資料品質原則
Principles ofData Quality
亞瑟．查普曼
Arthur D. Chapman1

雖然大多數人均不願見到自己的資料中
有錯誤而欲去除之，資料中的錯誤需要
公眾的關注和了解，因為錯誤是決定
適用性的關鍵。(Chrisman 1991)

1澳洲生物多樣性資訊服務(Australian Biodiversity Information Services)
PO Box 7491, Toowoomba South, Qld, Australia
email: papers.digit@gbif.org

（本頁留白 ）© 2005, M/l,]Dqc Global Biodiversity Information Facilityv^.4mV-O6z

B

Chapman, A. D. 2005. Principles of Data Quality, version 1.0. Report for the Global Biodiversity
Information Facility, Copenhagen.
2004 M/l,]Dqc

Tu4k";U(GBIF DIGIT programme)*E%[9QI(Arthur Chapman)jhKn/dN?+]@4p0<:,3(#>bzwtYi0fx]@HreGr)o`R(ZY0.NXs]@P'2

g8 2004 _SAR0C&21\0Fy

W$7LmJ!
Larry Speers
Senior Programme Officer
Digitization of Natural History Collections
Global Biodiversity Information Facility
Universitetsparken 15
2100 Copenhagen Ø
Denmark
E-mail: lspeers@gbif.org
andArthur Chapman
Australian Biodiversity Information Services
PO Box 7491, Toowoomba South
Queensland 4352
Australia
E-mail: papers.digit@gbif.org
July 2005

5=a © Per de Place Bjørn 2005
Amata phegea (Linnaeus 1758)

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目錄
目錄 ..................................................................................................................................................... ii
Introduction 前言 .............................................................................................................................. 1
Definitions 定義 ................................................................................................................................. 3
Principles of Data Quality 資料品質原則 ....................................................................................... 9
Taxonomic and Nomenclatural Data 分類及命名資料................................................................ 24
Spatial Data 空間資料..................................................................................................................... 29
Collector and Collection Data 採集者及採集資料 ....................................................................... 32
Descriptive Data 描述性資料 ......................................................................................................... 34
Capturing Data 資料擷取............................................................................................................... 36
Data Entry and Acquisition 資料輸入及取得............................................................................... 39
Documenting Data 資料建檔.......................................................................................................... 42
Storage of data 資料儲存 ................................................................................................................ 48
Manipulation of spatial data 空間資料運用 ................................................................................. 52
Representation and Presentation 表示及呈現 .............................................................................. 53
Conclusion 結論............................................................................................................................... 59
Acknowledgements 致謝................................................................................................................. 60
References 參考文獻 ....................................................................................................................... 61
Index 索引 ........................................................................................................................................ 64ii

（本頁留白 ）Introduction 前言
WHAT 物

分類/命名資料

WHERE 地
空間資料

WHO 人
採集資料

WHEN 時
採集資料

WHAT 事敘述性資料©q^¾m](Data quality principles)21d&¡e(SEC 2002)ÐÍ¡(Gad andTaulbee 1996)+©wA(Zhang and Goodchild 2002)³(Lunetta and Lyon 2004)
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博物館與植物標本館藏的動植物標本提供了大量的資料來源，不但保存了產
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Principles of Data Quality 資料品質原則
經驗告訴我們，將資料視為長期的資產，並在一整合的架構中管理，將能省下可觀的資金，並不斷創造價值(NLWRA 2003)。
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14

User responsibility 使用者責任^AN^R!1p"AN'l¢TdXMOerjvU_ymj)u"4^c^S

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15

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資料的類型化可能造成遺失及品質損害
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38

Data Entry and Acquisition 資料輸入及取得(取得電子資料)
資料輸入及取得本來就容易出錯。(Maletic and Marcus 2000)

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39

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47

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To be determined• Rd(Duplicate Occurrences)—M£AORdj7FA4LM&G?<6&VA93B!tm<p}WUA}WX[v~,4" ° Phaius tancarvilleae° Phaius tankervilliae° Phaius tankarvilleae° Phaius tankervilleae° Phaius tankervillae° Brassicaceae/Cruciferae>*@9(1B;#"6A• }WSP(Inconsistent Data Values)—5TMA}WU}W-uP<."K£E n@}WU<k@E}WU MA}WU• }WE(J(Information Quality Contamination)—axA}W xA}Wp
Xh$E(J"a¡:)2A}W ¡:)A}Wp

