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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Local Closed World Semantics: Keep it simple, stupid!</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Adila Krisnadhi</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Kunal Sengupta</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Pascal Hitzler</string-name>
          <email>pascalg@knoesis.orgg</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Wright State University</institution>
          ,
          <addr-line>Dayton OH 45435</addr-line>
          ,
          <country country="US">USA</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>A combination of open and closed-world reasoning (usually called local closed world reasoning) is a desirable capability of knowledge representation formalisms for Semantic Web applications. However, none of the proposals made to date for extending description logics with local closed world capabilities has had any signi cant impact on applications. We believe that one of the key reasons for this is that current proposals fail to provide approaches which are intuitively accessible for application developers and at the same time are applicable, as extensions, to expressive description logics such as SROIQ, which underlies the Web Ontology Language OWL. In this paper we propose a new approach which overcomes key limitations of other major proposals made to date. It is based on an adaptation of circumscriptive description logics which, in contrast to previously reported circumscription proposals, is applicable to SROIQ without rendering reasoning over the resulting language undecidable.</p>
      </abstract>
      <kwd-group>
        <kwd>description logic</kwd>
        <kwd>closed world</kwd>
        <kwd>circumscription</kwd>
        <kwd>decidability</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        The semantics of the Web Ontology Language OWL [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ] (which is based on the
description logic SROIQ [
        <xref ref-type="bibr" rid="ref17">17</xref>
        ]) adheres to the Open World Assumption (OWA).
This means that statements which are not logical consequences of a given
knowledge base are not necessarily considered false. The OWA is reasonable in a World
Wide Web context (and thus for Semantic Web applications), however situations
naturally arise where it would be preferable to use the Closed World Assumption
(CWA), that statements which are not logical consequences of a given
knowledge base are always considered false. The CWA is applicable, e.g., when data is
being retrieved from a database, or if data can otherwise be considered complete
with respect to the application at hand (see, e.g., [
        <xref ref-type="bibr" rid="ref14 ref34">14, 34</xref>
        ]).
      </p>
      <p>
        As a consequence, e orts have been made to combine OWA and CWA
modeling for the Semantic Web (see Section 4), and knowledge representation
languages which have both OWA and CWA modeling features are said to adhere to
the Local Closed World Assumption (LCWA). Most of these combinations are
derived from non-monotonic logics which have been studied in logic
programming [
        <xref ref-type="bibr" rid="ref18">18</xref>
        ] or on rst-order predicate logic [
        <xref ref-type="bibr" rid="ref28 ref29 ref35">28, 29, 35</xref>
        ]. Furthermore, many of them
have a hybrid character, meaning that they achieve the LCWA by combining,
e.g. description logics with (logic programming) rules.
      </p>
      <p>Of the approaches which provide a seamless (non-hybrid) integration of OWA
and CWA, there are not that many, and each of them has its drawbacks. This
is despite the fact that the modeling task, from the perspective of the
application developer, seems rather simple: Users would want to specify, simply, that
individuals in the extension of a predicate should be exactly those which are
necessarily required to be in the extension, i.e., extensions should be minimized.
Thus, what is needed for applications is a simple, intuitive approach to closed
world modeling, which can be easily picked up by application developers.</p>
      <p>
        Among the primary approaches to non-monotonic reasoning, there is exactly
one approach which employs the minimization idea in a very straightforward
and intuitively simple manner, namely circumscription [
        <xref ref-type="bibr" rid="ref28">28</xref>
        ]. However, a naive
transfer of the circumscription approach to description logics, which was done
in [
        <xref ref-type="bibr" rid="ref15 ref4 ref5">4, 5, 15</xref>
        ], appears to have three primary drawbacks.
1. The approach is undedicable for expressive description logics (e.g., for the
description logic SROIQ) unless awkward restrictions are put in place. More
precisely, it is not possible to have non-empty TBoxes plus minimization of
roles if decidability is to be retained.
