Abstract
What is the purpose of legal ontologies? This chapter reviews existing legal ontologies, their objectives, characteristics, methodological approaches, to offer an extensive account and analysis of the state-of-the art and trends in legal ontology development.
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- 1.
The A-Hohfeld Language for Legal Analysis by Allen and Saxon (1994, 1995) and Allen (1996) was not included in those early discussions by Valente and Breuker (1994b), Bench-Capon and Visser (1996), Visser and Bench-Capon (1998b) and Valente and Breuker (1999). It was at the time introduced as a representational language (used in the MINT – Multiple INTerpretation – system), based on the fundamental legal concepts – right, privilege, power, immunity, etc. – of Wesley N. Hohfeld.
- 2.
This language was used in the TAXMAN Project to write TAXMAN I and II systems (McCarty 1980, 1989, 1991).
- 3.
Visser and Bench-Capon (1998b) includes LLD representational categories as knowledge categories for ontology comparison, although LLD is not considered by its author as an ontology.
- 4.
In McCarty (1989) only permissions and obligations were defined.
- 5.
- 6.
“The norm based approach aims at developing a semantic database, which takes an ontology model as the conceptual schema. A conceptual schema contains affordances and their dependencies. The schema in principle describes the existence and dependencies of the existence of the affordances, which justifies why it is called an ‘ontology model’ ” (Liu and Sun 2000).
- 7.
Information gathering was as thorough as possible, although we apologize if any relevant publication has been overlooked.
- 8.
A complete norm is a norm that answers five questions: (1) Who is obligated or permitted to do something? (2) Is there an obligation or permission to do something or to leave something undone? (3) What must be done or forborne? (4) Where must something be done or forborne? (5) When must something be done or forborne? The first question is related to the norm subject, the second to the legal modality of the norm and the final three questions relate to the description of the act in different ways (van Kralingen 1997).
- 9.
“Frame-based systems are knowledge representation systems that use frames, a notion originally introduced by Marvin Minsky, as their primary means to represent domain knowledge. A frame is a structure for representing a concept or situation such as ‘living room’ or ‘being in a living room’. Attached to a frame are several kinds of information, for instance, definitional and descriptive information and how to use the frame (…) Collections of such frames are to be organized in frame systems in which the frames are interconnected” (Nebel 1999). Also, some common features in frame-based systems are (1) frames are organized in (tangled) hierarchies, (2) frames are composed out of slots (attributes) from which fillers have to be specified or computed and (3) properties (fillers, etc.) are inherited from superframes to subframes in the hierarchy according to some inheritance strategy (Nebel 1999).
- 10.
modellers: Legal Informatics at Liverpool, Department of Computer Science, University of Liverpool (UK) and Center for Law, Public Administration and Informatization, Tilburg University (The Netherlands). Also, Department of Law and Computer Science of the University of Leiden (ONTOLINGUA specification). Consult: van Kralingen et al. (1993), van Kralingen (1997), Visser and Bench-Capon (1996a, b) and Visser et al. (1997).
- 11.
Moreover, “[t]he ontology contains two separate ontologies, the generic legal ontology and the statute-specific ontology” (Visser and Bench-Capon 1996a). The generic ontology distinguishes: norms, acts and concept descriptions. In the ONTOLINGUA formalization, the authors discussed the trade-off between formalizing a detailed ontology (useful for domain knowledge acquisition) or a more reusable abstract ontology. Visser and Bench-Capon (1996a) opted for the latter specification.
- 12.
The ONTOLINGUA specification is published as an appendix in Visser and Bench-Capon (1996a).
- 13.
- 14.
“Like a knowledge-based system, the legal system executes a number of tasks, for which it uses extensive knowledge. Consequently, each piece of knowledge used by the legal system has a specific role distinguished by the legal system in the operationalization of its functions and tasks” (Valente and Breuker 1996).
- 15.
ON-LINE Valente and Breuker (1995, 1999) used FOLaw to define specialized representations for objects in each of the categories of the ontology (Valente and Breuker 1995, 1999) for information retrieval and problem solving (legal analysis). PROSA, a training system for solving legal cases. When applied to ontology based management of legal information systems FOLaw did not provide appropriate support (Breuker et al. 2005).
