Legal Ontology Modelling: Some Current Trends in Legal Knowledge Representation

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Legal Ontology Modelling
:

Some Current Trends in
Legal Knowledge Representation


Núria Casellas


This paper explores some of the existing boundaries between Law, Knowledge Management, and
Artificial Intelligence. Traditionally, the most important meeting p
oints of these, not so distant, areas of
study have been legal information search and retrieval, legal knowledge representation and management,
legal reasoning, argumentation and legal expert and knowledge
-
based systems (KBS) design.
Since the
first ideas
of computerization of the law on the late 1940s early 1950s (American School of Jurimetrics)
and the appearance of the first legal information systems in the 1950s and the first legal expert systems in
the 1970s, paraphrasing

Bing (1984)
, computers have no
w been used in legal information systems for
more than 40 years.
1


The interest from the Artificial Intelligence (AI) and Knowledge Management (KM) community for the
formalization of legal information and knowledge for computer processing is not thus recen
t. The legal
domain was of interest for AI since its first steps.

The design of information retrieval systems and
problem solving and reasoning programs has been central to Artificial Intelligence since its
initial

efforts
and with them it appeared the nee
d to represent human knowledge in a machine
-
readable form. Thus,
knowledge

representation (semantic information processing) became a major sub
-
domain of AI research.
In a significant panel of the IJCAI 1985 conference entitled

AI and Legal Reasoning
, the p
anel discussed
the characteristics of the legal domain and its main points of interest for th
e application of AI techniques
(Rissland, 1985)
.


From this previous experience, during the 1990s, the knowledge management discipline took off with the
widespread

of information and communication technologies and the growing interest in knowledge,
procedural and conceptual, as an important asset of government and commercial organizations (van
Engers, 2001).


For 30 years now, different artificial intelligence and k
nowledge engineering

techniques have been
applied to the legal domain to construct expert and other knowledge
-
based systems (KBS).

Nevertheless,
claims such as

searching a large database is an important and tim
e
-
consuming part of legal work”

(Hafner, 1980
), “
our programming research was initiated by the needs of lawyers for high speed comput
er
assistance in their studies”
(Kehl et al., 1961)
or “
the large volume of legal information and the
enormous

effort required to manually abstract and index cases for
every domain of law call for a syst
em which
automates the process”

(Gelbart et al., 1991)
, which drove the development of legal expert systems during
the 80s and 90s, have not yet been left behind.


Similar claims may be found nowadays together with others

regarding the challenge posed by the
complexity of dealing with multi
-
lingual legislative corpuses (e.g., European Legislation (Ajani et al.,
2007)), the need for laymen to access legal information on
-
line either because of open e
-
Government
policies or t
o gain legal knowledge towards choosing alternative dispute resolution methods (Uijttenbroek
et al., 2007a), within others.


Therefore, with the increasing need for legal information and content management caused by the growing
amount of unstructured (or
poorly structured) legal data managed by legal publishing companies, law
firms and public administrations or the increasing amount of legal information directly available on the
World Wide Web (WWW or Web), there is an urgent need to construct conceptual s
tructures for
knowledge representation to share and manage intelligently all this information, whilst making human
-
machine communication and
understanding possible:
legal ontologies
.


This
paper

brings together
Law, Artificial Intelligence and Knowledge Ma
nagement, for the analysis of
current
ontology
-
based representation
s

of conceptual legal knowledge.

Legal ontologies are a popular
field of research,

its development and quantity increasing over the

years

(see, for example,

Casanovas et
al., 2008 and Breuk
er et al., 2009)
. Most of the initial ontologies were directed

towards theoretical



*

Institute of Law and Technolog
y (IDT
-
UAB),
Universitat Autònoma de Barcelona
,
08193, Bellaterra (Barcelona),
Spain. E
-
mail: nuria.casellas@uab.es (http://idt.uab.es).

1

See Bing (1984) for an extensive introduction to legal information retrieval systems until the 1980s,

and Bench
-
Capon

(1990) for an account of legal knowledge based systems until the 1990s.

investigations or knowledge acquisition

and reuse, and were built mainly at the

core level, while latter
ontologies are built with

particular applications in mind, especiall
y towards

semantic indexing, search and
retrieval.


Acknowledgements:

(i) ONTOMEDIA. TSI
-
020501
-
2008
-
131; (ii) INTEGRA Programa INGENIO 2010
-

CEN2008
-
1018;
(iii) NEURONA TSI
-
020100
-
2008
-
134. Plan AVANZA I+D; (iv) ONTOMEDIA CSO
-
2008
-
05536
-
SOCI.


Reference
s:


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AI and Legal R
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