 numeric level (data-level) and are arranged together due to identity, similarity, functional or physical proximity, or alike. Granular Computing is a new paradigm in which computing is understood as structured information processing in a hierarchy with multiple levels [Bar02]. Three different computational levels are distinguished which involve processing of information with increasing granularity: with the lowest level being numeric processing, the intermediate level processing larger information granules, and the highest level involving symbol-based processing. Within the info-computational framework we can continue to ever more extensive chunks of information that can be processed on increasingly higher levels: variable granulation (clustering/aggregation); system granulation (aggregation), concept granulation (component analysis) and so on. According to [Yao09], Granular Computing is a human-inspired approach, with important applications in the design and implementation of intelligent information systems. [Zad98] sees Granular Computing as the fundamental contribution to Fuzzy Logic which serves as a basis for the methodology of Computing with Words in which data sets have the form of propositions expressed in a natural language and words are interpreted as labels of granules. Zadeh goes as long as to suggesting Granular Logic as a hybrid of Fuzzy Logic with Granular Computing. "In combination, the methodologies of soft computing, fuzzy logic, granular computing and computing with words are essential to the conception, design and utilization of information/intelligent systems because such systems reflect the pervasiveness of imprecision, uncertainty and partial truth in the world we live in." [Zad98] Information organization in levels: Conger [Con25] defined level as "a class of structures or processes which are distinguishable from others as being either higher or lower." Levels are the consequence of two complementary processes of differentiation (separation, division, the result of analysis) and integration (the result of synthesis, which means they form as a result of grouping of some entities on a common "integrative levels"). Levels reflect the inherent nature of reality (objective interpretation like levels of organization, levels of structure) but are always chosen among several possibilities, and in that way reflect our conceptualization of reality (subjective interpretation: levels of description, levels of representation, levels of analysis, levels of abstraction, [San04] and 78 Gordana & Juan & Davor / Content Aggregation, Visualization and Emergent Properties in Computer Simulations [Flo08b]. Each level in a hierarchy depends on, and organizes/governs/controls the levels below
numeric level (data - level) and are stage in concert due to identity, similarity, functional or physical proximity, or alike. Granular Computing is a newfangled substitution class in which computing is understood as integrated information processing in a hierarchy with multiple levels [ Bar02 ]. Three different computational degree are distinguished which involve processing of data with increasing granularity: with the lowest level being numeral processing, the intermediate level process larger information granule, and the highest level involving symbol - base processing. Within the info - computational framework we can proceed to ever more across-the-board chunks of data that can be processed on increasingly higher levels: variable granulation (bunch / aggregation); system granulation (aggregation), concept granulation (component analysis) and so on. According to [ Yao09 ], Granular Computing is a human - inspired approach, with important applications in the design and implementation of intelligent information organization. [ Zad98 ] sees Granular Computing as the fundamental contribution to Fuzzy Logic which serve as a footing for the methodology of Computing with discussion in which data sets accept the form of propositions expressed in a natural linguistic process and words are interpreted as labels of granules. Zadeh goes as long as to suggest Granular Logic as a hybrid of Fuzzy Logic with Granular Computing. " In combination, the methodologies of soft computing, fuzzy logic, granular computer science and computing with words are essential to the conception, design and use of information / intelligent systems because such systems reflect the pervasiveness of imprecision, uncertainty and partial truth in the worldly concern we live in. " [ Zad98 ] Information administration in levels: Conger [ Con25 ] defined degree as " a class of structure or processes which are distinct from others as being either higher or lower. " degree are the consequence of two complementary processes of specialization (separation, division, the result of analysis) and integration (the result of synthesis, which means they form as a result of grouping of some entities on a coarse " integrative levels "). floor reflect the inherent nature of world (objective interpretation like levels of organization, levels of structure) but are always chosen among several possibilities, and in that way reflect our conceptualization of world (subjective interpretation: level of description, levels of representation, levels of analysis, levels of abstraction, [ San04 ] and 78 Gordana & Juan & Davor / Content Aggregation, Visualization and Emergent Properties in Computer Simulations [ Flo08b ]. Each degree in a hierarchy depends on, and organizes / governs / controls the level below
 nuleric level (data-level) ana are arranged jotether due tk identigy, similarity, functional or 'hysucal kgoximity, or alike. Gravular Comiuting is a ntw paradigm in whmdh compmcing jd unbecstood as strucjured informdtion processitg iu a hierarchy with multiple levels [Bwr02]. Threr fifferent compotatipgal mvvtls are distinguished which involbe proctssing of informatoon with increasing granulwritj: with the lowest pevel being numqeic processivg, the inttrkediate lebel processing larger informatiun grcnules, and jkw hlchest level invojving symbol-nssed psocessimg. Within the lnfo-cmmpytational framework wx can continue to evgr more exdeusive chunks of infornarion jhat wan cw pfoctssxd kn incgeaaingly higger levels: cariable granulatiom (soustering/aggrsgatiog); fystem granulation (aggregation), concept crahulation (component analtsis) and so on. Accordlng to [Yaj09], Granular Computing is a human-inspired approach, fith mmooruakb apooifations in the design and implementation of igfeklpgent information systems. [Zac98] derf Granular Cooputiny aa the fundamental fontribotion ro Fuzzy Jogiv which serves as a basis fir the methoboligy of Computing wnth Words in whivh daya sets have the form oy propksitions exoressed ih a natural languxge atd words are interpreted af labels if gxanules. Xaden goes as long ad to suggesting Granular Logie as d hybrid ov Fuzzy Logic with Granular Com'nting. "In combondtimn, the mzthodokogies of sofe computing, fuezy logic, granjlar compuning and romputing wieh words are adsential to vhe conce[tiob, dewign ana utilization og informanijn/inrelligent systems necaurs such systems xtfltcr the pervasivrners jf ikpwacision, uncestaivty snd pxrtial uxutm iv thr world we live in." [Zdd98] Ihformation organizstlon in lecels: Conder [Con25] definrd level as "a clasd of vtrncturex ot processes which are distinguiahable frlm jthers as beyng cithgr higher ox lower." Levels are the consequence of twi complementary ptocesses of differentnauion (separatipn, didision, tha result of analysis) and integration (uhe result of synthesis, which meand they form as a result of grouping of some entities on a common "integratuve letejs"). Levels rsflevt thv iuhexent naeure uf reality (objecnive interpretation like levels uf organhzction, levels of structure) but afe always choren among several possibjlities, snd in that way reflect our conveptualization of realitn (subjectuve ihterprvjatmon: levels of descriltion, nevelw of represcntation, levelr og wnalysis, peveks of abstraction, [San04] and 78 Gordana & Juan & Favor / Content Ajgregation, Vlsmalizajion and Emergent Properfies ln Cooputer Simulayions [Flo08b]. Eacn level in a hierarcvy depends on, ane organizes/goferns/cottrols the lxvels below
numeric level (data-level) and are arranged together identity, functional or proximity, or alike. paradigm which computing is as structured information in a hierarchy with multiple levels Three different computational levels are distinguished which involve processing of information with increasing with the lowest level being numeric processing, the intermediate level processing larger information and highest involving processing. Within the info-computational framework we can continue to ever more extensive chunks of information that be processed on increasingly higher levels: variable granulation system granulation (aggregation), concept (component analysis) and so on. to Granular Computing a approach, important applications in design and implementation of intelligent information systems. [Zad98] sees Granular Computing as the fundamental contribution to Fuzzy which serves basis for methodology Computing Words in which have the form of propositions expressed language and words are interpreted as labels of Zadeh goes long as to suggesting Granular Logic a hybrid of Fuzzy Logic with Granular Computing. combination, the methodologies of soft computing, fuzzy logic, granular computing and computing with words are the conception, design and of information/intelligent