o wledge engineeringmlanzenberger/teaching/ws... · olog 2008 : o wledge engineering ger ml 2 •...
TRANSCRIPT
Mo
nik
a L
an
zen
be
rge
r
pro
log
20
08
:In
tro
du
ctio
n t
o
Kn
ow
led
ge
En
gin
ee
rin
g
ML
2
•W
orl
d W
ide
We
b
•W
eb
2.0
•S
em
an
tic
We
b
•D
ata
, In
form
ati
on
, an
d K
no
wle
dg
e
•X
ML
an
d O
WL
•O
nto
log
ies
in P
ract
ice
•C
on
clu
sio
ns
Ou
tlin
e
ML
Wo
rld
Wid
e W
eb
•In
teg
rati
on
of
dif
fere
nt
da
ta t
yp
es
an
d s
erv
ice
s
•S
imp
le a
nd
fre
ely
av
aila
ble
sta
nd
ard
s a
nd
pro
toco
ls
•C
lien
t-se
rve
r a
rch
ite
ctu
re o
r p
ee
r to
pe
er
•C
om
pa
tib
le u
pg
rad
es
by
W3
C (
Wo
rld
Wid
e W
eb
Co
nso
rtiu
m)
•IC
AN
N (
Inte
rne
t C
orp
ora
tio
n f
or
Ass
ign
ed
Na
me
s a
nd
Nu
mb
ers
) co
ord
ina
tes
the
un
iqu
e id
en
tifi
ers
(d
om
ain
na
me
s, IP
ad
dre
sse
s,
etc
.)
•P
latf
orm
ind
ep
en
de
nt
•D
ece
ntr
aliz
ed
re
sou
rce
s (h
ard
wa
re a
nd
so
ftw
are
)
3
ML
Wo
rld
Wid
e W
eb
•E
ncr
yp
tio
n a
nd
se
cure
co
nn
ect
ion
s
•Fr
ee
to
ols
fo
r a
uth
ori
ng
, se
arc
hin
g, c
om
mu
nic
ati
ng
, etc
.
•In
teg
rati
on
of
tex
t, lin
ks,
pic
ture
s, a
ud
io a
nd
vid
eo
file
s, e
tc.
•H
yp
ert
ex
t u
sin
g H
TM
L -
La
you
t (H
yp
ert
ex
t M
ark
up
La
ng
ua
ge
)
•S
imp
le e
lem
en
ts c
alle
d t
ag
s <A HREF="... "> ... </A>
4
ML
Wo
rld
Wid
e W
eb
•S
pa
m
•S
ecu
rity
an
d p
riv
acy
pro
ble
ms
•E
ne
rgy
inte
nsi
ve
•C
urr
en
tly
aro
un
d 8
0 %
of
the
wo
rld
po
pu
lati
on
ca
nn
ot
acc
ess
th
e W
WW
•A
uth
or
or
use
r?
•W
eb
co
nte
nt
ma
inly
fo
r h
um
an
s
5
ML
Wo
rld
Wid
e W
eb
6
ML
7
•W
orl
d W
ide
We
b
•W
eb
2.0
•S
em
an
tic
We
b
•D
ata
, In
form
ati
on
, an
d K
no
wle
dg
e
•X
ML
an
d O
WL
•O
nto
log
ies
in P
ract
ice
•C
on
clu
sio
ns
Ou
tlin
e
ML
We
b 2
.0
•Fi
rst
We
b 2
.0 c
on
fere
nce
wa
s h
eld
Oct
ob
er
5-7
, 20
04
in
Sa
n F
ran
cisc
o
•S
erv
ice
s lik
e w
eb
log
s, s
oci
al b
oo
km
ark
ing
, w
ikis
, etc
.
8
[An
ge
rme
ier/
Cre
mo
nin
i]
ML
We
b 2
.0 C
on
fere
nce
20
08
9
[htt
p:/
/we
b2
con
.co
m]
ML
So
cia
l Bo
ok
ma
rkin
g
•K
ee
p li
nk
s to
yo
ur
fav
ori
te a
rtic
les,
blo
gs,
mu
sic,
re
vie
ws,
re
cip
es,
an
d m
ore
, an
d a
cce
ss t
he
m f
rom
an
y
com
pu
ter
on
th
e w
eb
.