2. Extensions of minimized prediates can still contain elements which are not
named individuals (or pairs of such, for roles) in the knowledge base, which
is not intuitive for modeling (see also [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ]).
3. Complexity of the approach is very high.
      </p>
      <p>
        The undecidability issue (point 1) hinges, in a sense, also on point 2 above.
In this paper, we provide a modi ed approach to circumscription for description
logics, which we call grounded circumscription, which remedies both of points 1
and 2. We are not yet addressing the complexity issue; this will be done in future
work. Our idea is simple yet e ective: we modify the circumscription approach
from [
        <xref ref-type="bibr" rid="ref15 ref4 ref5">4, 5, 15</xref>
        ] by adding the additional requirement that extensions of minimized
predicates may only contain named individuals (or pairs of such, for roles). In a
sense, this can be understood as porting a desirable feature from (hybrid) MNKF
description logics [
        <xref ref-type="bibr" rid="ref20 ref21 ref32 ref9">9, 20, 21, 32</xref>
        ] to the circumscription approach. In another (but
related) sense, it can also be understood as employing the idea of DL-safety [
        <xref ref-type="bibr" rid="ref33">33</xref>
        ],
respectively of DL-safe variables [
        <xref ref-type="bibr" rid="ref24">24</xref>
        ] or nominal schemas [
        <xref ref-type="bibr" rid="ref22 ref23">22, 23</xref>
        ].
      </p>
      <p>
        Note that we do not claim that our approach is the only road to take|we
rather view it as one step on the quest of designing suitable LCWA languages for
the Semantic Web. Indeed, we mainly intend to highlight that there is a plethora
of methods how to obtain local closed world versions of description logics (and
thus of OWL), see e.g. [
        <xref ref-type="bibr" rid="ref25 ref26">25, 26</xref>
        ], and all of them are potential alternatives to the
big three (circumscription [
        <xref ref-type="bibr" rid="ref28">28</xref>
        ], autoepistemic logic [
        <xref ref-type="bibr" rid="ref29">29</xref>
        ], and default logic [
        <xref ref-type="bibr" rid="ref35">35</xref>
        ]).
The Semantic Web community needs a systematic investigation of options for
modeling local closed world aspects, which are not ideologically bound to
approaches which have been developed for di erent purposes in the KR community.
      </p>
      <p>The paper is structured as follows. In Section 2 we introduce the semantics
of grounded circumscription. In Section 3 we show that the resulting language is
decidable. In Section 4 we discuss related work, and conclude with a discussion
of further work in Section 5.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Grounded Circumscription</title>
      <p>
        We now describe a very simple way for ontology designers to model local closed
world aspects in their ontologies: simply use a description logic (DL) knowledge
base (KB) as usual, and augment it with meta-information which states that
some predicates (concept names or role names) are closed. Semantically, those
predicates are considered minimized, i.e. their extensions contain only what is
absolutely required, and furthermore only contain known (or named )
individuals, i.e., individuals which are explicitly mentioned in the KB. In the case of
concept names, the idea of restricting their extensions only to known individuals
is similar to the notion of nominal schema [
        <xref ref-type="bibr" rid="ref23">23</xref>
        ] (and thus, DL-safe rules [
        <xref ref-type="bibr" rid="ref24 ref33">24, 33</xref>
        ])
and also the notion of DBox [
        <xref ref-type="bibr" rid="ref38">38</xref>
        ], while the minimization idea is borrowed from
circumscription [
        <xref ref-type="bibr" rid="ref28">28</xref>
        ], one of the primary approaches to non-monotonic reasoning.
      </p>
      <p>
        In the earlier e orts to carry over circumscription to DLs [
        <xref ref-type="bibr" rid="ref14 ref15 ref4 ref5">4, 5, 14, 15</xref>
        ],
circumscription is realized by the notion of circumscription pattern. A circumscription
pattern consists of three disjoint sets of predicates (i.e., concept names and role
names) which are called minimized, xed and varying predicates, and a
preference relation on interpretations. The preference relation allows us to pick
minimal models as the preferred models with respect to inclusion of the extension
of the minimized predicates.
