1、外文翻译COMPETENCYMODELINASEMANTICCONTEXTMEANINGFULCOMPETENCIESMATERIALSOURCEVRIJEUNIVERSITEITBRUSSELAUTHORCHRISTIAENSINTHISPAPER,WEWILLPROPOSEOURIDEASFORASEMANTICALLYREADYCOMPETENCYMODELTHEMODELWILLALLOWSEMANTICENRICHMENTONDIFFERENTLEVELS,CREATINGTRULYMEANINGFULCOMPETENCIESTHEAIMOFTHISMODELISTOPROVIDEA
2、FLEXIBLEAPPROACHFORREUSE,MATCHING,INTERPRETATION,EXCHANGEANDSTORAGEFORCOMPETENCIESOURCOMPETENCYMODELISBASEDONTHEDOGMAONTOLOGYFRAMEWORKANDTHEPROPOSEDIEEESTANDARDSRCDANDSCRMWEWILLFOCUSONTHEMODELITSELFANDHOWSEMANTICSCANBEAPPLIEDTOITASTHESEELEMENTSFORMTHEBASISFORANYKINDOFPROCESSINGONTHEMKEYWORDSCOMPETEN
3、CE,COMPETENCY,RCD,SEMANTICS,DOGMA,EHRM,HRM,OCCUPATION,ONTOLOGY,SEMANTICWEBONTHEHIGHLYVOLATILEJOBMARKETTHATWEARELIVINGINATTHISMOMENT,GETTINGAGOODMATCHBETWEENACVANDAJOBOPENINGISAKEYPROBLEMTHEMAINELEMENTINTHISMATCHINGPROCESSISSHIFTINGFROMMONOLYTHICFUNCTIONTITLESTOFUNCTIONSBUILTWITHMINIMALISTIC,DESCRIPT
4、IVEANDHIGHLYREUSABLECOMPETENCYBUILDINGBLOCKSSUCHABUNCHOFSMALLINFORMATIONPIECESPUTTOGETHERALLOWSFORAFARMOREDETAILEDANDCLOSELYFITTINGMATCHBOTHAPERSONANDAFUNCTIONCANBESEENASAGROUPINGOFCOMPETENCIESANDFITTINGONEWITHTHEOTHERBECOMESAMATTEROFCOMPARINGTHESECOLLECTIONSOFBUILDINGBLOCKSWHATISSTILLMISSINGINTHISP
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9、HATTHERELATIONTYPESARELIMITEDTOPARENTCHILDORSIBLINGOURWORKISBASEDONTHECURRENTSITUATION,BUTFORMSAMODELWHICHALLOWSRICHSEMANTICSONDIFFERENTLEVELSINTHISINTRODUCTIONWEDESCRIBEDTHETHEORYWHICHSERVEDASTHEBASISFOROURCOMPETENCYMODELWEGIVEABRIEFOVERVIEWOFTHEDOGMAFRAMEWORKFORONTOLOGYENGINEERINGINSECTIONOURMODEL
10、WASINSPIREDBYTHISFRAMEWORK,ANDWEALSOMAKEUSEOFITFORFORMALIZINGSEMANTICSINSECTIONWEPRESENTOURMODELANDHOWMEANINGFITSINTHISPICTUREFINALLY,INSECTION,WESUMMARIZEOURFURTHERINTENTIONS2THEDOGMAFRAMEWORKDOGMAISARESEARCHINTITIATIVEOFVUBSTARLABWHEREVARIOUSTHEORIES,METHODS,ANDTOOLSFORONTOLOGIESARESTUDIEDANDDEVEL
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12、TATIONLESS“SETOFCONTEXTSPECIFICBINARYFACTTYPESCALLEDLEXONSALEXONREPRESENTSAPLAUSIBLEBINARYFACTTYPEANDISFORMALLYDESCRIBEDASA5TUPLE,WHEREVISANABSTRACTCONTEXTIDENTIFIER,LEXICALLYDESCRIBEDBYASTRINGINSOMENATURALLANGUAGE,ANDISUSEDTOGROUPLEXONSTHATARELOGICALLYRELATEDTOEACHOTHERINTHECONCEPTUALISATIONOFTHEDO
