=Paper=
{{Paper
|id=Vol-496/paper-23
|storemode=property
|title=Use of OWL in the Legal Domain (Statement of Interest)
|pdfUrl=https://ceur-ws.org/Vol-496/owled2008dc_paper_24.pdf
|volume=Vol-496
|dblpUrl=https://dblp.org/rec/conf/owled/Hoekstra08
}}
==Use of OWL in the Legal Domain (Statement of Interest)==
https://ceur-ws.org/Vol-496/owled2008dc_paper_24.pdf
Use of OWL in the Legal Domain
Statement of Interest
Rinke Hoekstra
Leibniz Center for Law, University of Amsterdam
PO Box 1030, 1000 BA, Amsterdam, The Netherlands
hoekstra@uva.nl
Abstract. The Leibniz Center for Law at the University of Amsterdam
is involved in several research projects that deal with the integration of
knowledge representation with legal texts. For many of these projects,
the use of ontologies in OWL DL plays an important, if not a central
role. In this statement of interest we give a short sketch of the kind
of application we see for OWL in the legal domain, and discuss several
state-of-the-art developments by leaders in the OWL DL field, that are
of primary interest to us.
1 Introduction
The Leibniz Center for Law1 at the University of Amsterdam is involved in sev-
eral research projects that deal with the integration of knowledge representation
with legal texts, both in the form of semantic annotations and for the devel-
opment of full-blown knowledge based systems. For many of these projects, the
use of ontologies in OWL DL plays an important, if not a central role. In this
statement of interest we give a short sketch of the kind of application we see
for OWL in the legal domain, and discuss several state-of-the-art developments
by pioneers of uncharted territories in the OWL DL field, that are of primary
interest to us.
2 Text and Representation
In many ways, the corpus of legal information available today is the world wide
web’s little sister, at least qua structure. It consists of a huge volume of hetero-
geneous, but closely inter-linked documents. These documents are increasingly
being made available in digital form as part of public accessibility projects by
governments.2 However, a major difference is that the relations between legal
1
The Leibniz Center for Law is part of the Faculty of Law of the University of Amster-
dam and participates in the OWL Working Group. See http://www.leibnizcenter.
org.
2
An example is the portal of the Dutch government http://www.wetten.nl that
discloses currently active legislation
texts are typically expressed in natural language only. Also, these references are
not always absolute, typically point to parts of documents, and often import an
externally defined meaning of a term [7, 8]. Consolidation of such semantic ref-
erences into a single representation introduces a significant maintenance issue,
as legal texts are very dynamic and undergo change independently from each
other. In fact, the meaning of terms in law imposes an ordering on entities in
reality that can change over time, but stays applicable to older cases. In short,
law adopts an intricate versioning scheme [2, 4]. We are involved in the Met-
aLex/CEN3 XML standard for legislative sources [5, 1] that provides an XML
schema for representing the structure and dynamics of legal texts.
It is our firm conviction that a semantic representation – be it for the purpose
lightweight annotation, consistency checking or legal knowledge based reasoning
(planning, assessment) – should take the dynamic and structural properties of
legal texts into account. This is most directly reflected in the principle of trace-
ability: any representation of some legal text should be traceable to its original
source. A representation of some (part of) legislation is dependent on that leg-
islation, and is therefore essentially always an annotation on that text. The
MetaLex/CEN initiative provides a standard transformation of XML encoded
legal texts to RDF/XML. More elaborate, formal representations of the contents
of the texts in OWL are then related to this RDF representation. An exciting
application area for this methodology is that of compliance, where the business
processes of organisations (businesses and governments alike) need to be aligned
with respect to some body of regulations.4
We are currently investigating means to represent definitions of concepts in
OWL in such a way that their semantic interpretation mimics the structure and
applicability of the texts. This includes means to scope definitions with respect
to particular parts of a text, as in e.g. deeming provisions, regarding the temporal
validity of a text [14], and concerning its jurisdiction.
One could argue that such requirements indicate the need for knowledge
representation languages specific to law (as in e.g. deontic logics). However, the
legal field is in one respect wholly analogous to the web in that legal information
is used and incorporated in a wide variety of systems, each using the information
in different ways. Also, the whole body of legal information is not maintained by a
single issuer, but rather by a significant number of authorities that each publish,
incorporate, extend, comply with, enforce and implement regulations. Therefore,
the requirements for knowledge representation on the Semantic Web hold for
representation of legal texts as well. Especially as the information exchange
between those parties can benefit enormously from a well designed standard.
We are currently involved in an effort to develop a legal knowledge inter-
change language (LKIF) that allows for the interchange of legal knowledge be-
3
CEN is the European Committee for Standardization, See http://www.metalex.eu,
http://legacy.metalex.eu and http://www.cen.eu
4
This is the subject of the recently granted AGILE project.
tween commercial vendors [3, 5].5 LKIF is an example of a hybrid approach
in that it combines OWL DL (for the representation of concepts) with a rule
formalism.
3 Representation and Reasoning
The LKIF includes a core ontology (LKIF Core) that provides a vocabulary
and a set of standard definitions of concepts common to all legal fields based
on commonsense [6, 10].6 In the development of this ontology, we frequently
encountered the limitations of OWL DL, both with respect to reasoner per-
formance and expressiveness. Especially the extensive use of a combination of
Generic Concept Inclusion axioms (equivalent class statements on existential re-
strictions) and inverse properties turned out to be quite taxing for (in our case)
the Pellet reasoner. As at this time we used the reasoner primarily for debugging
purposes, a single inconsistency in the TBox could cause the reasoner to stall,
making it hard to debug the ontology. Although this problem was remedied by
lifting some of the restrictions on classes, it indicated that real time performance
of reasoners on ontologies that use the full expressiveness of SHOIN (D) can
still be improved.