      </p>
      <p>Our formalism simpli es the circumscription approach by restricting our
attention to models in which the extension of the minimized predicates may only
contain known individuals from the KB. Moreover, we divide predicates in the
KB only into two disjoint sets of minimized and non-minimized predicates.1
The non-minimized predicates would be viewed as varying in the more general
circumscription formalism mentioned above.</p>
      <p>
        Let NC , Nr, and NI be disjoint, countably in nite sets of concept names,
role names, and individual names, resp. Let L be a standard description logic
whose concepts and roles are formed based on the signature that consists of NC ,
NR, and NI , together with a set of standard DL (concept and role) constructors
[
        <xref ref-type="bibr" rid="ref2">2</xref>
        ]. The only non-standard DL constructor that is needed in this paper is the
role constructor concept product, written C D with C; D concepts in L, which
allows a role to be constructed from the Cartesian product of two concepts [
        <xref ref-type="bibr" rid="ref23 ref37">23,
37</xref>
        ]. In addition, we de ne an L-KB as a set of concept inclusion axioms C v D
where C; D 2 NC , role inclusion axioms r v s where r; s 2 Nr, and assertions of
the form C(a) and r(a; b) where C 2 NC ; r 2 Nr and a; b 2 NI .
      </p>
      <p>
        The semantics for L is de ned in terms of interpretations I = ( I ; I ) where
I is a non-empty set called the domain and I is an interpretation function
1 Fixed predicates can be simulated in the original circumscriptive DL approach if
negation is available, i.e., for xed class names, class negation is required, while for
xed role names, role negation is required. The latter can be added to expressive
DLs without jeopardizing decidability [
        <xref ref-type="bibr" rid="ref23 ref40">23, 40</xref>
        ].
that maps each concept name to a subset of I , each role name to a subset of
      </p>
      <p>I I and each individual name to an element of I . An interpretation I is
extended to complex concepts and roles in the usual way for L, and for concept
products, (C D)I = f(x; y) j x 2 CI ; y 2 DI g. We say that I satis es (is a
model of ): a concept inclusion axiom C v D if CI DI ; a role inclusion axiom
r v s if rI sI ; a concept assertion C(a) if aI 2 CI ; and a role assertion r(a; b)
if (aI ; bI ) 2 rI . We also say that I satis es (is a model of ) an L-KB K if it
satis es every axioms in K.</p>
      <p>The non-monotonic feature of the formalism is given by restricting models
of an L-KB such that the extension of closed predicates may only contain
individuals (or pairs of them) which are explicitly occurring in the KB, plus a
minimization of the extensions of these predicates. We de ne a function Ind that
maps each L-KB to the set of individual names it contains, i.e., given an L-KB
K, Ind(K) = fb 2 NI j b occurs in Kg. Among all possible models of K that are
obtained by the aforementioned restriction to Ind(K), we then select a model
that is minimal w.r.t. concept inclusion or role inclusion.</p>
      <p>De nition 1. A GC-L-knowledge base (KB)|GC stands for grounded
circumscription|is a pair (K; M ) where K is an L-KB and M fA 2 NC j</p>
      <sec id="sec-2-1">
        <title>A occurs in Kg [ fr 2 Nr j r occurs in Kg. For every concept name and role</title>
        <p>name W 2 M , we say that W is closed with respect to K. For any two models</p>
      </sec>
      <sec id="sec-2-2">
        <title>I and J of K, we furthermore say that I is smaller than J w.r.t. M , written</title>
        <p>I M J , i all of the following hold: (i) I = J and aI = aJ for every
aI 2 J ; (ii) W I W J for every W 2 M ; and (iii) there exists a W 2 M
such that W I W J
We now de ne models of GC-L-KBs as follows.</p>