- 16.
“Consequently, we propose that core ontologies should attempt to define basic categories of domain knowledge. Categories are meant in an Aristotelian/Kantian sense” (Valente and Breuker 1996).
- 17.
In Valente and Breuker (1994b), the authors distinguished between commanding, derogative (which included permitting) and empowering norms, also inspired by Kelsen (1991).
- 18.
Referred to as terminological in Valente and Breuker (1994b).
- 19.
In Valente and Breuker (1994b), it contains causal responsibility, related to causal knowledge and legal responsibility.
- 20.
The authors considered both reactive and creative knowledge “to have a relatively minor character, insofar as they are not part of the core of legal reasoning” (Valente and Breuker 1994b).
- 21.
“The modelling effort necessary for representing a single regulation (…) is rather large. Furthermore, even if some help is provided by browsers and editing tools, most of this work needs to be done or at least checked by a specialist. It may be necessary to read books or commentaries about the specific regulation being modelled in order to come up with a well-structured model (…) While it is expected that the ontology is able to represent adequately legal knowledge in several types of legislation and legal systems, this issue was not yet tested in practice. Further, in order to model legal knowledge with ON-LINE the user or knowledge engineer must understand the ontology and analyse the legislation in the terms it defines. This may or may not cause problems, depending on the specific knowledge engineer or user in question, but some of the comments received so far point to a mismatch between the way these experts reason and the framework provided by the ontology: the ontology, they say, is not ‘intuitive”’ (Valente 1995).
- 22.
- 23.
The notion of states of affairs and events was inspired by von Wright (1963).
- 24.
“[G]oals underlie reasons for deontic states of affairs. Their functioning is related to that of principles, in that they generate reasons which pleased for or against a particular (deontic) conclusion” (Hage and Verheij 1999).
- 25.
- 26.
“Juristic acts are acts to which the law assigns consequences because of the intention to invoke these consequences by means of the act (…) A juristic act supervenes on another act which legally counts as juristic act. To count as a juristic act, the underlying act must satisfy a number of conditions, such as the condition that the actor is competent to perform the juristic act in question” (Hage and Verheij 1999).
- 27.
Inspired by the work of Kelsen (1991), in a German 1979 edition.
- 28.
CLIME, Computerized Legal Information Management and Explanation,(EC ESPIRIT programme P25.414), project duration 1998–2001. The CLIME partners were: British Maritime Technologies (UK), University of Brighton (UK); Bureau Veritas (France); TXT (Italy), and University of Amsterdam (Netherlands). Relevant publications are: Winkels et al. (1998, 1999, 2000), Boer et al. (2001) and Winkels et al. (2002). Visit also: http://www.lri.jur.uva.nl/~winkels/clime.html, retrieved August 18, 2010.
- 29.
From Bureau Veritas ship classification documentation and International Convention for the Prevention of Pollution from Ships, 1973, as modified by the Protocol of 1978 relating thereto (MARPOL 73/78).
- 30.
The ON-LINE architecture, is used as the basis for the commercial applications developed in the CLIME project, and the representations of the legal knowledge in ON-LINE are based upon FOLaw (Valente and Breuker 1999).
- 31.
The MILE system was partially evaluated in Winkels et al. (2000).
- 32.
The Legal Encoding Tools (LET, java and applet versions), the modelling tool for the ontology was developed parallel to the building of the ontology (Winkels et al. 2002). KDE Project (IST 28678-1999).
- 33.
“Bureau Veritas is the owner of most of the CLIME ontology (because Rinke Hoekstra was employed by Bureau Veritas at the time it was made) it cannot be freely distributed for reuse in other projects. It was reused in KDE because in that project Bureau Veritas was a partner” (Boer et al. 2001).
- 34.
The author gave also an example of its potential application in a collaborative workspace environment (Mommers 2003).
- 35.
modellers: Leibniz Center for Law, The Netherlands. Consult relevant publications: Breuker and Hoekstra (2004b), Breuker (2004) and Breuker et al. (2005).
- 36.