•S
ha
re f
av
ori
tes
wit
h f
rie
nd
s, f
am
ily, c
ow
ork
ers
, an
d t
he
d
el.i
cio
.us
com
mu
nit
y.
•D
isco
ve
r n
ew
th
ing
s. E
ve
ryth
ing
on
de
l.ici
o.u
s is
so
me
on
e's
fa
vo
rite
--
the
y'v
e a
lre
ad
y d
on
e t
he
wo
rk o
f fi
nd
ing
it. S
o d
el.i
cio
.us
is f
ull
of
bo
ok
ma
rks
ab
ou
t te
chn
olo
gy,
en
tert
ain
me
nt,
use
ful i
nfo
rma
tio
n, a
nd
m
ore
.
10
[htt
p:/
/de
l.ici
o.u
s]
ML
So
cia
l Bo
ok
ma
rkin
g1
1
[htt
p:/
/de
l.ici
o.u
s]
ML
So
cia
l Bo
ok
ma
rkin
g1
2
[htt
p:/
/de
l.ici
o.u
s]
ML
So
cia
l Bo
ok
ma
rkin
g1
3
[htt
p:/
/de
l.ici
o.u
s]
ML
So
cia
l Bo
ok
ma
rkin
g
•Ta
gs
On
e-w
ord
de
scri
pto
rs;
Ass
ign
th
em
to
yo
ur
bo
ok
ma
rks;
Sim
ilar
to k
ey
wo
rds
bu
t n
on
-hie
rarc
hic
al;
Ass
ign
as
ma
ny
ta
gs
to a
bo
ok
ma
rk a
nd
re
na
me
or
de
lete
th
em
late
r;
Tag
gin
g is
ea
sie
r a
nd
mo
re f
lexi
ble
th
an
usi
ng
ca
teg
ori
es
or
fold
ers
.
•Fe
ed
ba
ck f
rom
a u
ser
"Fe
ed
ba
ck is
imm
ed
iate
. As
soo
n a
s yo
u a
ssig
n a
ta
g t
o a
n it
em
, yo
u
see
th
e c
lust
er
of
ite
ms
carr
yin
g t
he
sa
me
ta
g. I
f th
at'
s n
ot
wh
at
you
e
xpe
cte
d, y
ou
're
giv
en
ince
nti
ve
to
ch
an
ge
th
e t
ag
or
ad
d a
no
the
r ...
yo
u c
an
ad
ap
t to
th
e g
rou
p n
orm
, ke
ep
yo
ur
tag
in a
bid
to
infl
ue
nce
th
e g
rou
p n
orm
, or
bo
th."
•Fo
lkso
no
my
Th
e e
me
rgin
g c
ate
go
ry s
tru
ctu
re t
ha
t re
sult
s fr
om
th
e c
om
bin
ati
on
of
a la
rge
nu
mb
er
of
use
rs t
ag
gin
g r
eso
urc
es
for
the
ir o
wn
use
.
14
[htt
p:/
/de
l.ici
o.u
s]
ML
So
cia
l Bo
ok
ma
rkin
g
Fro
m F
olk
son
om
y t
o T
axo
no
my
...
We
bsi
tes
like
Ya
ho
o! o
rga
niz
e a
nd
pre
sen
t lin
ks
in a
fix
ed
hie
rarc
hy
(t
axo
no
my
)
Taxo
no
my
dir
ect
ed
fo
lkso
no
mie
s: T
ex
t a
na
lysi
s o
f th
e w
eb
site
usi
ng
a
lexi
cal d
ata
ba
se li
ke
Wo
rdN
et
•E
ng
lish
no
un
s, v
erb
s, a
dje
ctiv
es
an
d a
dv
erb
s a
re g
rou
pe
d in
to s
ets
of
cog
nit
ive
sy
no
ny
ms
(sy
nse
ts),
ea
ch e
xpre
ssin
g a
dis
tin
ct c
on
cep
t w
ith
20
69
41
wo
rd-s
en
se p
air
s.
•S
yn
sets
are
inte
rlin
ke
d b
y m
ea
ns
of
con
cep
tua
l-se
ma
nti
c a
nd
lexi
cal r
ela
tio
ns
resu
ltin
g in
a
ne
two
rk o
f m
ea
nin
gfu
lly r
ela
ted
wo
rds
an
d c
on
cep
ts.
