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The Origin of Data Information Knowledge Wisdom (DIKW) Hierarchy

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Abstract

The Data Information Knowledge and Wisdom Hierarchy (DIKW) has been gaining popularity in many domains. While there has been a lot of articulation of the hierarchy itself, the origins of this ubiquitous and frequently used hierarchy are largely unexplored. In this short piece we trace the trails of this hierarchy. Like an urban legend, it’s everywhere yet few know where it came from.
TheOriginofDataInformation
KnowledgeWisdom(DIKW)Hierarchy
NikhilSharma
[Updated:February4,2008]
ImageoriginallypublishedintheDecember1982issueofTHEFUTURIST.Usedwithpermission
fromtheWorldFutureSociety,7910WoodmontAvenue,Suite450,Bethesda,Maryland20814.
Telephone:301/6568274;Fax:301/9510394;http://www.wfs.org
TheHierarchy
TheDataInformationKnowledgeandWisdomHierarchy(DIKW)hasbeengainingpopularityinmany
domains.InmostKnowledgeManagementliteraturethehierarchyisoftenreferredtoasthe“Knowledge
Hierarchy”orthe“KnowledgePyramid”,whilethe“InformationScience”domainreferstothesame
hierarchyas“InformationHierarchy”or“InformationPyramid”forobviousreasons.Oftenthechoice
between“Information”and“Knowledge”isbasedonwhattheparticularprofessionbelievestobe
manageable.
Whiletherehasbeenalotofarticulationofthehierarchyitself,theoriginsofthisubiquitousand
frequentlyusedhierarchyarelargelyunexplored.Inthisshortpiecewetracethetrailsofthishierarchy.
Likeanurbanlegend,it’severywhereyetfewknowwhereitcamefrom.
TheDomains
WhilethedomainsofInformationScienceandKnowledgeManagementbothrefertotheDIKWhierarchy,
theydonotcrossreference.Thustherearetwoseparatethreadsthatleadtotheoriginofthehierarchy.
InKnowledgeManagement,RussellAckoffisoftencitedastheinitiatoroftheDIKWhierarchy.His1988
PresidentialAddresstoISGSRisconsideredbymanytobetheearliestmentionofthehierarchy.Ackoff’s
presidentialaddresswasprintedina1989article“FromDatatoWisdom”[1]anditdoesnotciteany
earliersourcesofthehierarchy.
SearchingfortheoriginsofthehierarchyintheKnowledgemanagementdomain,wefindMilanZelenyto
beanearlierproponentofthehierarchy.Inhisarticleon“ManagementSupportSystems”[2],Zeleny
detailsouttheDIKWhierarchyin1987.ZelenybuildstheknowledgehierarchybyequatingData,
Information,KnowledgeandWisdomtovariousknowledgeforms:“knownothing”,“knowwhat”,
“knowhow”and“knowwhy”respectively.Yet,thetrailstopsagain,Zeleny’s1987mentionofthe
hierarchyisearlierthanAckoff’s1989address,buthealsodoesnotciteanyearliersourcesofthe
hierarchy.ItcanthusbearguedthatZelenywasthefirsttomentionthehierarchyinthefieldof
KnowledgeManagement.
ThedomainofdesignhasalsodrawnonandreferredtotheDIKWhierarchy.Almostatthesametimeas
MilanZeleny’sarticle,MichaelCooley’sbookpublishedin1987:“ArchitectureorBee?”[3],buildsthe
DIKWhierarchyduringhisdiscussionoftacitknowledgeandcommonsense.Onceagainnoearlierwork
iscitedorreferredtobyCooleyandtrailoftheoriginhasanabruptending.
ItisinInformationSciencedomainthatthetrailcanbepickedupagain.Herethehierarchyismentioned
asearlyas1982,whenHarlanCleveland[4]wroteaboutitinaFuturistarticle.Cleveland’sarticle
mentionstheInformationKnowledgeWisdomhierarchyindetailgivinganexample.Whatisdifferent
aboutthisarticlefromtheonesmentionedaboveisthatClevelandpointstothesurprisingoriginofthe
hierarchyitself.