      </sec>
      <sec id="sec-2-3">
        <title>De nition 2. An interpretation I is a GC-model of a GC-L-KB (K; M ) if all</title>
        <p>of the following hold: (i) I is a model of K; (ii) for each concept name A 2 M ,</p>
      </sec>
      <sec id="sec-2-4">
        <title>AI fbI j b 2 Ind(K)g; (iii) for each role name r 2 M , rI fbI j b 2</title>
      </sec>
      <sec id="sec-2-5">
        <title>Ind(K)g fbI j b 2 Ind(K)g; and (iv) I is minimal w.r.t. M , i.e., there is no model J of K such that J M I.</title>
        <p>The notion of logical consequence is de ned as usual: An axiom is a logical
consequence (a GC-inference) of a given GC-L-KB (K; M ) if and only if is
true in all GC-models of (K; B).</p>
        <p>
          Our formalism here is inspired by one of the approaches described by
Makinson in [
          <xref ref-type="bibr" rid="ref26">26</xref>
          ], namely restricting the set of valuations to get more logical
consequences than what we can get as classical consequences. Intuitively, this approach
is a simpler version of the circumscription formalism for DLs as presented in [
          <xref ref-type="bibr" rid="ref15 ref5">5,
15</xref>
          ] in the sense that concept names and role names are either varying or
minimized, i.e., no predicate is considered xed. Indeed, every GC-model of a KB
is also a circumscriptive model,2 hence every circumscriptive inference is also a
valid GC-inference.
2 This can be seen, e.g., by a straightforward proof by contradiction.
        </p>
        <p>To give an example, consider the knowledge base K consisting of the axioms
hasAuthor(paper1; author1)</p>
        <p>
          hasAuthor(paper1; author2)
hasAuthor(paper2; author3)
&gt; v 8hasAuthor:Author:
Then ( 2 hasAuthor:Author)(paper1) is not a logical consequence of K under
the classical description logic semantics. However, if we assume that we have
complete information on authorships relevant to the application under
consideration, then it would be reasonable to close parts of the knowledge base in the
sense of the LCWA. In the original approach to circumscriptive DLs, we could
close the class name Author, but to no avail. But if we close hasAuthor, we
obtain ( 2 hasAuthor:Author)(paper1) as a logical consequence. However, closure
of roles in the original circumscriptive DL approach leads to undecidability [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ].
The GC-semantics, in contrast, is decidable even under role closure (see Section
3 below), and also yields the desired inferences.
        </p>
        <p>Are there inferences which hold with respect to the GC-semantics but not
with respect to the original circumscriptive DL approach? There are, but it seems
di cult to nd a convincing example which might indicate practical relevance.
If this is indeed the case, then we could argue that the original circumscriptive
approach is too sceptical with respect to application requirements, in addition
to the decidability issue already noted.</p>
        <p>
          The following is an academic example, adapted from [
          <xref ref-type="bibr" rid="ref15">15</xref>
          ], which shows the
di erent inferencing capabilities of the GC-semantics versus the original
circumscriptive DL semantics. Consider the knowledge base K1 consisting of the
following axioms, where EndangeredSpecies is a minimized class name.
        </p>
        <p>Bear(polarBear)
9isHabitatFor:(Bear u EndangeredSpecies)(arcticSea)</p>
        <p>In the original circumscriptive DL approach, there is a model in which the
extensions of both Bear and EndangeredSpecies share a common element
distinct from polarBear, hence it cannot be concluded that polarBear is an
EndangeredSpecies. Under the GC-semantics, however, this can be concluded.