In general, the developers argued that they made a number of different design choices and reuse was not possible: (a) “We do not make the distinction between ‘perdurant’ and ‘endurant’ entities as in Sowa’s ontology and in DOLCE. In principle all concepts are endurants, i.e., all concepts are ‘timeless’; all instances are perdurants (occurrences)”. (b) “Mental concepts are not ‘non-physical’ concepts (DOLCE); the mental world is an analogon of the physical world with an intentional perspective”. (c) “Energy is virtually absent in other ontologies. In LRI-Core it plays an important role in defining mental and physical processes”. (d) “The notion of role covers in LRI-Core most social concepts, where in other ontologies role is rather a relationship (Sowa)” Breuker et al. (2005).
- 37.
Other evaluation methodologies were taken into account. “LRI-Core is written in OWL which enables us to do verification of the specifications (consistency checking). However, the question of how we can assess its validity is also actual, but not easy to resolve and certainly not in a very near future. Up till now, some ‘face-validity’ has been established by comparing it with other core or foundational ontologies – in particular: DOLCE – by arguments. That was thusfar the methodology also used through the centuries by philosophers” (Breuker and Hoekstra 2004b).
- 38.
modellers: Leibniz Center for Law, The Netherlands. For relevant publications see: Breuker et al. (2002a, 2005) and Breuker (2004). The ontology is referred to as CRIME.NL in Breuker et al. (2007).
- 39.
e-COURT European Project IST-2000-28199, project duration 2000–2003.
- 40.
“However, due to the translation problems and a limited budget, this part of the project was never really executed” (Breuker 2004).
- 41.
The EuroWordNet project aimed at interrelate European languages to the lexical/semantic network developed at Princeton University (Miller 1995). “ItalWordNet (IWN) is the Italian section of the EuroWordnet, developed at the Institute for Computational Linguistic of the CNR of Pisa” (Gangemi et al. 2003c).
- 42.
“A synset is a set of one or more uninflected word forms (lemmas) with the same part-of-speech (noun, verb, adjective, and adverb) that can be interchanged in a certain context. For example, action, trial, proceedings, law suit form a noun synset because they can be used to refer to the same concept” (Tiscornia 2007).
- 43.
“Compared to formal ontologies, semantic lexicons, also called lightweight ontologies, are generic and based on a weak abstraction model, since the elements (classes, properties, and individuals) of the ontology depend primarily on the acceptance of existing lexical entries” (Tiscornia 2007).
- 44.
The NormeInRete portal is no longer available at: www.normeinrete.it
- 45.
“DOLCE is essentially a top-level FO, while DOLCE + is an extension of DOLCE containing some modules dedicated to core ontologies of contexts, time, space, plans, etc. The current implementation of DOLCE+ is DOLCE-Lite-Plus” (Gangemi et al. 2005). Visit: http://www.loa-cnr.it/DOLCE.html, retrieved August 18, 2010.
- 46.
“The current version of CLO is based on the DOLCE+ distinction between descriptions (in this domain legal descriptions), which encompass laws, norms, regulations, crime types, etc., and situations (legal facts or cases in this domain), which encompass legal states of affairs, non-legal states of affairs that are relevant to the right, and purely juridical states of affairs” (Gangemi et al. 2003a).
- 47.
“The methodological choices, as well as the exploitation of properties suitable for the legal domain are based upon the approach of legal theory and of the philosophy of law. Legal world is conceived as a representation, or a description of the reality, an ideal view of the behaviour of a social group, according to a system of rules that are commonly accepted and acknowledged” (Gangemi et al. 2003c).
- 48.
The Core Legal Ontology is available at: http://www.loa-cnr.it/ontologies/CLO/CoreLegal.owl, retrieved August 18, 2010.
- 49.
Laboratory of Applied Ontology (Institute for Cognitive Sciences and Technology, ISTC, Rome, Italy), Institute for Theory and Techniques for Legal Information (ITTIG, Florence, Italy), and Istituto di Linguistica Coputazionale (ILC-NRC, Pisa, Italy) took part in the development of CLO and Jur-IWN. See Gangemi et al. (2003a, c, 2005), Sagri et al. (2004), Dini et al. (2005) and Peters (2004).
- 50.