•W
ord
Ne
t is
als
o f
ree
ly a
nd
pu
blic
ly a
va
ilab
le (
htt
p:/
/wo
rdn
et.
pri
nce
ton
.ed
u/)
•Ta
gs
cou
ld b
e s
ug
ge
ste
d b
y u
sin
g t
he
lexi
cal d
ata
ba
se
Usi
ng
fo
lkso
no
mie
s to
cre
ate
sim
ple
on
tolo
gie
s•
Exa
min
e w
hic
h t
ag
s a
re u
sed
in c
om
bin
ati
on
to
est
ima
te t
he
re
lati
on
s a
mo
ng
th
ese
ta
gs
•M
ap
th
e t
ag
s to
a le
xica
l da
tab
ase
•Le
arn
ad
dit
ion
al r
ela
tio
ns
ba
sed
on
th
e t
ag
clo
ud
s a
nd
th
e le
xica
l da
tab
ase
15 M
L
16
•W
orl
d W
ide
We
b
•W
eb
2.0
•S
em
an
tic
We
b
•D
ata
, In
form
ati
on
, an
d K
no
wle
dg
e
•X
ML
an
d O
WL
•O
nto
log
ies
in P
ract
ice
•C
on
clu
sio
ns
Ou
tlin
e
ML
Th
e S
em
an
tic
We
b is
a v
isio
n f
or
the
fu
ture
of
the
We
b [
...]
info
rma
tio
n is
giv
en
exp
licit
me
an
ing
, [...
] m
ach
ine
s a
uto
ma
tica
lly p
roce
ss a
nd
inte
gra
te in
form
ati
on
av
aila
ble
on
th
e W
eb
.
If m
ach
ine
s a
re e
xpe
cte
d t
o p
erf
orm
use
ful
rea
son
ing
ta
sks
on
th
ese
do
cum
en
ts,
the
lan
gu
ag
e m
ust
go
be
yon
dth
e b
asi
c se
ma
nti
cso
f R
DF
Sch
em
a.
[W3
Ca
, Mill
er]
Se
ma
nti
c W
eb
17 M
L
On
tolo
gy
lan
gu
ag
es
allo
w u
sers
to
wri
te e
xplic
it, f
orm
al
con
cep
tua
liza
tio
ns
of
do
ma
in m
od
els
.
Th
e m
ain
re
qu
ire
me
nts
are
:•
a w
ell-
de
fin
ed
sy
nta
x
•e
ffic
ien
t re
aso
nin
g s
up
po
rt
•a
fo
rma
l se
ma
nti
cs
•su
ffic
ien
t e
xpre
ssiv
e p
ow
er
•co
nv
en
ien
ce o
f e
xpre
ssio
n
Re
qu
ire
me
nts
fo
r O
nto
log
y L
an
gu
ag
es
18
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
•C
lass
me
mb
ers
hip
If x
is a
n in
sta
nce
of
a c
lass
C,
an
d C
is a
su
bcl
ass
of D
,
the
n w
e c
an
infe
r th
at x
is a
n in
sta
nce
of D
.
•E
qu
iva
len
ce o
f cl
ass
es
If c
lass
A is
eq
uiv
ale
nt
to c
lass
B,
an
d c
lass
B is
eq
uiv
ale
nt
to c
lass
C,
the
n A
is e
qu
iva
len
t to
C, t
oo
.
Re
aso
nin
g A
bo
ut
Kn
ow
led
ge
in
On
tolo
gy
La
ng
ua
ge
s1
9
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
•C
on
sist
en
cy
Co
nsi
de
r x
be
ing
an
inst
an
ce o
f cl
ass
es A
an
d B
,
bu
t A
an
d B
are
dis
join
t.
-->
Ind
ica
tio
n o
f a
n e
rro
r in
th
e o
nto
log
y.
•C
lass
ific
ati
on
Ce
rta
in p
rop
ert
y-v
alu
e p
air
s a
re a
su
ffic
ien
t co
nd
itio
n f
or
me
mb
ers
hip
in a
cla
ss A
; if
an
ind
ivid
ua
l x s
ati
sfie
s su
ch c
on
dit
ion
s, w
e c
an
con
clu
de
th
at x
mu
st b
e a
n in
sta
nce
of A
.
20
Re
aso
nin
g A
bo
ut
Kn
ow
led
ge
in
On
tolo
gy
La
ng
ua
ge
s
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
Re
aso
nin
g s
up
po
rt is
imp
ort
an
t fo
r...