This is due to the fact that there are no individuals other than polarBear in
the knowledge base. Indeed, if we assume that there is another individual, say,
blueWhale, then the conclusion no longer holds even under the GC-semantics.</p>
        <p>Is the conclusion under the GC-semantics desirable, that polarBear is an
EndangeredSpecies? We believe so, because we are essentially restricting our
world to one individual. I.e., if we would like to reject the conclusion, we should
rather question the adequacy of our modeling, than of the semantics. However,
this discussion seems to be quite academic, since the situation above is not that
of a realistic knowledge base, where we could reasonably assume the presence of
other individuals, such as blueWhale, such that the arguable inference no longer
holds even with respect to the GC-semantics.3 And indeed it should not hold
3 The situation might be di erent with respect to knowledge bases under development,
but this would rather be an interface issue.
in this case under an intuitive reading of the knowledge base: If there is also a
second individual blueWhale, then we have no reason to assume that it must
be polarBear which is an EndangeredSpecies (unless, of course, we also state
that blueWhale must not be a Bear).
3</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Decidability Considerations</title>
      <p>
        As noted earlier, circumscription in many expressive DLs is undecidable [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ].
Undecidability even extends to the basic DL ALC when non-empty TBoxes are
considered and roles are allowed as minimized predicates. Such a bleak outlook
would greatly discourage useful application of circumscription, despite the fact
that there is a clear need of such a formalism to model LCWA.
      </p>
      <p>
        Our formalism aims to ll this gap by o ering a simpler approach to
circumscription in DLs that is decidable provided that the underlying DL is also
decidable. The decidability result is obtained due to the imposed restriction of
minimized predicates to known individuals in the KB as speci ed in De nition 2.
Let L be any standard DL. We consider the following reasoning task of GC-KB
satis ability : \given a GC-L-KB (K; M ), does (K; M ) have a GC-model?" and
show in the following that this is decidable. Note that other basic reasoning tasks
can usually be reduced to this task [
        <xref ref-type="bibr" rid="ref15 ref5">5, 15</xref>
        ].
      </p>
      <p>Assume that L is any (standard) DL, e.g., ALCOB( ), featuring nominals,
concept disjunction, concept products and role disjunctions.4 We show that
GCKB satis ability in L is decidable if satis ability in L is decidable.</p>
      <p>Let (K; M ) be a GC-L-KB. We assume that M = MA [ Mr where MA =
fA1; : : : ; Ang is the set of minimized concept names and Mr = fr1; : : : ; rmg is
the set of minimized role names. Now de ne a family of (n + m)-tuples as
G(K;M) = f(X1; : : : ; Xn; Y1; : : : ; Ym) j Xi
Ind(K); Yj</p>
      <p>Ind(K)</p>
      <p>Ind(K)g
with 1
i
n; 1
j</p>
      <p>m. Note that there are
of such tuples; in particular note that G(K;M) is a nite set.</p>
      <p>Now, given (K; M ) and some G = (X1; : : : ; Xn; Y1; : : : ; Ym) 2 G(K;M), let
KG be the L-KB consisting of all axioms in K together with all of the following
axioms, where the Ai and rj are all the predicates in M |note that we require
role disjunction and concept products for this.
for every a 2 Xi and i = 1; : : : ; n
fbg)</p>
      <p>for every pair (a; b) 2 Yj and j = 1; : : : ; m</p>
      <p>
        Then the following result clearly holds.
4 For concept products, see [
        <xref ref-type="bibr" rid="ref23">23</xref>
        ]|they can be eliminated if role constructors are
available. For role disjunctions, see [
        <xref ref-type="bibr" rid="ref40">40</xref>
        ], where it is shown, amongst other things, that
ALCQIOB is decidable.