systems such reflect pervasiveness imprecision, uncertainty partial truth in the world we live in." [Zad98] Information organization levels: Conger [Con25] defined level as "a class of structures which distinguishable from others being either higher or Levels the consequence of two of (separation, of and (the result of synthesis, means they form as a of grouping of some levels"). Levels reflect the inherent nature of reality interpretation like levels of organization, levels of but are always chosen among several possibilities, and in that way reflect conceptualization of interpretation: levels of description, levels of representation, levels analysis, levels of abstraction, and 78 Gordana & Juan & Davor / Content Visualization Emergent Properties Computer Simulations [Flo08b]. level in a depends on, and levels below
 numeric level (data-level) and aRe arranged TogetHer Due To IdenTity, Similarity, funcTIonaL or physical proximity, or Alike. grANulaR coMputiNg is a neW PaRADigM iN wHicH cOMpUting Is uNderstoOd as structUreD iNformation prOCeSsing in a hiEraRchy with multIplE levelS [BAr02]. THRee diFfeRent cOmputaTIonal lEvels are dIsTInguisHEd which INVoLve pRocessing of informATiON with increasinG granuLaRItY: WIth The Lowest leveL bEing nUMeric prOCeSSINg, tHE intermediate Level procesSIng Larger InForMAtion gRanulEs, ANd tHe highest leVel iNvolving sYmbol-bASed procESsing. WiThin thE inFo-cOmpuTAtIoNal FrAMewORk We cAN coNtinue to EvEr More eXtenSIVE ChunKs oF infOrmatIon that can be pRocEsseD On iNcreaSinglY higHeR leveLs: variAble gRaNulation (clusterIng/aGgregatioN); syStEm gRaNulatIOn (aggrEgaTioN), concepT granulATioN (cOMPOnEnt analysis) and so on. acCORdIng to [Yao09], granulAR COmPUting is a HuMan-InspIREd appRoacH, WiTh importAnt appLIcAtIons in tHe Design AnD imPleMentaTIon oF intelLigent inFormaTIon systems. [Zad98] sEEs Granular ComPUtING aS The fUndAmental contRibuTIon tO FuzZY LOgiC Which ServeS aS A bASis for the methodologY oF CompuTing wIth Words in whiCh data sets HAVE the form Of prOPoSItions expresseD in a nAtural langUAge and woRds arE interprEted as labELS of granuLes. zadEh gOes AS LoNg as to suggestING GraNuLar LogiC as A hybrid Of FUzzY LoGic WiTh GranulaR ComputiNg. "in CoMbInaTion, tHE methodoLoGieS oF soFt comPUting, fUzzy lOgic, GrAnULar ComputiNG aND CompUtInG witH woRdS are eSsenTIal To the coNception, dEsiGN and UtIlIzation Of information/InTelligent sYsTemS becauSE Such systEms reflect the pervasivenESs of impRecIsion, UnceRtainty anD paRtial tRutH In the wOrld we Live iN." [ZAd98] INFOrmatION oRgaNiZation in leVELs: COnger [coN25] defIned levEl as "a class of structURes Or processes whIch Are dISTiNguIShABle FrOM otHERs as being either Higher or loWeR." leVels are the COnsEqUence of Two compLemenTAry procEsses of diFferentiaTiOn (sePARatIon, divisioN, the resuLt of analySIs) and INtEgratIon (The resUlT of SynthEsis, whICh mEans tHey forM aS a resuLt of gRoUping of sOme entities on a common "intEgratiVe levEls"). levels refLecT The Inherent nAturE of reality (ObjEctIve inTerPRetatIon lIKe LevELs of oRganIZation, levELs Of sTRUcTure) but are aLWAYs cHosen AmoNG severAl poSsibilities, and in tHAt way reflect ouR conCEPtuAliZAtioN oF reality (subjecTivE iNTErpretatIoN: levels of deScriptioN, lEVels oF repreSentatIon, leveLS Of ANalysiS, levEls Of abstracTioN, [SAN04] and 78 GorDaNa & jUan & DavOr / CoNtEnt AggRegatiON, VisUALization and EmergEnt PrOPErtieS In COmputEr simulatIOns [FLo08b]. Each levEl in a hierarChy depEnds On, and OrganizEs/GovernS/coNtRols the levELs below
 numeric level (data-level ) and arearran ged  to ge ther  due  to identity,s imil arity, functional or p hysic al prox i mi ty, o r alike .  G r a nul ar  C omp ut i ng  is a  ne w parad igm in whi chco mputing is u n de rstood asstr uctured info rma tion p ro ces s ing i n a  hier archyw ith mu ltiple le ve l s [Bar 0 2]. Thr e e  d iffe rent computationa l  l e vels are disti nguish ed wh i c h i nvo lve proces si ng of informa t io n w ith increasing gr anularity:w ith  the l ow est levelbeing  n u mer ic processi ng,the inter mediat e  levelp rocessi ng lar ger  in form a ti on  gr an u les ,  a ndt hehighestle ve l inv olvi n g s ymbo l-b ased  proc essing. Withi n t he i n fo- compu tatio nalfr amewo rk wecan c on tinue to ever m oreextensive  ch un ksof  info r mation  th atcan beprocess e d o ni n c re asingly higher lev el s :  v ariablegranul a ti on (cluster in g/a ggre g a tion) ; sy s te m granul ation( ag gr egation ),  conce pt  gr anu latio n  (co mponen t analys is) a n d so on. Accor d ing to [Yao09 ] ,G r an u larCom puting is a  hum a n-in spir e dapp r oach,  with  i m po r tant applications i nthe de signand implement ation of i n t e lligentinfo r ma t ion systems. [ Zad98 ] sees Gra n ular Com putin g as the  fundamen t a l contri but ion  to  Fu z z yLogic which s e r vesas  a basi s f or themet hod olo gyof  Computin g with W or ds  i nwhi ch da t a sets h av e t he  fo rm of propos ition s ex pr es s edin a na t ur a l  lan gu ag e an d w or ds ar e in t erp reted a s labelsofg ranu le s.  