...ch
eck
ing
th
e c
on
sist
en
cy o
f th
e o
nto
log
y a
nd
th
e k
no
wle
dg
e.
...ch
eck
ing
fo
r u
nin
ten
de
d r
ela
tio
nsh
ips
be
twe
en
cla
sse
s.
...a
uto
ma
tica
lly c
lass
ify
ing
inst
an
ces
in c
lass
es.
Ch
eck
s lik
e t
he
pre
ced
ing
on
es
are
va
lua
ble
fo
r...
...d
esi
gn
ing
larg
e o
nto
log
ies,
wh
ere
mu
ltip
le a
uth
ors
are
inv
olv
ed
.
...in
teg
rati
ng
an
d s
ha
rin
g o
nto
log
ies
fro
m v
ari
ou
s so
urc
es.
21
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
Re
aso
nin
g in
Pra
ctic
e
ML
Se
ma
nt
We
b A
pp
lica
tio
n F
OA
F
Th
e F
rie
nd
of
a F
rie
nd
(F
OA
F)
pro
ject
:•
is c
rea
tin
g a
We
b o
f m
ach
ine
-re
ad
ab
le p
ag
es
de
scri
bin
g p
eo
ple
, th
e
link
s b
etw
ee
n t
he
m a
nd
th
e t
hin
gs
the
y c
rea
te a
nd
do
•a
pp
lies
sim
ple
te
chn
olo
gy
th
at
ma
ke
s it
ea
sie
r to
sh
are
an
d u
se
info
rma
tio
n a
bo
ut
pe
op
le a
nd
th
eir
act
ivit
ies
(eg
. ph
oto
s, c
ale
nd
ars
, w
eb
log
s)
•F
OA
F u
ses
W3
C's
RD
F t
ech
no
log
y t
o in
teg
rate
info
rma
tio
n f
rom
yo
ur
ho
me
pa
ge
wit
h t
ha
t o
f yo
ur
frie
nd
s, a
nd
th
e f
rie
nd
s o
f yo
ur
frie
nd
s, a
nd
th
eir
fri
en
ds.
..
•F
OA
F-a
-ma
tic
is a
sim
ple
Ja
va
scri
pt
ap
plic
ati
on
th
at
allo
ws
you
to
cr
ea
te a
FO
AF
("F
rie
nd
-of-
A-F
rie
nd
") d
esc
rip
tio
n o
f yo
urs
elf
•M
ak
e f
ile p
ub
lica
lly a
cce
ssib
le (
foa
f.rd
f) a
nd
lin
k it
on
yo
ur
we
bsi
te22
[htt
p:/
/ww
w.f
oa
f-p
roje
ct.o
rg]
ML
Se
ma
nt
We
b A
pp
lica
tio
n F
OA
F C
od
e
<rdf:RDF
...
<foaf:Person rdf:ID="me">
<foaf:name>Monika Lanzenberger</foaf:name>
<foaf:title>Dr.</foaf:title>
<foaf:givenname>Monika</foaf:givenname>
<foaf:family_name>Lanzenberger</foaf:family_name>
<foaf:mbox rdf:resource="mailto: ... "/>
<foaf:phone rdf:resource="tel:+43-1-58801-18871"/>
<foaf:workplaceHomepage rdf:resource="http://www.ifs.tuwien.ac.at/
~mlanzenberger"/>
<foaf:knows>
<foaf:Person>
<foaf:name>Elke Michlmayr</foaf:name>
<foaf:mbox rdf:resource="mailto: ..."/>
</foaf:Person>
</foaf:knows>
</foaf:Person>
</rdf:RDF>
23
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p:/
/ww
w.f
oa
f-p
roje
ct.o
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ML
Se
ma
nt
We
b A
pp
lica
tio
n F
OA
F C
od
e
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:admin="http://webns.net/mvcb/">
<foaf:PersonalProfileDocument rdf:about="">
<foaf:maker rdf:resource="#me"/>
<foaf:primaryTopic rdf:resource="#me"/>
<admin:generatorAgent rdf:resource="http://www.ldodds.com/
foaf/foaf-a-matic"/>
<admin:errorReportsTo