      </p>
      <sec id="sec-3-1">
        <title>Lemma 1. Let (K; M ) be a GC-L-KB. If (K; M ) has a GC-model I, then there</title>
        <p>exists G 2 G(K;M) such that KG has a (classical) model J which coincides with</p>
      </sec>
      <sec id="sec-3-2">
        <title>I on all minimized predicates. Likewise, if there exists G 2 G(K;M) such that KG</title>
        <p>has a (classical) model J , then (K; M ) has a GC-model I which coincides with</p>
      </sec>
      <sec id="sec-3-3">
        <title>J on all minimized predicates.</title>
        <p>
          Observe that class disjunction, nominals, concept products, and role
disjunction are needed to obtain Lemma 1. From [
          <xref ref-type="bibr" rid="ref40">40</xref>
          ] we know that adding role
disjunction to ALCQIO retains decidability. Now consider the set
        </p>
        <p>G(0K;M) = fG 2 G(K;M) j KG has a (classical) modelg;
and note that this set is nite and computable in nite time since G(K;M) is
nite and L is decidable. Furthermore, consider G(0K;M) to be ordered by the
pointwise ordering induced by . Note that the pointwise ordering of the
nite set G(0K;M) is also computable in nite time.</p>
      </sec>
      <sec id="sec-3-4">
        <title>Lemma 2. Let (K; M ) be a GC-L-KB and let</title>
        <p>G(00K;M) = fG 2 G(0K;M) j G is minimal in (G(0K;M); )g:</p>
      </sec>
      <sec id="sec-3-5">
        <title>Then (K; M ) has a GC-model if and only if G(00K;M) is non-empty.</title>
        <p>Proof. This follows immediately from Lemma 1 together with the following
observation: Whenever K has two GC models I and J such that I is smaller than
J , then there exist GI ; GJ 2 G(0K;M) with GI GJ such that KGI and KGJ
have (classical) models I0 and J 0, respectively, which coincide with I,
respectively, J , on the minimized predicates.</p>
        <p>Theorem 1. GC-KB-satis ability is decidable.</p>
        <p>Proof. This follows from Lemma 2 since the set G(00K;M), for any given GC-KB
(K; M ), can be computed in nite time, i.e., it can be decided in nite time
whether G(00K;M) is empty.</p>
        <p>Some remarks on complexity are as follows. Assume that the problem of
deciding KB satis ability in L is in the complexity class C. Observe from
equation (1) that there are exponentially many possible choices of the (n + m)-tuples
in G(K;M) (in the size of the input knowledge base). Computation of G(0K;M) is
thus in ExpC, and subsequent computation of G(00K;M) is also in Exp. We thus
obtain the following upper bound.</p>
        <p>Proposition 1. GC-KB satis ability is in ExpC , where C is the complexity
class of the DL under consideration.</p>
        <p>
          Observe that the decidability proof gives rise to a straightforward
implementation procedure, however this is certainly not a smart algorithm. As future
work, it should be possible to adjust the tableaux algorithm from [
          <xref ref-type="bibr" rid="ref15">15</xref>
          ], which
may also give rise to a sharpening of the upper bound on complexity.
        </p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>Related Work</title>
      <p>In this paper we have presented a new approach to DL reasoning under the Local
Closed World Assumption (LCWA). There are several approaches described in
the literature for LCWA which combine the OWA and CWA semantics, and in
the following we brie y discuss some of the most important proposals.</p>
      <p>
        Autoepistemic Logic [
        <xref ref-type="bibr" rid="ref29 ref30">29, 30</xref>
        ] is an approach followed by a number of authors.
The semantics of autoepistemic logic have been de ned using an autoepistemic
operator K [
        <xref ref-type="bibr" rid="ref7 ref8">7, 8</xref>
        ] and has been studied for ALC and also for more expressive
DLs. [
        <xref ref-type="bibr" rid="ref7 ref9">7, 9</xref>
        ] further provide an epistemic operator A related to negation-as-failure
which allows for the modeling of default rules and integrity constraints.
      </p>
      <p>
        Circumscription [
        <xref ref-type="bibr" rid="ref28">28</xref>
        ] is another approach taken to develop LCWA
extentions of DLs [
        <xref ref-type="bibr" rid="ref14 ref15 ref5">5, 14, 15</xref>
        ]. [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] evaluates the complexities of reasoning problems in
variations of DLs with circumscription. [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ] provides examples to stress the
importance of LCWA to provide an intuitive notion of matchmaking of resources
in the context of Semantic Web Services. [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ] provides an algorithmization for
circumscriptive ALCO by introducing a preferential tableaux calculus, based on
previous work on circumscription [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ]. [
        <xref ref-type="bibr" rid="ref19">19</xref>
        ] proves a method to eliminate xed
predicates in circumscription patterns by adding negation of xed predicates to
the minimized set of predicates.