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14、SIBLEELEMENTARYFACTTYPESTHATARECONSIDEREDASBEINGTRUETHETERMSINTHELEXONCOMBINEDWITHTHECONTEXTRESULTINGIN2CONCEPTSBYALSOCONCEPTUALIZINGTHEROLE/COROLE,THELEXONBECOMESALANGUAGEANDCONTEXTINDEPENDENTMETALEXONANYSPECIFICAPPLICATIONDEPENDENTINTERPRETATIONISMOVEDTOASEPARATELAYER,IETHECOMMITMENTLAYERTHECOMMIT
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17、BEFOUNDINDELEENHEER,MEERSMAN,ANDDEMOOR3MEANINGFULCOMPETENCIES31COMPETENCYMODELASWEEXPLAINEDINTHEPREVIOUSSECTIONS,THEDOGMAARCHITECTUREDIVIDESTHECOMPLEXITYOVERTHREELEVELSLEXONBASE,COMMITMENTLAYERANDAPPLICATIONLAYERWEWEREINSPIREDBYTHISAPPROACHTOCONSTRUCTOURCOMPETENCYMODELTHETOTALOVERVIEWONTHEMODELCANBE
18、SEENINFIGURETHELOWESTLEVELISTHERCDORCOMPETENCYREPOSITORY,THEMIDDLELEVELISTHEREUSABLECOMPETENCELAYERANDONTOPARETHEUSERSOFTHECOMPETENCYDATA,THEAPPLICATIONSWEADOPTTHEDEFINITIONOFCOMPETENCYASGIVENBYTHEHRXMLCONSORTIUMASPECIFIC,IDENTIFIABLE,DEFINABLE,ANDMEASURABLEKNOWLEDGE,SKILL,ABILITYAND/OROTHERDEPLOYME
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22、WECANBUILDAMORESEMANTICALLYRICHSETOFCOMPETENCIESFORINSTANCE,ANRCD“CANDRIVE“CANBERELATEDWITHANRCD“CANREADROADSIGNS“USINGAN“ASSUMES“RELATIONINSTEADOFA“REQUIRES“RELATIONTOINDICATEASOFTERCONSTRAINTBETWEENTHETWORCDSTHERCDISBUILTUSINGADEDICATEDWEBINTERFACESTILLTOBECREATEDWHICHWILLENCOURAGETHEREUSABILITYOF
23、THECOMPETENCIESFORINSTANCE,IFTHEREPOSITORYALREADYCONTAINSANRCD“CANDRIVEACAR“,ANDTHEUSERCREATESANEWRCD“CANDRIVEATRUCK“,THESYSTEMWILLINFORMTHEUSEROFTHEEXISTINGRCDANDENCOURAGEHIMTOGROUPTHESERELATEDRCDSWITHARELEVANTRELATIONREUSABILITYISASTRONGPOINTTOINTEROPERABILITY,ASTHEUSEOFTHEEXACTSAMEOBJECTSCOMPETEN
24、CIESIMPLIESASHAREDUNDERSTANDINGFURTHERMORE,WEWILLALLOWTHEUSERTOSEMANTICALLYTAGORDOGTAGTHERCDWITHAPARTOFTHEDOMAINONTOLOGYTHESYSTEMWILLPROPOSECONCEPTSANDRELATIONSBETWEENTHEMFROMTHEONTOLOGYASSEMANTICTAGSANDTHEUSERCANSELECTTHEEXACTONEORMULTIPLEONESINTHISWAY,ANRCDCANBEANNOTATEDWITHSEMANTICS,RANGINGFROMON
25、ESIMPLECONCEPTTOCOMPLETESEMANTICGRAPHSWEWILLMAKEUSEOFTHEALREADYENTEREDFIELDSOFTHERCDTITLE,DESCRIPTIONANDDEFINITIONTOAPPLYSOMEHEURISTICSEARCHFORPOSSIBLYRELATEDCONCEPTSINTHEONTOLOGYTHISMETADATACANBESTOREDINTHEMETADATAFIELDOFTHERCDWEWILLMAKEUSEOFTHEMOSTCOMMONLYKNOWNFORMATSFORSUCHDESCRIPTION,LIKERDFSAND