rdf:resource="mailto:[email protected]"/>
</foaf:PersonalProfileDocument>
24
[htt
p:/
/ww
w.f
oa
f-p
roje
ct.o
rg]
ML
25
•W
orl
d W
ide
We
b
•W
eb
2.0
•S
em
an
tic
We
b
•D
ata
, In
form
ati
on
, an
d K
no
wle
dg
e
•X
ML
an
d O
WL
•O
nto
log
ies
in P
ract
ice
•C
on
clu
sio
ns
Ou
tlin
e
ML
De
fin
itio
ns
•D
ata
“in
pu
t si
gn
als
to
se
nso
ry a
nd
co
gn
itiv
e p
roce
sse
s”
•In
form
ati
on
“da
ta w
ith
an
ass
oci
ate
d m
ea
nin
g”
•K
no
wle
dg
e“t
he
wh
ole
bo
dy
of
da
ta a
nd
info
rma
tio
n t
og
eth
er
wit
h c
og
nit
ive
ma
chin
ery
th
at
pe
op
le a
re a
ble
to
e
xplo
it t
o d
eci
de
ho
w t
o a
ct, t
o c
arr
y o
ut
task
s a
nd
to
cr
ea
te n
ew
info
rma
tio
n”
26
[Sch
reib
er
et
al.,
20
00
]
ML
Exa
mp
les
•S
om
e p
iece
s o
f d
ata
a:= 15
b:= "Huber"
•A
pie
ce o
f in
form
ati
on
•A
pie
ce o
f k
no
wle
dg
e
27 M
L
28
•W
orl
d W
ide
We
b
•W
eb
2.0
•S
em
an
tic
We
b
•D
ata
, In
form
ati
on
, an
d K
no
wle
dg
e
•X
ML
an
d O
WL
•O
nto
log
ies
in P
ract
ice
•C
on
clu
sio
ns
Ou
tlin
e
ML
XM
L
•e
Xte
nsi
ble
Ma
rku
p L
an
gu
ag
e
•Fo
un
da
tio
n f
or
the
cre
ati
on
of
pu
rpo
se s
pe
cifi
c, X
ML
-ba
sed
m
ark
up
lan
gu
ag
es
•In
div
idu
ally
de
fin
ed
ta
gs
such
as <company_name>
•U
sin
g U
nic
od
e (
mu
lti-
ling
ua
l ch
ara
cte
r-e
nco
din
g s
yst
em
)
•Fr
ee
, op
en
sta
nd
ard
re
com
me
nd
ed
by
W3
C
•Tw
o le
ve
ls o
f co
rre
ctn
ess
: We
ll-fo
rme
d a
nd
Va
lid
•N
am
esp
ace
pro
vid
e u
niq
ue
ly n
am
ed
ele
me
nts
an
d a
ttri
bu
tes
(xmlns="http://www.w3.org/1999/xhtml"
)
29 M
L
XM
L
<?xml version = "1.0"?>
<buecher schlagwort = "semantic web" >
<buch>
<titel>Visualizing the Semantic Web</titel>
<isbn>1-85233-576-9</isbn>
<ed>
<vorname>Vladimir</vorname>
<nachname>Geroimenko</nachname>
</ed>
<seiten>202</seiten>
<photo filename = "vis_semweb.jpg" />
</buch>
</buecher>
30
ML
•X
ML
pro
vid
es
a s
urf
ace
sy
nta
x fo
r st
ruct
ure
d d
ocu
me
nts
, b
ut
imp
ose
s n
o s
em
an
tic
con
stra
ints
on
th
e m
ea
nin
g o
f th
ese
do
cum
en
ts.
•X
ML
S
che
ma
is
a
la
ng
ua
ge
fo
r re
stri
ctin
g
the
st
ruct
ure
o
f X
ML
d
ocu
me
nts
an
d a
lso
ex
ten
ds
XM
L w
ith
da
ta t
yp
es.
•R
DF
is
a d
ata
mo
de
l fo
r o
bje
cts
("re
sou
rce
s")
an
d r
ela
tio
ns
be
twe
en
th
em
, pro
vid
es
a s
imp
le s
em
an
tics
fo
r th
is d
ata
mo
de
l, a
nd
th
ese
da
ta
mo
de
ls c
an
be
re
pre
sen
ted
in a
n X
ML
sy
nta
x.
•R
DF
Sch
em
a is
a v
oca
bu
lary
fo
r d
esc
rib
ing
pro
pe
rtie
s a
nd
cla
sse
s o
f R
DF
re
sou
rce
s,
wit
h
a
sem
an
tics
fo
r g
en
era
liza
tio
n-h
iera
rch
ies
of
such
p
rop
ert
ies
an
d c
lass
es.