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Datums 基準'n7Å?w97¤Zs*ÀByìÀF|ìÀoQcë6næV©Zsl[(Chapman et al. 2005)|ËU­öÅnÃhòÎB+ÅyV1nó,`o.ÀPnEÉÊ8ìÀnÆ7óÑ&7¤n2?2nÆV©8¯ézê+x-k7¤ef¡!ÛG#/¤nÆV©iÅI,2n7Æ¡#nÈèv87on¼'Ð 400 !(Wieczorek 2001)
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15

http://www.biogeomancer.org/
51

Manipulation of spatial data 空間資料操作
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¨µ WGS84 jwm 10 ¼gW EUREF89 µ WGS84 ]jwm 20 

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 WGS84  S
52

System F»¨0"qX?IQBd86B(raster)+\BB@W_3([_3MU7L586
BbA\B/;c1QX?(Burrough and McDonnel 1998)HX?<TdQB

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=/GeF`

Data Integration 資料整合:5KX?S)!RR

9/J#2gaL%

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•

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G<{WF$ A{WF9y

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• 9y

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El

53

Representation and Presentation 表示及呈現
無論現有資料品質如何，都應建立一套方法，讓資料發揮最大的功用。另外，為維持其可靠性，必須驗證資料，或附加資訊以說明其可靠程度。(Olivieri
et al. 1995)
ÜÎÜßÇ3ãÀÀí·µB&k4ÖblÄ±¨Ê¦´|Ã®

Xm§ÖlÐ!Z>d®X!Û!'lÃR³mÍ¡
1ÃÍ¡T©8Ã×¾[!Ï¤Î]

Ág@È~*àÑ<Ôï]E|Ã®XmÜðuläî(Dalcin 2004)
&kÜÃÕAlêå)l3d®XW'm«\8$ljZ{ÂhÃ1;]8

ÎH`RdyHõW'm½Ø2ÃãÀ&kl}D&kl}»|Ùé#¿æç`]¼
7w4!ªÄ2¡ÃS¥âÆ×t
]

lò£­

Vó+Ñ

ef(I¢(Goodchild et al. 1991)I¢\R³xS¥²Dá'#ºcÖ¯·Øab§35lY¢qÓL

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&kÜy-G'ÑnÅ(error bar)07¥Ü·v_aÑ¬JjlÜÒfÃlÑVo

5ÑB®X»lÃõL%ØÀñÃ(Chrisman 1991),kÌÃÓìClÑÒfM"6;W'm

:/Öl%ØÀñVW'Ã





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

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Determining Users’ Needs 判定使用者需求
FaW'mlÓQV

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Relevancy 相關性54ĔlòĂĔxäò_1÷VxĔla?)¥*ďÄ;êâ_1

Çwô<d-üùn©îx®¯:ªC+XBd$.)`ãmän<xSû®òn÷8¶¤ÕË_äB1"cĔl

Believability 可信度)

L_1|õä)xÎ(Dalcin 2004))

i_1|îäă1lx

¦ºixþÞ!ç(Pipino et al. 2002)äuòÔHûĚ)¥°p_1|é(àĝmòÙxČęBhWp_1|õjxä)

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(1995)#ë}³Á^ėĒēóú£Ĕ\¼)

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č

Living with uncertainty in spatial data 與空間資料的不確定性共處ÿjld{ØäxÿjlÊuTěx]ìI
jl/áì§è_1|qíĖďÄ>1xy#bäxÿ

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¹fäëú!a?_1|oċÓ;ë8xëúE­%¼m¡,)È^)¥xĆöÍ0äxÿjlĉđ2PÑxÀämĜ4òN¼x@ĊFpwðòwð%¼
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xz·äd{ØòĘlfx

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Visualisation of error and uncertainty 誤差及不確定性的顯示55ô¸¥<8OîìcÂ`Qý*bØËÝE¼Ýý*`cn+Xp(e.g. Zhang and Goodchild 2002)

B

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2Ð

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\mcõQf*kêÝQÄcèÕËcþ÷Ûñx:Lvz

Æ8ßcSÝú`(misclassification matrix)<f*·.f*ĀÔ­3¿<
9ú§}cazÆ8)39Ú`<cïÝvÖ@(errors of omissions).cï
ÝvÝ@(errors of commission)(Chrisman 1991)9`dë)^bØ
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Risk Assessment 風險評估I»eFòçWÁ>;¸K§üÈc[ù¦0c·ð¾=