TheOrigin
InterestinglythefirstevermentionofthehierarchyisneitherintheKnowledgeManagementfield,northe
InformationSciencedomain,butinanunexpectedplace:poetry.InhisFuturistarticle,Clevelandcites
T.S.Eliotasthepersonwhosuggestedthehierarchyinthefirstplace.Clevelandnamesit“theT.S.Eliot
hierarchy”.ThepoetT.S.Eliotwasthefirsttomentionthe“DIKWhierarchy”withoutevencallingitbythat
name.In1934Eliotwrotein“TheRock”[5]:
WhereistheLifewehavelostinliving?
Whereisthewisdomwehavelostinknowledge?
Whereistheknowledgewehavelostininformation?
ThisisthefirstvaguementionofthehierarchythatwasexpandedbyCleveland.Thoughthisisthefirst
mentionofthehierarchyinthearts,itisnottheonlyone.Beforemanagementandinformationscience
caughton,FrankZappaalludedtothehierarchyin1979[6]:
Informationisnotknowledge,
Knowledgeisnotwisdom,
Wisdomisnottruth,
Truthisnotbeauty,
Beautyisnotlove,
Loveisnotmusic,
andMusicisTHEBEST.
BeyondEliot’shierarchy
InhisFuturistarticle[4],HarlanClevelandconcedesthatinformationscientistsare“stillstrugglingwiththe
definitionsofbasicterms”ofthehierarchy.HeusesElliot’shierarchyasastartingpointtoexplainthe
basicterms.Clevelandalsoagreesthattherearemanywaysinwhichtheelementsofthehierarchymay
bedefined,yetuniversalagreementonthemneednotbeagoalinitself.WhileClevelandhimselfdoesn’t
add‘Data’toEliot’shierarchyhementionsYiFuTuan’sandDanielBell’sversionsofthehierarchyinthe
articlewhichincludes“data”[4].
RussellAckoff’sversionoftheDIKWhierarchyhasanother“layer”of“understanding”builtin.Thus
Ackoff’shierarchyisDataInformationKnowledgeUnderstanding&Wisdom.“Understanding”requires
diagnosisandprescription,whichAckoffconsiderstobebeyond“knowledge”butbelow“wisdom”.
Discussingthetemporaldimensionofhisversionofthehierarchy,Ackoffpointsoutthatwhileinformation
agesrapidly,knowledgehasalongerlifespanandunderstandinghasonlyanauraofpermanence.Itis
wisdomthatheconsiderstobe“permanent”inthetruesense.
ZelenyalsoproposesadditionstotheDIKWhierarchy.Accordingtohim“enlightenment”shouldbeonthe
topofthefamiliarDIKWframework[2].Enlightenment,accordingtoZeleny(personalcommunication,
October29,2004)“isnotonlyansweringorunderstandingwhy(wisdom),butattainingthesenseoftruth,
thesenseofrightandwrong,andhavingitsociallyaccepted,respectedandsanctioned.”
Acknowledgements
GeorgeFurnassuggestedthisessay.MilanZeleny,AdamKeenandPaulLinkprovidedimportant
feedback,pointersandreferences.
References
1. Russell.L.Ackoff,“FromDatatoWisdom,”JournalofAppliedSystemsAnalysis16(1989):
39.
2. MilanZeleny,“ManagementSupportSystems:TowardsIntegratedKnowledgeManagement,”
HumanSystemsManagement7,no1(1987):5970.
3. M.Cooley,ArchitectureorBee?(London:TheHogarthPress,1987).
4. HarlandCleveland,“InformationasResource,”TheFuturist,December1982,3439.
5. T.S.Eliot,TheRock(Faber&Faber1934).
6. FrankZappa,“PackardGoose”inalbumJoe’sGarage:ActII&III(TowerRecords,1979).
Contactinformation
NikhilSharma,UserExperienceResearcher,GoogleInc.(nsharmaATumichDOTedu)
... Wisdom [52] is the ability to think and act using knowledge, experience, understanding, common sense, and insight. It is also the ability to guess where your action will take you and consequences of your decision. ...