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27、ULFORITSOWNAPPLICATIONCONTEXTATTHISPOINTTHEAPPLICATIONCOMMITSTOUSINGEXCHANGING,MATCHING,THATSPECIFICCOMPETENCEBUILTFROMTHOSESPECIFICRCDSANDTHEIRRELATIONSASSUCHITALSOLOCKSTHEINTERPRETATIONOFTHEPLAUSIBLERELATIONS,ANDTHUSTHERELATIONSARENOLONGERSIMPLYPLAUSIBLE,BUTACTUALLYFACTUALTHEAPPLICATIONCANNOWPROVI
28、DEANEXPLICITFORMALIZATIONOFTHERELATIONMEANINGEG,IFITHASTOMATCHWITHOTHERAPPLICATIONSORSIMPLYLEAVEITASATERMWITHIMPLICITMEANINGEG,IFITONLYUSESTHECOMPETENCEINTERNALLYTHEUSERCANDESCRIBETHECOMPETENCEWITHATITLEFORINSTANCE,SHECREATESTHECOMPETENCE“CANDRIVE“CONTAININGTHERCDS“CANDRIVEACAR“REQUIRES“CANUNDERSTAN
29、DTRAFFICSIGNS“THECONTAINEDRCDSANDTHEIRINTERRELATIONSFORMTHEMEANINGFORTHECOMPETENCEINANOTHERMEANINGOTHERRCDSTHECOMPETENCE”CANDRIVE”COULDHAVEANOTHERINTERPRETATIONSTOREDINTHECONTAINEDRCDSOFTHATCOMPETENCEAGAIN,WEWILLBUILDADEDICATEDWEBINTERFACEFORCONSTRUCTINGTHESECOMPETENCESITWILLENCOURAGETHEUSERINSEVERA
30、LWAYSSEETHEPREVIOUSSUBSECTIONTOREUSEEXISTINGCOMPETENCESATTHISLAYERWEDONOTINTRODUCEADDITIONALTAGGINGFUNCTIONALITYSEARCHINGFOREXISTINGCOMPETENCESCANBEDONEBYUSINGTHESEMANTICSINSIDEDOGTAGANDOUTSIDERCDRELATIONSTHATAREPARTOFTHECOMPETENCEASTHEPICTURESHOWS,ACOMPETENCEISMORETHANDATAFROMTHECOMPETENCYREPOSITOR
31、YEXTRAFIELDSAREALSOADDEDTOEACHRCDTOFURTHERSPECIFYTHECOMPETENCYEXAMPLESOFSUCHFIELDSAREPROFICIENCYLEVEL,LEVELOFIMPORTANCE,LEVELOFINTEREST,ITISIMPORTANTTONOTETHATTHEVALUESOFTHESEFIELDSARENOTYETFIXED,ASTHISWOULDHINDERREUSEAPPLICATIONLAYERTHEAPPLICATIONLAYERHOLDSALLAPPLICATIONSTHATWILLUSEOURCOMPETENCYMOD
32、ELANDITSDATAEACHAPPLICATIONUSESTHESAMEREPOSITORYCOMPETENCEANDCOMPETENCYTHEAPPLICATIONSWORKWITHAPPLICATIONPROFILES,COLLECTIONSOFCOMPETENCESFROMTHECOMPETENCEREPOSITORYTHEUSERSOFTHESEAPPLICATIONSARERESPONSIBLEFORFILLINGBOTHREPOSITORIESWITHRELEVANTDATAHOWEVER,ONETYPEOFAPPLICATIONCANBECOMPLETELYDEDICATED
33、TOADDINGDATA,WHILEANOTHERONLYUSESEXISTINGDATATHEAPPLICATIONCOLLECTSREQUIREDCOMPETENCIESANDPOPULATESTHEEXTRAFIELDVALUESITISALSORESPONSIBLEFORSETTINGTHEEXPERTISELEVELOFTHECOMPETENCETHEEXPERTISELEVELSPECIFIESATWHATLEVELTHECOMPETENCENEEDSTOBEWITHLEVELWEDONOTSIMPLYMEANANUMBEREG,ONSOMEFURTHERUNSPECIFIEDSC
34、ALEORASYMBOLEG,GOOD,BAD,MEDIUM,BUTAREALDEFINITIONOFTHEEXPERTISELEVELUSINGSEMANTICANNOTATIONDOGTAGTHEEXPERTISELEVELCANBELINKEDTOTHEDOMAINONTOLOGY,ANDTHUSBEEXPRESSEDFORMALLYWECONSTRAINTHISEXPERTISELEVELBYSTATINGTHATITCANONLYMAKETHECOMPETENCEMORESPECIFICFORINSTANCE“CANDRIVEACAR“CANHAVEANEXPERTISELEVEL“