G¨ÿI»eóÑÙ¤HÎ=çW[ÛðÿóÑzøI»HSçW[:µbØ:LbØÓÞ

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¥í£H(Chapman 2002)

:LðcÃZ!DR|—N¹(c#[©æ¹(c_(Beer and Ziolkowski 1995)bØËcð¾=oá²-<:3ËUËkê?É¯7óÑI»ïÝcð°!D3{8Ës
Ø

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w28VlbJ=ÚÇÆ2n«#¯7c7'4ÒivbØð¾=cP193wOóÑuY®×)預警原則(precautionary principle)Q<~|cóÑI»

Legal and moral responsibilities 法律及道德責任bØËckêÛC¥¢UO`qÍã¬,!t• )!")
• &

)

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#

• '$• )• 
• (%(Caveats and Disclaimers)56Äd版權與智慧財產權Ç^iÄL²{â\r£ÄäÇÄ

0Fä4{âÕV<ShVÊ"隱私權dbÄÏ\v¦^ÐÆ

9äa»¥S®ÁÄ(¬Å¶xKÓHa»4tSjæ¢Im

\Tv¦¥ÌcÎÄdiÄ½<ÔÖð&l

Ä

ã7^

`FÏ

äeßzìíêQÉ,5À©N5dÄnÝ·¯r£Ä1真實標示」d¿[@ª&ldbq>OË×'

^cnd¡ÚF4<ì-f¸Äéo£(Global Spatial Data

Infrastructure, Nebert and Lance 2001, Lance 2001)|-f¸Äéo£( National
Spatial Data Infrastructure for the USA, Nebert 1999)áuBîf¸Äéo£(Australianand New Zealand Spatial Data Infrastructure, ANZLIC 1996b)±Üy«È¥¿[
4-f¸Äéo£(Lance 2001)oíf¸Äv¦(¬àX(Spatial Data
Clearinghouse)äJ免費的廣告方法，讓世人能取得遵循真實標示原則的資料4áuBîdP+)«W
『土地及地理資料品質標準可是敘述性或說明性，或兩者結合。敘述性的標
準係基於「真實標示概念」，要求資料建立者提供已知的資料品質資訊。如此，資料使用者方能在資訊充足的情況下，判定「資料適用性」。』
敏感物種資料品質呈現受限°$4;¹3ÄØÛ

U6ë/cÎ\µ_¼cÎdÙCÂÄ<]X¥½§:ÄnÝG2=ä¾ÇòT%gçÃÄwEQ?AMZÄsIÞ%
原住民權利(Indigenous rights)ÖðWÄnÝ<SÄ2D#¼êYWX2=Ó´`wÑïD#ñtSÄY
1998 8Epstein ±å³f¸ÄT%Òbq¤*díê.

}è

• 空間資訊的誤差，「極有可能」引發訴訟，造成個人及組織的名聲與誠信受損。
• 訴訟中，以往的免責聲明可能無法構成有力的辯護。
• 為減少責任義務，組織可能需要維持高品質的文件記載，「盡其所能，竭其所知」、
適當並真實地標示其產品。
警告及免責說明sÄnÝÇp~}d¨kïÏàÍ!
ÃÄnÝnÝÉ­dRº

57

äòT%gç

$+&%,# "' )$$$(! *
$+  (NLWRA 2003).

Certification and Accreditation 認證及認可Jvejo°¹¯"¬»?'Ke>MLac¬O­a®~eR¦@X>MV2j­*#K¬7F
#K¬)¶*§Ke+&L#¬ArKea<O­a<Lj>

M6}e?f名聲(reputation)qVº³EK9C%h.#²V`¾KD
I/Y9,l·BK¥n´(Dalcin 2004){V5_©Z
KTzeeR¦4kqjp#²¾%h
fjo­K=ª

mGt:

;3

Y>M,Z©uEK-y5_[Cb¹KX½>MLsa<xµw$|0eR¦k¤X(¸SR¦¹PQ«¼eR¦K>Me¡^O]

xµ*

j±r8'N1Dalcin (2004)U分類學資料

的品質認證包含三個層面：原始資料來源（原料）、資訊鏈（流程）及資料庫（產品）。」Peer Review of databases 資料庫同儕審查ed!¨¢WK¬@°HJed{£K!¨¢W4i\K¹X

ygR¦@XkTze8:°¬@58

Conclusion 結論每位資訊專家都致力於避免不必要的錯誤。直截了當地點出錯誤，可將錯誤
限制於可接受的範圍內，但錯誤不是花小錢或輕易地就能避免的。
(Chrisman 1991)。
UE+BRP=H^lRW[

L!i^h5|

UVBS#'9;)yB&¢1

/wa"UE?#

UlJGRPB¨¥uJoA>sA¤E¬tOKU>A`pN
vMz4z
• h9l#Z

I<P.rZUE)mUF&~!
6*E4<• U$Uk[%
Bk[\@bR

.D!?]5\@\CQ\

\@jR_IV-J&PN\@BJ`oT0<+• AT17!0iGB
C
• 6*WV(=S)KI\@

LT,T!2F&e0\@g0c"M\\@0?Had>

• \@;n+^'=SX0m3f8,\@_Ia/Y:OUEB.u]%f§PB7

UaClL0c

?#BUl#

BUu—>#u

;=?#Bl}©8UneBjx@LrUE?{$BU:_alJUa
QgAbUBd£K2*yYE¦

RPBk

B-T,«67XD\RPª3CW¡U/;UJ(q/;UE
人為因素可能是對空間資訊的準確度及可靠度最大的潛在威脅，同時也是確
認可靠度、瞭解任何空間資料固有缺失的一項因素。(Bannerman 1999)

59

Acknowledgements 致謝#23¼51?]Ċñð+$1n8£Ğ¼5;VÊYo´nēI;V]ÔpÚ?Í7n¡Ă;Vwå-ĂÑrd¯¢Ûg¿Ü´\Iûù+Gßėnì']¸4h@K.Ëĕïé(CRIA)$ČK¬fĕïéãé¢õ(ERIN, Environmental Resources Information Network)i¨n1ßė%ÊYĝÙnÞSZ·ĂUöÔpnè³àkčÑñ~¤ðĕïé¢n÷äþ{ğĚ¡Ă57ą@«uġ,m5ýc^á«ÈęËRĊñ(CSIRO)«ěf5&6

ĆČ«ĆâĆ°QF6n.æ(Peabody)=Ï(Æmđ«ĆF×$[*¼5ÇAÓÛÅcnEēIOĖçnmóéyăô·ßė2A£ĞnÞSö|½cnµ<)ßė Town Peterson [%«ÈęËĆn Barry Chernoff«Ą

Ćn1?«°QFĀËÀ

Beaman«&6

Ćn ReadĆF×n John Wieczorek  Robert Hijmans»Ġs_ËĜĢ`®(ETI)n Peter Shalk [%&6ĆĆán Stan Blum $Ã+z
GBIF n14öÔp¡ĂìÒÊY¼5àköĈÁÉ+¼5àkD/Bď÷òdlğn¾/J-Ôpeĉ

ßė2A4+ÿĎìÒnPØµ[ GBIF =Ïċ(ĘyéüAº^án^j-ë§_ÎmÝÆmđn Anton Güntsch@"¦úTÎmÝFrancisco PandoxtÌH:HW«êâÂ©ÎmĔM(USDA-Aphis, Pretoria, South
Africa)n Mervyn Mansell«ÈęËĆn A. Townsend PetersonqĠĆn Tuuli

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64Index 索引
accessibility -P,, 48

peer review of x<, 61

accountability [, 24

data mI

Accreditation u, 61

archiving , 50

accuracy kz9

backup of \, 50

accuracy kz9, 3

believability 59, 58

attribute ,1, 34, 46
documentation of :