EDC-22161 (2003–2006). The project LOIS had several partners: ITTIG (coordinator), Italy, The Academy of Science of Czech Republic, University of Wien, Austria, University of Leiden, The Netherlands, University of Evora, Portugal, University of Sheffield, UK, Ellis Publishing, The Netherlands, C.E.L.I., Torino, Italy, C.E.S.I. Multimedia, Milano, Italy, GoNetwork, Pisa, Italy.
- 51.
“Within the lexical database of LOIS the Italian JWN is used as the ILI to map the language specific word-nets” (Schweighofer and Liebwald 2007). Two ontologies have been integrated “to a greater or lesser extent” in the LOIS lexical database: the foundational ontology DOLCE2.1-Lite-Plus and the Core Legal Ontology. On one hand, DOLCE2.0-Lite-Plus was already aligned with WordNet 1.6 Noun Synsets, on the other, the Core Legal Ontology helps the structuring of ILI legal concepts (Peters et al. 2007).
- 52.
“However, original hopes were a bit disappointed as the development of the ontology was very time-consuming and difficult. The number of 5,000 descriptors is now considered as too low for a broad legal application. Besides that, more work has to be done on the qualitative structuring of various concepts that will require even to a higher extent lawyers with excellent conceptual knowledge of the domain. Besides these shortcomings, the LOIS thesaurus provides a good basis for next steps to a Comprehensive Legal Ontology” (Schweighofer and Liebwald 2007).
- 53.
“In the LOIS project, various methods for building the lexical ontology were used. The main part has been developed manually (…) At the moment, the LOIS project follows a combination of semi-automatic methods to achieve a sufficient level of quality” (Schweighofer and Liebwald 2007).
- 54.
“In European Community legislation, a unique situation is created regarding legal meaning. All language versions of regulations and directives are deemed to be authentic. Thereby, they are de iure equivalent to each other. Thus, for instance, the meaning of the Dutch version of a European directive is deemed identical to the meaning of the English or Greek version of that directive” (Dini et al. 2005). “Once alignment had been established, legal equivalence was assumed and each set of corresponding terms in different languages were automatically linked to one unique identifier. An additional legal relation implemented_as defines the link between a European legal concept and its implementation in national legislation. As to legal concepts from European legislation, the Identifier acts as the Interlingual Index item” (Tiscornia 2007).
- 55.
Current work focuses on building a tool that assists development, discussion, retrieval, and interchange of CODePs over the Semantic Web, and towards establishing the model-theoretical and operational foundations of CODeP manipulation and reasoning” (Gangemi 2007). For more information regarding conceptual ontology design patterns consult Gangemi (2005) and Blomqvist (2007, 2010) and to access the repository of content ontology design patterns visit: http://wiki.loa-cnr.it or http://www.ontologydesignpatterns.org
- 56.
Financial Fraud Prevention Oriented Information Resources using Ontology Technology (IST 2001-38248), visit http://starlab.vub.ac.be/research/projects/poirot, retrieved August 18, 2010, for more information. The ontologies were modeled by the Department of Applied Linguistics (Centrum voor Vaktaal en Communicatie, Belgium) and STARLab (Vrije Universiteit Brussel, Belgium). For relevant information see: Kerremans et al. (2005a, c), Kerremans and Zhao (2005), and Zhao and Leary (2005b).
- 57.
Ontology requirements identified by the Joseph Bell Centre for Forensic Statistics and Legal Reasoning (University of Edinburgh, UK) are detailed in Kingston et al. (2003): (1) representing national and supranational law regarding online investments and VAT – key requirement that involves the representation of goals as intention, motives and capabilities of actors, plans as actions and sequences of actions, and legal and administrative rules together with definitions and sanctions for fraud in different EU countries –, (2) representing postulates of legal rules – a rule consists of a number of conditions –, (3) representing products or commodities, (4) representing commercial transactions, (5) representing VAT invoices, (6) representing indicators – types of evidence that can be identified which indicate a risk of fraud –, (7) including knowledge of companies and their structure, (8) including knowledge of individuals and their relationships, (9) including knowledge of databases and their communication formats, (10) representing websites, and (11) thesaurus and other support for natural language processing tools.
- 58.
For the user requirements see Kingston et al. (2003).
- 59.