      </p>
      <p>
        Some signi cant proposals involve the use of hybrid MKNF knowledge bases
[
        <xref ref-type="bibr" rid="ref32">32</xref>
        ] which are based on an adaptation of the Stable Model Semantics [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ] to
knowledge bases consisting of ontology axioms and rules, thereby combining
both open world and closed world semantics. A variant of this approach using
the well-founded semantics, i.e., with a lower complexity, has also be presented
[
        <xref ref-type="bibr" rid="ref20 ref21">20, 21</xref>
        ], and algorithms and implementations have been developed [
        <xref ref-type="bibr" rid="ref1 ref13">1, 13</xref>
        ].
      </p>
      <p>
        [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ] takes a hybrid approach to combine ontologies and rules by keeping the
semantics of both parts separate, but also at the same time allowing for building
rules on top of ontologies and vice versa with some limitations, again following
the Stable Model Semantics. [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ] provides a related well-founded semantics.
      </p>
      <p>
        Some of the work related to LCWA also involves the use of integrity
constraints (ICs) and of the Unique Name Assumption (UNA). An approach
extending OWL ontologies to add ICs such that it adds non-montonicity to the
DL is [
        <xref ref-type="bibr" rid="ref31">31</xref>
        ]. [
        <xref ref-type="bibr" rid="ref39">39</xref>
        ] provides semantics for OWL axioms to allow for IC and UNA to
achieve local closed world reasoning.
      </p>
      <p>
        In [
        <xref ref-type="bibr" rid="ref38">38</xref>
        ], the notion of DBox is introduced. A DBox consists of a set of (atomic)
assertions such that the extension of a DBox predicate under any interpretation
is exactly as de ned by this set of assertions. In a sense, grounded
circumscription encompasses this expressive feature but goes beyond it, while, as expected,
loosing some of the desirable features of the more specialized DBox approach.
      </p>
      <p>
        There are a number of other approaches which have been attempted in the
past, but without follow-up work, e.g. [
        <xref ref-type="bibr" rid="ref27 ref3 ref36 ref6">3, 6, 27, 36</xref>
        ]. For some further pointers to
the literature, please refer to [
        <xref ref-type="bibr" rid="ref22">22</xref>
        ].
      </p>
    </sec>
    <sec id="sec-5">
      <title>Conclusion and Outlook</title>
      <p>We have provided a new approach for incorporating the LCWA into description
logics. Our approach, grounded circumscription, is a variant of circumscriptive
description logics which avoids two major issues of the original approach:
Extensions of minimized predicates can only contain named individuals, and we
retain decidability even for very expressive description logics while we can allow
for the minimization of roles.</p>
      <p>A primary theoretical task is to investigate the complexity of our approach,
but it can be expected that it is not going to be worse than the previous
circumscription proposal. In fact, lower complexities should result in some cases,
which may yield to tractable or data-tractable fragments.</p>
      <p>
        Likewise, it should be possible to adapt the tableaux algorithm for
circumscriptive description logics from [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ] to our setting, and there may even be more
e cient procedures.
      </p>
      <p>From a more general perspective, it should be worthwhile to investigate
further alternatives for incorporating closed world modeling into description logics.
Preferably, one would like to obtain a language which is intuitively very simple,
appeals to ontology engineers, and is computationally e ective. Whether such a
language exists, however, is an open question.</p>
      <p>Acknowledgements. This work was supported by the National Science
Foundation under award 1017225 \III: Small: TROn|Tractable Reasoning with
Ontologies," and by State of Ohio Research Incentive funding in the Kno.e.CoM
project. The rst named author acknowledges support by a Fulbright Indonesia
Presidential Scholarship PhD Grant 2010.</p>
    </sec>
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