capture (, 38, 41
, 45

categorization of 8, 23false v, 33

collection 7, 34

positional l1, 32, 46

collector Rg3, 34

recording of

consistency ?,, 34, 36

taxonomic data 1mI, 27

descriptive ^A,, 36

spatial 2f1, 32

documentation of

temporal Jf1, 48

entry

Mn, 23, 41archiving , 50

grid sL, 56

attribute accuracy ,kz9, 34, 46

integration , 56

audit trail {K+, 22

integrity !,, 51bias NF, 29

nomenclatural )1, 26

BioGeomancer 0VC

G@a, 33

observational `1, 38

caveats and disclaimers [w., 61

opportunistic j,, 38

Certification u, 61

presentation W, 57

classification data domain mIO, 26

relevancy =,, 58Collection data domain 7mIO, 34

representation 4, 57

collection data 7mI, 34

spatial 2f1, 31, 53

collector Rg3

storage , 50

collector Rg3, 13

survey ~<, 38

responsibility of [, 13

taxonomic 1, 26

completeness !,, 16, 29, 35, 36, 47

uncertainty z*,, 58

consistency ?,, 17, 29, 34, 36

decimal degrees e9, 53

semantic ti1, 17

DELTA standard qyk, 36

descriptive data ^A,mI, 36

structural dp1, 17
copyright /, 60

Differential DGPS FU*#Y, 39

currency J,, 16

documentation ::data cleaning mITV, 20

database design mIHZ@, 49

data custodian mIrV, 14

documentation ::

data management mIrV, 22

validation precedures b", 48

, 44domain schizophrenia DOh, 52

data quality mI7policy ;c, 11

Domain value redundancy DOB}, 51

principle E6, 1

duplicate data records mIB}>, 52

strategy cX, 11

duplication B}

vision _, 10

minimisation of ]

data user mI&3

edit controls |Q', 22, 22

eduction S$, 24

responsibility of [, 15error prevention o%v, 12

databases mIH
65

error X

positional accuracy &error X, 7error «precision G, 3precision GG, 32, 46

documentation of H, 45

documentation of H, 45

patterns ½F, 51

false «, 33

visualisation Ã~¾, 59

numerical T>, 3
statistical pO>, 3

Federal Geographic Data Committee (FGDC) Mg³
0#m\5W, 32

primary species data V6=\, 3

feedbackprinciples of data quality \E¢VD, 10°/, 24

Field data domain u\h, 31prioritisation ¯,, 16

fitness for use £8, 4, 5, 44

quality assurance E¢B¹, 6

flexibility 8, 19

quality control E¢3, 6

gazetteers #!º2

quality E¢, 4

electronic $, 43
geodetic datums #i, 53, 55

Real-time Differential GPS +1X
39

Geodetic Networks, 32

resolution ;G, 3Georeferencing Guidelines #mf¥, 42risk S¬

l7&.p,assessment S¬(, 59

geo-referencing #mf, 41
Geospatial Positioning Accuracy Standards (GPAS) #mZ G, 32
Global Positioning System, GPS l7&.p, 38

selective availability ª§8µ, 39
spatial accuracy, 32

Global Positioning Systems l7&.p, 31

Spatial Data Transfer Standards ?\y,
31

identification precision Á7

spatial data ?\, 31, 53

inconsistency

G, 29species-occurrence data =n\, 3

N, 29inconsistent data values \TN, 52

incorrect data values \T

, 52



Static GPS ­l7&.p, 39
Structure of Descriptive Data xQ8\}, 36
targets 

Indigenous rights V'À*, 60

setting of P7, 21

Information for Spatial Information in Europe L?
aO|, 31
Information Management Chain am», 13, 22

Taxonomic Database Working Group, TDWG
\Y)q, 36

information quality contamination \E¢%K, 52

Taxonomic ImpedimentIntellectual Property Rights zcoÀ, 60

taxonomy

ISO 19115 for Geographic Information – Metadata #ma> ISO 19115 Jr\, 31

temporal accuracy ]

legal responsibilities <Is, 59

timeliness ][8, 16

lineage ., 46
logical consistency Â©N8, 47

Total Data Quality Management Cycle ¨Ä\E¢mw±, 13MaPSTeDI Guidelines eV]?\Ya¤U¿, 42training b¡, 24

metadata Jr\, 44transparency t:G, 20

missing data values \T`, 51

truth in labelling ^, 8, 60

moral responsibilities s, 59

uncertainty

nomenclatural data 4!\, 26

update frequency -®k, 17

nonatomatic data values Av_\T, 52

User Interface 1@R, 41outlier detection Td{, 21voucher collections ¹¦¶E, 30

partnerships ")¼C, 15

Wide Area Augmentation System, WAAS h´.
p, 39

½¤

½¤¸, 27½¤, 26threatened species ·G, 48=, 60trade sensitive species 9j=, 60

performance measures ²[(, 2066

78, 6