FF POIROT, Introduction to topical ontology of fraud: http://starlab.vub.ac.be/research/projects/poirot/contents/FraudOntology.htm, retrieved August 18, 2010.
- 60.
Main developer: G. Lame (2000, 2001, 2002, 2005) and Lame and Desprès (2005). Nevertheless, the work of updating the legal ontology was “performed by a pluridisciplinary group of researchers gathered for a 1 year work session in Paris: Action Spécifique Ontologies du Droit et Langage Juridique” (Lame and Desprès 2005). Also, the ontology was represented in XML and was, initially, made available at http://ontologie.w3sites.net. It is no longer available at this site. Lists of terms obtained during the knowledge acquisition process may be found in the appendices of Lame (2005).
- 61.
57 codes in Lame (2005), 58 codes in Lame (2002).
- 62.
“[n]otre position d’ingénieur de la connaissance et d’expert du domain nous a permis d’avoir una vision globale sur la tâche que nous avons définie de qualifiation sémantique des relations linguistiques établies entre les termes de la ressource ontologique” (Lame 2002).
- 63.
“Le principe fondamental de ce processus d’évaluation est de mettre la ressource ontoloquique en contexte, c’est-à-dire de l’intégrer dans un système d’aide à la reformulation de requête” Lame (2002).
- 64.
Distributed Multimedia Applications Group: http://dmag.ac.upc.edu
- 65.
See García et al. (2004) regarding this project.
- 66.
IPROnto was modeled by the Departament de Tecnologia, Universitat Pompeu Fabra and the Departament d’Arquitectura de Computadors, Universitat Politécnica de Catalunya. See, for further information, (Delgado et al. 2003; García et al. 2005). IPROnto has \(\mathcal{A}\mathcal{L}\mathcal{C}\mathcal{H}\mathcal{I}\) expressivity, and was developed with the Protégé ontology Editor. It contains 113 classes and 54 properties, and is available at: http://dmag.ac.upc.edu/ontologies/ipronto/index.html, retrieved August 18, 2010.
- 67.
The Copyright Ontology is available from http://rhizomik.net/ontologies/2006/01/copyrightonto.owl, retrieved August 18, 2010. CO was modeled by R. García, see García and Gil (2006, 2007, 2009) and García (2006).
- 68.
http://rhizomik.net/semdrms, retrieved November 10, 2008.
- 69.
Towards Copyright Ontology evaluation, the Protégé editor was used. “This kind of evaluation has been performed during the ontology formalisation phase, which has not been documented in this work as it has been automatically performed by the ontology modelling tools that have been employed” (García 2006).
- 70.
Visit http://dmag.ac.upc.edu/ontologies/odrlonto/index.html and http://dmag.ac.upc.edu/ontologies/relonto/index.html, both retrieved August 18, 2010, for more information and downloads.
- 71.
CCFORM Thematic Network project, IST-2001-34908, 5th framework. For more information regarding this project consult: http://www.fedma.org/cc-form.71634.en.html, retrieved August 18, 2010.
- 72.
“Ontology development and maintenance is not a single-person effort. Adequate ontologies are normally built, reviewed, and maintained by several types of knowledge experts. For example, our experience in building a ‘Customer Complain Ontology’, reported in chap. 7 [in Jarrar (2005)], shows that some parts of the ontology - specifically those that capture knowledge about customer regulations -should be built and evaluated by lawyers” (Jarrar 2005).
- 73.
The DOGMAModeler tool was used towards formalization in ORM, the conceptual graphical modelling notation used by DOGMAModeler. See Jarrar (2007) for further information on ORM. Context (in the CContology the “customer complaint context”), terms and their glosses (220 terms) and lexons (“represent taxonomies of complaint problems, complaint resolutions, etc.) are the three representation units.
- 74.
CContology was modeled by STARLab (Vrije Universiteit Brussel). For relevant publications see: Jarrar et al. (2003) and Jarrar (2005, 2008). Initially the CContology was implemented in the CC-form demo portal, although “[t]his portal (which was not an official deliverable in the project) is no longer available due to copy-right issues” (Jarrar 2008). Nevertheless, the CContology may be downloaded at: http://www.jarrar.info/CContology, retrieved August 18, 2010.
