multilingual aspects of AGRO-VOC there appeared to be a “life cycle” formultilingualsystems. The multilingual life cycle appears to be firstto develop multiple language versions of the web page“around” the ontology. Second, the ontology itself ismapped into another language, while non-matchingconcepts are kept in the original language. Third, thedocumentation supporting the concepts is adopted last.

• Search by keyword can be by multiple sets ofkeywords, such as one per language (where the lan-guage could be chosen by the user) or using a single listof keywords that is itself multilingual (CARIS).

• Computer programs, such as web services, seemlikely to have a name that is based on a singlelanguage (“getTermByLanguage”), however, usinglinks and other devises it is possible to chose webservices names that are in the context of the nativelanguage.

• The overall emerging architecture is XML-based,allowing substantial flexibility in the future.

Acknowledgements

I would like to acknowledge the many commentsfrom the anonymous referees on two earlier versions ofthis paper. Further, I would like to acknowledge themany unique and insightful resources about FAO andWAICENT systems that made much of this analysispossible. The author apologizes for any errors andomissions that might have occurred, inevitable in a paperof this type. Finally, I would like to thank ChristopherYang for his work and patience with this project.

Appendix A. Selected Internet sites

Nutch Home Page: http://lucene.apache.org/nutch/AGROVOC Ontology: http://www.fao.org/aims/

ag_intro.htmUN Common Library: http://www.un.org.pk/library/

unirr_waicent.htmlFAO Statistical Databases (FAOSTAT): http://apps.

fao.org/default.htmEMPRES System: http://www.fao.org/empresGlobal Information and Early Warning System:

http://www.fao.org/giews/english/giewse.htmFood Insecurity and Vulnerability Information and

Mapping Systems (FIVIMS): http://www.fivims.orgFAO Country Profiles and Mapping Information

System: http://www.fao.org/countryprofilesInternational Information System for the Agricultural

Sciences and Technology (AGRIS): http://www.fao.org/agris/

FAO Document Repository: http://www.fao.org/documents

FAO On-Line Catalogues: http://www4.fao.orgHome-Page of FAO: http://www.fao.orgWAICENT Access Statistics: http://www.fao.org/

wwwstatsRome Declaration on World Food Security and

World Food Summit Plan of Action, http://www.fao.org/wfs/final/rd-e.htm

Home-Page of WAICENT: http://www.fao.org/waicent

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Daniel E. O'Leary is a Professor in theMarshall School of Business at the Universityof Southern California (USC). Dan has been atUSC since 1985, when he got his Ph. D. fromCaseWestern Reserve University. Recently, Danhas focused on Enterprise Resource Planning

Systems and Knowledge Management. Profes-sor O'Leary's book, Enterprise Resource Plan-ning Systems: A Life Cycle Approach waspublished by Cambridge University Press.

Dan is a former editor of IEEE Intelligent Systems, and has been on theeditorial boards of a number of journals, including Decision Sciences,European Journal of Information Systems, and Expert Systems withApplications. Professor O'Leary has published research in a number ofdifferent journals in different areas, includingDecision Science, European