Structured Objects On the other hand, for many common concepts in law OWL
DL is still too limited in its expressiveness. To be sure, some of these restrictions
are alleviated by the OWL 1.1 proposal – in particular, we applaud the role
inclusions and qualified cardinality restrictions of SROIQ [12]– but for several
common patterns we currently need to resort to rule-based solutions. This is
not desirable for many reasons. To give an example, law mainly governs the ac-
tions of people, and is especially detailed where they interact, as in transactions.
Transactions can be conceptualised in a straightforward manner as two interde-
pendent actions. For instance, a sales transaction contains of the two actions of
buying and selling, each of which involves its own actor, recipient and object.
This pattern is analogous to that of structured objects, as described in [16], and
is essentially diamond shaped, where OWL DL only handles tree (or forest) like
structures. A similar problem occurs when expressing the complementarity of
rights and duties.
Arguably, several of such patterns could be expressed using DL safe rules,
but this solution is in many cases not satisfactory as it requires us to represent
additional information in rules that can be represented using description logics
(cf. [11]). Also, rules only take into account the individuals that were explicitly
asserted in an ABox, and these as such do not necessarily express a valid model
of the theory expressed by the TBox. Furthermore it seems more cognitively in-
tuitive to indicate corresponding identity between relata using pronouns than by
5
LKIF is developed as part of the ESTRELLA project, see http://www.
estrellaproject.org
6
LKIF Core currently contains about 205 named class definitions defined using 114
properties. See http://www.estrellaproject.org/lkif-core
means of variables or property reflexivity. We are currently investigating means
to approximate such structures using role inclusion axioms, and are very much
looking forward to progress in the direction of description graphs to describe
structured objects [16].
Hybrid Approaches Notwithstanding our preference for DL-based concept defi-
nitions, we believe that any useful application of OWL DL in a knowledge based
system will inevitably require interplay with different formalisms. For obvious
reasons, a combination with rule-based solutions is the most likely, not only be-
cause most legacy systems (as e.g. developed by commercial vendors) are based
on this paradigm. We feel that the current discussion on rule-like fragements
of OWL (in the OWL WG), such as Oracle’s OWL-Prime and OWL DLP (cf.
[17, 9])7 is therefore very important. Progress in the specification of combina-
tions between DL and rule-based approaches is closely watched by us and we
are hopeful that in the end, RIF and OWL will get along.
Conditional Classification A relatively uncharted territory in the field of legal
knowledge representation is the combination of regulations with a geospatial ju-
risdiction, as in spatial planning. In recent projects we have experimented with
semantic annotation of maps in combination with legal texts in MetaLex and
the Dutch IMRO standard vocabulary for zoning plans [18, 19]. Spatial plans
essentially enforce a particular type of use in some area expressed as designa-
tions, e.g. ‘housing’, ‘water’, ‘greenery’ etc. However, regulations may be in place
that further refine those designations with additional restrictions. We envisage
applications where users can describe their intended use, run it as query on a
suitably represented body of regulations, and have the areas available for that
use depicted on a map.
However, usage designations are not only enforced exclusively. Because of
intricate interplay between regulations of different authorities (EU directives,
national legislation, provincial and local directives) land use is open to compen-
sation. For instance, a particular lot may have both the designation ‘greenery’
and ‘housing’ but each only to a varying degree. This means that someone ap-
plying for a permit to build a house on that particular lot is bound to some
measure of compensation if the ‘housing’-use of that lot exceeds the designated
maximum. A permit will only be issued if the damage to existing greenery is
compensated in a different area.
We hope that recent developments with respect to probabilistic extensions to
OWL DL along the lines of [15], and currently implemented in Pronto,8 can be
usefully applied to indicate necessity of possibility for compensation of land use.
We furthermore feel that the way in which annotations are used to incorporate
a non-intrusive extension of the OWL DL semantics is a very sensible approach
that deserves further thought.
7
Recently named OWL-R Full and OWL-R DL respectively, see http://www.w3.org/
2007/OWL/wiki/Fragments Proposal
8
See http://pellet.owldl.com/pronto
Explanation Reasoning in law is all about justification: the rational reconstruc-
tion of a case is often the most convincing argument.9 For this reason, a legal
knowledge based system needs to be equipped with elaborate explanation facil-
ities. The current state-of-the-art in explanation and justification of DL entail-
ments as e.g. supported by Pellet ([13]) is therefore a very welcome addition to
standard OWL DL reasoning services.
4 Conclusion
As we discuss above, in our view OWL plays (or at least, should play) a central
role in knowledge representation in the legal domain. We feel that law is an
excellent example of a domain where the combination of semantic web technology
and traditional knowledge representation can make a difference.
In particular, we hope to see progress in the areas dealing with:
Expressivity especially with respect to ‘diamond shaped’ class descriptions.
Performance both on ABox and TBox reasoning with highly expressive on-
tologies.10
Explanation of DL entailments for the purpose of justification and traceability.
Annotation with respect to a transparent connection between the axioms in
an OWL ontology, and structural elements represented as RDF.
Extensions possibility to extend the OWL DL semantics (as used by Pronto)
using a standard extension mechanism.
Versioning of both ontologies and concepts in the ontology.
Interaction with Rules for the purpose of building hybrid knowledge based
systems.
9
Of course this is not always the case, and legal argumentation is often performed in
such a way as to make it appear rational.
10
Wouldn’t we all. . .
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