- 75.
The BEST project is funded by the Netherlands Organisation for Scientific Research and is part of the ToKeN research programme (01-02-2005/01-07-2010, 634.000.436B). Visit: http://www.best-project.nl for further details.
- 76.
However, in the description of the Ontology of Dutch Tort Law by van Laarschot (2005), more reasoning capabilities were established: [i]n this Ontology of Dutch Tort law “all possible case descriptions in tort law can be expressed plus it must be able when a given one of these case descriptions to determine (after reasoning) which party is liable, on what grounds a party is liable and the corresponding article numbers”. Therefore, “The role of the BEST-ontology is reasoning and problem solving” (van Laarschot 2005).
- 77.
“Since I am a layman in the field of law myself, the first thing to do is knowledge acquisition. I try to achieve that by: reading a recommended book about the unlawful act and the sections in Dutch law concerning tort law, doing a think aloud session with a Master student in law and getting a lot of help and advice from a PhD student of Law, who’s main task is to analyze the domain of tort law. Together, we try to understand the domain of tort law as best as possible. Then a hierarchical structure will be made of the domain of tort law. This hierarchical structure will only contain article numbers. A domain in law seldom stands alone; it will refer to definitions or articles of another domain of law. These also have to be modelled in the hierarchical structure. Then we will use the hierarchical structure to build the legal or expert’s part of the ontology. For the common sense or layman’s part of the ontology a number of well-chosen case descriptions will be extracted from www.rechtspraak.nl. These will give a good idea of how to express a case in layman terms and the problems that arise in transforming them into legally valid statements, which can be used in reasoning” (van Laarschot 2005).
- 78.
The BEST-User ontology is available from http://www.best-project.nl/ontology/BEST.daml, retrieved August 18, 2010.
- 79.
The description of the system is as follows: “[f]irst a case description is entered by the layman user. An ontology with layman concepts is used to structure the input and guides the user by entering relevant aspects of the case at hand. The laymen ontology is mapped to a second, legal ontology that is used for indexing case law” (Uijttenbroek et al. 2008).
- 80.
More current information regarding the BEST project developments may be found in Uijttenbroek et al. (2007a, b, 2008) and Hoekstra (2009a). Ontology visualizations are provided with TopBraid Composer.
- 81.
BestPortal: http://sembweb.cs.vu.nl/best-portal
- 82.
BestMap: http://www.best-project.nl/owl/bestmap.owl, both retrieved August 18, 2010.
- 83.
Estrella project (IST-2004-027665), http://www.estrellaproject.org. See Boer et al. (2007) for a specification of the Legal Knowledge Interchange Format.
- 84.
Also MetaLex XML is, as LKIF, a knowledge interchange format of sources of law and references to sources of law. It has been based from best practices from amongst other versions of MetaLex schema, Akoma Ntoso schema and Norme in Rete schema, and it has been inspired also from the experiences of LexDania, CHLexML, FORMEX, and R4eGov. Earlier descriptions of MetaLex can be found in Boer et al. (2002) and Winkels et al. (2003). The European Committee for Standardization has adopted the latest proposal as a prenorm and a workshop is open to participation (Boer et al. 2008). Latest proposals can be viewed at http://www.metalex.eu. Description of the interfacing between MetaLex and LKIF may be consulted at Boer et al. (2008).
- 85.
Due to its knowledge interchange purpose “[i]t is dependent on the (potential) users what kind of vocabulary is aimed at” (Hoekstra et al. 2007).
- 86.
The lists of concepts can be found in the Appendix of Breuker et al. (2007). These “terms formed the basis for the identification of clusters and the development of the LKIF Core ontology” (Hoekstra et al. 2007). These clusters were: Expression, Norm, Process, Action, Role, Place, Time, and Mereology, which were further specified following a middle-out strategy. A final total of 14 modules was obtained after discussion and reuse (Legal Role, Legal Action, Rules, Time Modification, Core and Top – based on LRI-Core – were added). They are integrated in the LKIF-Core ontology module, which acts as entry point (Breuker et al. 2007).
- 87.
EU Directive 2006/126/EC of the European Parliament and of the Council of 20 December 2006 on driving licences (OJ L403, 30/12/06).