•O
WL
a
dd
s m
ore
v
oca
bu
lary
fo
r d
esc
rib
ing
p
rop
ert
ies
an
d
cla
sse
s:
am
on
g o
the
rs,
rela
tio
ns
be
twe
en
cla
sse
s (e
.g.
dis
join
tne
ss),
card
ina
lity
(e
.g. "
exa
ctly
on
e")
, eq
ua
lity,
ric
he
r ty
pin
g o
f p
rop
ert
ies,
ch
ara
cte
rist
ics
of
pro
pe
rtie
s (e
.g. s
ym
me
try
), a
nd
en
um
era
ted
cla
sse
s.
Fro
m X
ML
to
OW
L3
1
[W3
Ca
]
ML
32
[W3
Ca
, W3
Cb
]
OW
L L
ite
Co
nst
ruct
s: S
imp
le C
lass
es
an
d In
div
idu
als
Sim
ple
Na
me
d C
lass
es:
Class
rdfs:subClassOf
Individual
De
fin
ing
Pro
pe
rtie
s:
rdf:Property
sub
pro
pe
rtie
s:
owl:ObjectProperty
(In
sta
nce
- In
sta
nce
)
owl:DatatypeProperty
(In
sta
nce
- rdfs:Literal
/
XM
L S
che
ma
da
taty
pe
s)
rdfs:subPropertyOf
rdfs:domain
rdfs:range
Pro
pe
rtie
s o
f In
div
idu
als
ML
Sim
ple
Na
me
d C
lass
es:
Class
rdfs:subClassOf
Individual
De
fin
ing
Pro
pe
rtie
s:
rdf:Property
sub
pro
pe
rtie
s:
owl:ObjectProperty
(In
sta
nce
- In
sta
nce
)
owl:DatatypeProperty
(In
sta
nce
- rdfs:Literal
/
XM
L S
che
ma
da
taty
pe
s)
rdfs:subPropertyOf
rdfs:domain
rdfs:range
Pro
pe
rtie
s o
f In
div
idu
als
33
[W3
Ca
, W3
Cb
]
OW
L L
ite
Co
nst
ruct
s: S
imp
le C
lass
es
an
d In
div
idu
als
ML
Sim
ple
Na
me
d C
lass
es:
Class
rdfs:subClassOf
Individual
De
fin
ing
Pro
pe
rtie
s:
rdf:Property
sub
pro
pe
rtie
s:
owl:ObjectProperty
(In
sta
nce
- In
sta
nce
)
owl:DatatypeProperty
(In
sta
nce
- rdfs:Literal
/
XM
L S
che
ma
da
taty
pe
s)
rdfs:subPropertyOf
rdfs:domain
rdfs:range
Pro
pe
rtie
s o
f In
div
idu
als
34
[W3
Ca
, W3
Cb
]
OW
L L
ite
Co
nst
ruct
s: S
imp
le C
lass
es
an
d In
div
idu
als
ML
35
•W
orl
d W
ide
We
b
•W
eb
2.0
•S
em
an
tic
We
b
•D
ata
, In
form
ati
on
, an
d K
no
wle
dg
e
•X
ML
an
d O
WL
•O
nto
log
ies
in P
ract
ice
•C
on
clu
sio
ns
Ou
tlin
e
ML
36
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Cla
ss H
iera
rch
y
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
37
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Sch
em
ati
c R
ep
rese
nta
tio
n
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
38
<owl:TransitiveProperty rdf:ID="is-part-of"/>
<owl:ObjectProperty rdf:ID="eats">
!<rdfs:domain rdf:resource="#animal"/>
</owl:ObjectProperty>
<owl:ObjectProperty rdf:ID="eaten-by">
!<owl:inverseOf rdf:resource="#eats"/>
</owl:ObjectProperty>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Pro
pe
rtie
s
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
39
<owl:Class rdf:ID="plant">
<rdfs:comment>Plants are disjoint from animals.
</rdfs:comment>
<owl:disjointWith="#animal"/>
</owl:Class>
<owl:Class rdf:ID="tree">
<rdfs:comment>Trees are a type of plant.</rdfs:comment>
<rdfs:subClassOf rdf:resource="#plant"/>
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Pla
nts
an
d T
ree
s
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
40
<owl:Class rdf:ID="branch">
!<rdfs:comment>Branches are parts of trees.</rdfs:comment>
!<rdfs:subClassOf>
!<owl:Restriction>
!!