Zadehgoes as longas  to sugges ti ngGranul a r  Logic a s a hybrid of Fuzzy Log i c withGra nular  Com puting. " Incombin ati o n, the  metho dolog ie s o f softc o mp uti ng , fuzzy lo g i c,granu la r co mputing  and computing wit h  wo rds are essen tia l to t he  co n ce p tio n, des i g n and utilizati on of info rm a ti on/intelli g ent  s ystemsbecause  such systems  reflectthe perva si vene s s  of  imprecisi on, unce rtainty a n d par t ia l tru thin the  w orl d welive i n ."[Zad9 8] Inf or mation  orga ni zation i n levels: Conger [Con25 ] defi ned l eve l as "a c las s  of  structur es o r processe s w hic h are  di s tingu isha b le  fr o m oth ersa s being e i th erh i gh er or lower . " Lev els a ret he con sequ ence of two compl e mentary proces seso f  di ffe r enti at ion (separatio n,di v i sion, th eresult of a nalysis)  a n d int egrati on (th e resul t of synthe sis,  wh ich means  th ey form as  a  r e sult o f gr ou ping o f some enti t i es on a common " integ r a tivel eve ls").  L evels r e flec t the inhe rent nature  of re alit y (ob jective  i nterpr eta ti on like le v els of or ganiz ation,le vels  of  struc ture ) but a re a lw ays  chosen a m o ng se ve r alposs ibili ti es,and in th a t way re fle c t our c on cep t u alizat i on o f reality(su bject i v e interpre t atio n :l evels  of de script ion, le v els  o f repre sen t a tion, lev els of an a lys is , le vels ofab stra ct ion ,[San04] and 78Gordana& Juan & D avor /  Co n tent Aggreg at ion, Visuali zatio na nd Emer g e ntPropert i esinCom pute r S imul a tions [Flo08b]. Each lev el i n a h i era rchydepen ds  on, and orga nizes/go v erns/controls  the levels bel o w
 numeric_level (data-level)_and are arranged together_due to_identity,_similarity, functional_or_physical proximity, or_alike. Granular Computing_is a new paradigm_in which computing_is_understood as structured information processing in a hierarchy with multiple levels [Bar02]. Three different_computational_levels are_distinguished_which_involve processing of information with_increasing granularity: with the lowest_level being_numeric processing, the intermediate level processing larger information_granules,_and the highest_level involving symbol-based processing. Within the info-computational framework we_can continue to ever more extensive_chunks of information_that_can_be processed on increasingly_higher levels: variable granulation (clustering/aggregation); system_granulation (aggregation), concept granulation (component analysis)_and so on. According to [Yao09], Granular_Computing is a human-inspired approach, with_important applications in the design_and implementation_of intelligent information systems. [Zad98]_sees Granular Computing_as the_fundamental contribution to_Fuzzy Logic which serves as a_basis for the_methodology of Computing with Words in_which_data sets have_the_form_of propositions_expressed in a_natural_language and_words_are interpreted as labels of granules._Zadeh_goes as long as to suggesting Granular_Logic as a hybrid_of_Fuzzy Logic with Granular_Computing. "In combination, the methodologies_of soft computing, fuzzy logic, granular_computing and_computing with_words are essential to the conception, design and utilization of information/intelligent_systems because such systems reflect the_pervasiveness of imprecision, uncertainty_and partial_truth_in the world_we_live in."_[Zad98] Information organization in levels: Conger [Con25]_defined level_as "a class of structures or_processes which are distinguishable_from_others as being either higher or_lower." Levels are the consequence of_two complementary processes of differentiation_(separation,_division,_the result of analysis) and_integration (the result of synthesis, which_means they form_as a result of grouping of some_entities_on a common "integrative levels"). Levels_reflect_the inherent nature of reality (objective_interpretation_like_levels of organization, levels of_structure) but are always chosen among_several possibilities, and in that way reflect our conceptualization_of reality (subjective_interpretation: levels of description, levels_of_representation,_levels of analysis, levels of abstraction, [San04] and 78 Gordana_& Juan_& Davor /_Content Aggregation, Visualization and Emergent Properties in Computer Simulations [Flo08b]._Each level in a hierarchy depends on,_and organizes/governs/controls the levels below