35、CANDRIVEACARINTHEDARK“,BUTNOT“CANDRIVEATRUCK“ASTHEFIRSTLEVELISASPECIFICATIONOFTHECOMPETENCE,WHILETHESECONDISNOTIFTHEUSEDONTOLOGYDOESNOTSTATETHAT“TRUCK“ISA“CAR“译文胜任力模型在定义方面界定胜任特征资料来源布鲁塞尔自由大学作者克里斯蒂安在本文中，我们对胜任力模型语义进行研究，旨在研究胜任特征不同层次的语义，创造出规范的胜任特征。本研究的目的在与提供一个可重复使用，能够实际运用的胜任力模型。我们的胜任力模型是基于胜任力辞典和SCRM，专注于模
36、型本身，以及如何在实际工作中运用，因为这些因素构为任何一种胜任力模型奠定了基础。关键词胜任力，胜任特征，RCD，语义学，DOGMA，EHRM，HRM1绪论我们生活在就业市场大幅波动的时代，要在员工和岗位之间获得很好地匹配是一个关键性的问题。该匹配过程的主要从具有功能标题，以兴建简约的、描述性的和可重复使用的胜任力素质模型，如同信息技术里，将一个小的信息碎片整理成一束更为详细密切拟合的匹配。一个人的胜任力素质可以视为多种能力组合在一起的系列。我们缺少一个胜任力和胜任特征群的通用词汇。如何辨别一个能力如何描述它我们如何可以确定一项胜任力真实的意义如何用正确科学的方式提出胜任力模型这正是我们在界定的
37、胜任力素质模型所要回答的问题。目前来看，当前最先进的研究仅有部分回答了这些问题。HRXML联盟提供了一个胜任力的定义，然而其重点在于如何构建胜任力。他们提供了一个胜任力素质辞典，但类型不多，只有通用素质。CLAUDEOSTYN创造了一种更使用，能够被人们接受的可重复使用的胜任力辞典。该辞典规定了胜任力素质的基本要求，描述描述的一项胜任力需包含标题和描述性的语句。其关于胜任力的介绍，并没有进一步的说明应当如何正确地使用。同时，OSTYN还提出了简单可重复使用的胜任力素质模型图。这解决了胜任力与胜任力模型之间的关系。此方式可以在不同情况下使用，又可以以不同的方式组合在一起。这种方法的局限性在于只能
38、够用在特定的职位上。由于日常生活中职位是丰富多样的，需要形成一种能够满足不同需求的胜任力素质模型。以上的研究为接下来描述胜任力模型奠定了理论基础。该胜任力模型来自于上述的胜任力辞典，同时也对它进行更为规范的定义。在第二节，我们提出胜任力素质模型在模型中是如何定义的。最后一部分，我们进一步进行总结。2胜任力素质“素质模型”原本的含义是布鲁塞尔自由大学立体星象馆对各种理论、方法与本体加以研究和发展地方的工具。胜任力辞典基于古典模型理论视角，将模型分解成词语并且分层。这就是所谓的双重衔接的原则。任何特定的胜任力素质都需要进行解释。名词和名词解释之间的联系都需要科学的研究及验证。每次这样的定义由于研究
39、的局限性而导致其不够完整。胜任力辞典包括一组的特定的词汇对胜任力素质进行解释，以及它们是如何表现的。实践证明,这更加难以是胜任力素质规范化。例如，如果实际生活中，每辆汽车都拥有一个车型号，就可以很快的知道那是一辆什么样的车。因此，一个完整的胜任力素质辞典被DELEENHEER,MEERSMAN和DEMOOR提出。3胜任力意义31胜任力模型正如我们在上一节所解释，一个完整的胜任力素质由三个部分组成名称、定义和级别。我们根据这种方法来构造出胜任力素质模型。在图中，可以看到模型的整体。最底层是技能知识库，中间层是可重复使用的能力层，顶层是胜任力数据库及运用。我们采用由HRXML联盟定义的胜任力特定的
40、、可以辨认的、可定义的和可衡量的知识、技能、能力或其他相关的特性（例如，态度、行为、体能以及人力资源所能控制的具体事务中的绩效。胜任力模型由多个胜任力素质组成。一个胜任力素质是胜任力模型的一部分。值得注意的是，在文中所述的胜任力模型仅可用于构建胜任力。我们将在以下小节中做更详细的说明。名称库。最底层是技能知识库。这些知识技能可以从ONET自动获得、人工输入或两者兼而有之。可以在库中连接到任意相关的任何其他技能知识条，用来解释技能知识库中的词组。因为他们代表了一个可能或可能不是真正的事实，我们要求他们看似合理的关系。正如我们不会限制自己到特定的关系中，可以构建一套词义更丰富的胜任力。例如,一个技
41、能知识库中的词组可能会与另外两个词组之间产生联系。技能知识库是使用专门网站界面，鼓励用户使用统一的可重复使用的词组构成的胜任力素质模型。例如,如果库中已经包含了一个“可以开车”,用户可以创造出一个新的词组“能开卡车”,系统会提示已存在的帮助提示,并鼓励他们运用这些词组建立相关联系。可重复性是一种词汇的互用性,指在对完全相同的对象能力进行表述时所使用的同样一种词汇。此外,用户可以使用语义标签，该系统将提出的概念及它们之间的关系进行研究，并从库中为用户提供可以选择准确的一个或多个词组。这样,一个词组可以标注定义，用一组简单的词汇来完成素质模型图。我们将已通过的词汇都存在系统的资料库中，为用户搜索资料库提供了可能。系统将使用频率最高的词组记录下来。之后在下一个用户需要构建胜任力模型时提示胜任力素质的词组。定义库。创造胜任力词库的基础是定义库。系统可以根据用户的使用信息重新定义胜任力素质，意味着程序能够自动修改定义，这方便了词组名称与胜任力素质定义之间互相交换和更换。