!<owl:onProperty rdf:resource="#is-part-of"/>
!!
!<owl:allValuesFrom rdf:resource="#tree"/>
!!
</owl:Restriction>
!</rdfs:subClassOf>
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Bra
nch
es
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
41
<owl:Class rdf:ID="leaf">
!<rdfs:comment>Leaves are parts of branches. </rdfs:comment>
!<rdfs:subClassOf>
!!
<owl:Restriction>
!!
!<owl:onProperty rdf:resource="#is-part-of"/>
!!
!<owl:allValuesFrom rdf:resource="#branch"/>
!!
</owl:Restriction>
!</rdfs:subClassOf>
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Le
av
es
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
42
<owl:Class rdf:ID="carnivore">
!<rdfs:comment>Carnivores are exactly those animals
!that eat also animals.</rdfs:comment>
!<owl:intersectionOf rdf:parsetype="Collection">
!<owl:Class rdf:about="#animal"/>
!<owl:Restriction>
!!
!<owl:onProperty rdf:resource="#eats"/>
!!
!<owl:someValuesFrom rdf:resource="#animal"/>
!!
</owl:Restriction>
!</owl:intersectionOf>
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Ca
rniv
ore
s
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
43
<owl:Class rdf:ID="herbivore">
<rdfs:comment>Herbivores are exactly those animals that
eat only plants or parts of plants.</rdfs:comment>
...
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
He
rbiv
ore
s
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
?
ML
44
<owl:intersectionOf rdf:parseType="Collection">
<owl:Class rdf:about="#animal"/>
<owl:Restriction>
<owl:onProperty rdf:resource="#eats"/>
<owl:allValuesFrom>
<owl:Class>
<owl:unionOf rdf:parseType="Collection">
<owl:Class rdf:about="#plant"/>
<owl:Restriction>
<owl:onProperty rdf:resource="#is_part_of"/>
<owl:allValuesFrom rdf:resource="#plant"/>
</owl:Restriction>
</owl:unionOf>
</owl:Class>
</owl:allValuesFrom>
</owl:Restriction>
</owl:intersectionOf>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
He
rbiv
ore
s
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
!
ML
45
An
Afr
ica
n W
ildlif
e O
nto
log
y –
He
rbiv
ore
s
[Pro
tég
é 3
.1.1
]
ML
46
<owl:Class rdf:ID="giraffe">
!<rdfs:comment>Giraffes are herbivores, and they
!eat only leaves.</rdfs:comment>
!<rdfs:subClassOf rdf:type="#herbivore"/>
!<rdfs:subClassOf>
!!
<owl:Restriction>
!!
!<owl:onProperty rdf:resource="#eats"/>
!!
!<owl:allValuesFrom rdf:resource="#leaf"/>
!!
</owl:Restriction>
!</rdfs:subClassOf>
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Gir
aff
es
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
47
<owl:Class rdf:ID="lion">
!<rdfs:comment>Lions are animals that eat
!herbivores.</rdfs:comment>
!<rdfs:subClassOf rdf:type="#animal"/>
!<rdfs:subClassOf>
!!
<owl:Restriction>
!!
!<owl:onProperty rdf:resource="#eats"/>
!!
!<owl:someValuesFrom rdf:resource="#herbivore"/>
!!
</owl:Restriction>
!</rdfs:subClassOf>
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Lio
ns
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
?
48
<owl:Class rdf:ID="tasty-plant">
<rdfs:comment>Plants eaten both by herbivores and
carnivores </rdfs:comment>
! !!
...
</owl:Class>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Ta
sty
Pla
nts
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
!
49
<rdfs:subClassOf rdf:resource="#plant"/>
<rdfs:subClassOf>
<owl:Restriction>
<owl:onProperty rdf:resource="#eaten_by"/>
<owl:someValuesFrom>
<owl:Class rdf:about="#herbivore"/>
</owl:someValuesFrom>
</owl:Restriction>
</rdfs:subClassOf>
<rdfs:subClassOf>
<owl:Restriction>
<owl:onProperty rdf:resource="#eaten_by"/>
<owl:someValuesFrom>
<owl:Class rdf:about="#carnivore"/>
</owl:someValuesFrom>
</owl:Restriction>
</rdfs:subClassOf>
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Ta
sty
Pla
nts
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
50
An
Afr
ica
n W
ildlif
e O
nto
log
y –
Ta
sty
Pla
nts
[Pro
tég
é 3
.1.1
]
ML
51
Wh
at
pro
ble
m w
ou
ld e
me
rge
if w
e r
ep
lace
owl:someValuesFrom
b
y
owl:allValuesFrom
in
th
e d
efi
nit
ion
of
carn
ivo
res?