... Not so for effectiveness. A judgment of the value of an act is never independent of the judge, and seldom is the same for two judges [52]. ...
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Thesis
La recherche biomédicale se caractérise par des évolutions fréquentes de méthodes, de types de données et de personnel. Il en résulte une hétérogénéité importante des données de recherche : multisources, multimodales, pluridisciplinaires, multisites, etc. L’hétérogénéité freine le partage et la réutilisation de données scientifiques puisque la confiance dans celles-ci et leur compréhension sont en jeu. Pour améliorer la confiance dans les données, nous avons appliqué aux études de recherche biomédicale le paradigme de gestion du cycle de vie, basé sur une solution de « Product Lifecycle Management » (PLM) qui a son origine dans l’industrie manufacturière. Ainsi, nous proposons une démarche de gestion de données, avec un maximum de traçabilité de la provenance des données, tout au long du cycle de vie d’une étude de recherche biomédicale. Quant à l’amélioration de la compréhension des données, nous nous sommes focalisés sur la mise en place d’une interopérabilité sémantique entre les terminologies vernaculaires utilisées par les équipes de recherche d’un côté, et les standards, terminologies et ontologies (i.e. Systèmes d’Organisation de Connaissances (KOS)) publiées et reconnues par la communauté, de l’autre côté. Nous avons conduit nos recherches dans le Laboratoire de Recherche en Imagerie (LRI), spécialisé en recherche préclinique sur le petit animal, du centre de recherche PARCC. Le résultat est une ontologie multi-niveaux implémentée sur un système de BMS-LM (pour BioMedical Study – Lifecycle Management par analogie au PLM). Pour valider notre proposition, nous avons procédé à l’intégration des données et calculs scientifiques du laboratoire LRI dans le système BMS-LM. Nous avons appliqué nos méthodes à (1) des données issues de modalités différentes (TEP-TDM, Histologie, Protéomique) et (2) deux calculs scientifiques au laboratoire LRI : un premier pour la quantification de tissues histologiques et un deuxième pour l’analyse de la Réponse Impulsionnelle (RI) du coeur en imagerie TEP-TDM.
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This paper discusses the concept of data and information and highlights the problems associated with their usage in healthcare. While data refers to facts and statistics collected for reference or analysis, information includes the context provided to data to gain meaning. Healthcare professionals use the information obtained from data to improve patients' health status and satisfaction. Nevertheless, the value of information depends on the data and how it is presented. As a result, many problems can arise in the collection and processing of data and the provision of information. In this paper, these are called data and information problems. One possible approach to reduce such problems in the future could be to use creative methods. To initially address this idea, exemplary keyword research was carried out, and examples are presented in this paper.
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In the emerging post-industrial society, there is little understanding of the characteristics of information, a basic, yet abstract resource. Information is expandable, compressible, substitutable, transportable, diffusive, and shareable. Implications for life, work, community, and conflict are considered. (AM)
Article
Humans do not apply formalistic scaffolds of fixed rules of ‘knowledge’ to integrate the a priori given objective world of data ‘out there’: they do not compute the world. Regardless of some ‘knowledge’-modeling assumptions, just the opposite is true: humans use their subjectively perceived world of turbulent circumstances to bring forth (create, recreate and adapt), again and again, knowledge as an autopoietic network of relations through which they coordinate their actions. Such knowledge brings (through language) coherence and coordination to the otherwise turbulent and chaotic world of human action. Knowledge is not ‘processing of information’ but a coordination of action. As a consequence, any management support system (DSS, AI, ES, etc.) claiming knowledge as its purpose or its base, cannot be of the symbolic computation type à la Simon.
Architecture or Bee?
  • M Cooley
M. Cooley, Architecture or Bee? (London: The Hogarth Press, 1987).
The Rock (Faber & Faber
  • T S Eliot
T.S. Eliot, The Rock (Faber & Faber 1934).
User Experience Researcher
  • Nikhil Sharma
Nikhil Sharma, User Experience Researcher, Google Inc. (nsharma AT umich DOT edu)