An
Afr
ica
n W
ildlif
e O
nto
log
y
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
]
ML
52
•W
orl
d W
ide
We
b
•W
eb
2.0
•S
em
an
tic
We
b
•O
nto
log
ies
in P
ract
ice
•X
ML
an
d O
WL
•D
ata
, In
form
ati
on
, an
d K
no
wle
dg
e
•C
on
clu
sio
ns
Ou
tlin
e
ML
Ple
ase
en
ter
you
r co
ncl
usi
on
s ...
•V
erw
en
de
n S
ie W
eb
2.0
To
ols
?
•H
att
en
Sie
sch
on
ma
l mit
Se
ma
nti
c W
eb
zu
tu
n?
•K
ön
nte
Ihn
en
ein
e O
nto
log
ie, d
ie W
isse
n ü
be
r d
as
Stu
diu
m u
nd
die
Te
chn
isch
e U
niv
ers
itä
t zu
r V
erf
üg
un
g s
tellt
, nü
tzlic
h s
ein
?
•W
en
n S
ie e
in S
em
an
tic
We
b T
oo
l en
twic
ke
ln w
ürd
en
, w
elc
he
s fä
nd
en
Sie
nü
tzlic
h u
nd
inte
ress
an
t?
53 M
L
54
[An
ge
rme
ier/
Cre
mo
nin
i] M
. An
ge
rme
ier,
We
b 2
.0 M
ind
ma
p, 2
00
5;
ex
ten
sio
n b
y L
. Cre
mo
nin
i, h
ttp
://
en
.wik
ipe
dia
.org
/wik
i/Im
ag
e:W
eb
_2
.0_
Ma
p.s
vg
(ch
eck
ed
on
line
10
. Oct
. 20
07
).
[An
ton
iou
an
d v
an
Ha
rme
len
, 20
04
] G
. An
ton
iou
an
d F
. va
n H
arm
ele
n,
A S
em
an
tic
We
b P
rim
er,
MIT
Pre
ss, M
ass
ach
use
tts,
20
04
.
[In
tern
etW
orl
dS
tats
] M
iniw
att
s M
ark
eti
ng
Gro
up
, In
tern
et
Wo
rld
Sta
ts, U
sag
e a
nd
Po
pu
lati
on
Sta
tist
ics,
htt
p:/
/ww
w.in
tern
etw
orl
dst
ats
.co
m/s
tats
.htm
(ch
eck
ed
on
line
10
. Oct
. 20
07
).
[Mil
ler]
Eri
c M
ille
r, W
3C
La
yer
Ca
ke
, htt
p:/
/ww
w.w
3.o
rg/2
00
1/0
9/0
6-e
cdl/
slid
e1
7-0
.htm
l(c
he
cke
d o
nlin
e 2
9. S
ep
. 20
06
).
[Pro
tég
é 3
.1.1
] S
tan
ford
Me
dic
al I
nfo
rma
tics
, Pro
tég
é-O
WL
,h
ttp
://p
rote
ge
.sta
nfo
rd.e
du
/do
wn
loa
d/d
ow
nlo
ad
.htm
l (ch
eck
ed
on
line
8. N
ov.
20
06
).
[Sch
reib
er
et
al.
, 20
00
] G
. Sch
reib
er,
H. A
kk
erm
an
s, A
. An
jew
ierd
en
, R. d
e H
oo
g, N
. Sh
ad
bo
lt, W
. va
n d
e F
eld
e, a
nd
B
. Wie
ling
a. K
no
wle
dg
e E
ng
ine
eri
ng
an
d M
an
ag
em
en
t: T
he
Co
mm
on
KA
DS
Me
tho
do
log
y, M
IT P
ress
, 20
00
.
[W3
Ca
] O
WL
We
b O
nto
log
y L
an
gu
ag
e O
ve
rvie
w,
htt
p:/
/ww
w.w
3.o
rg/T
R/2
00
4/R
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