- 88.
LKIF-Core version 1.0.2 had \(\mathcal{S}\mathcal{H}\mathcal{I}\mathcal{N}(\mathcal{D})\) expressivity, and used Protégé 3.2/4.0 and TopBraid Composer (Hoekstra et al. 2007) as ontology editing tools. Moreover, OWL2 expressiveness was also studied.
- 89.
The LKIF Core Ontology and relevant documentation are available from: http://www.estrellaproject.org/lkif-core, retrieved August 18, 2010. See also Hoekstra et al. (2007), Breuker et al. (2007), Hoekstra (2009b), Hoekstra et al. (2009). A Protégé 4 plugin for legal assessment based in LKIF-Core is being developed (Hoekstra et al. 2009).
- 90.
This ontology is available at: http://wyner.info/research/ontologies/LegalCaseOntology_v9.owl, retrieved August 18, 2010.
- 91.
Popov v. Hayashi, 2002 WL 31833731 (Ca. Sup. Ct. 2002).
- 92.
Previous work on the ontology for legal case-based reasoning (LCBR Ontology) and other related work may be found at Wyner (2007), Wyner and Bench-Capon (2007) and Wyner (2008, 2009). This LCBR Ontology was formalized in OWL-Lite using Protégé (the ontology was tested with the reasoner Pellet 1.3). “As the ontology is web-based and provided in the context of an open-source European Project (ESTRELLA), our object is to allow public use and development of the ontology” (Wyner 2007).
- 93.
Purpose: interoperability (int.), systems engineering (SE), knowledge acquisition (KA), reuse (R), indexing and search (IS), reasoning and problem solving (RPS), theoretical investigation (TI), and communication (com.). Subject-matter: static (S) and dynamic (D).
- 94.
Many contributions refer nowadays to the use of legal ontologies, however there are few specific details about their development processes. Some of these are Costa et al. (1999), Peek (1997), Singh (1999), Desprès and Delforge (2000), Zeleznikow and Stranieri (2001), Boella et al. (2001), Jouve et al. (2003), Ryan et al. (2003), Shaheed et al. (2005), Kayed (2005), Boella et al. (2005), Yan et al. (2006), Abramowicz et al. (2007), Saravanan et al. (2007), Gray (2007), Winkels et al. (2007), da Rosa Alves et al. (2007), Gray et al. (2007), Loukis (2007), Schweighofer and Liebwald (2007), Adams (2008), Khadraoui et al. (2008), Liebwald (2009), Rahmouni et al. (2009), Pazienza et al. (2009), Sonntag (2009), Stadlhofer et al. (2009), Charalabidis and Metaxiotis (2009), Zurek and Kruk (2009), Kharbili and Stolarski (2009), Barbagallo et al. (2010) and Luz Clara et al. (2010). Finally, other contributions such as the Multi-lingual and multi-jurisdictional RDF Dictionary for the legal world by M. Muller (see Muller (2001), the Dictionary Workgroup at LegalXML by J. McClure (see also McClure (2007) and the European Legal RDF Dictionary are relevant for this research. (Visit: http://rdfdictionary.sourceforge.net, http://www.legalxml.org, and http://www.lexml.de/eu/index.htm). Further, see some legal database providers which offer semantically-enhanced search in their search engines, although few information is available with regards to the development or technical details: LawMoose (MooseBoost: http://www.lawmoose.com/index.cfm?HomeCommunity=WorldLaw, retrieved August 18, 2010; LexisNexis Total Patent for patent research: http://www.lexisnexis.com/media/press-release.aspx?id=125674399689744, retrieved August 18, 2010; La Ley Digital con expansión semántica (sinónimos): http://www.atencionclientes.com/FAQ/LALEY/FAQ_Buscar_Sinonimos.htm, retrieved August 18, 2010.
- 95.
E-Power Project (Program for an Ontology-based Working Environment for Rules and Regulations) was partially funded by EC as IST Project 2000-28125.
- 96.
The list includes this ontology because, although it is informal, it provides a basis for the formalization of intellectual property rights, in a similar but more theoretical way as IPROnto, CO, or the Ontology of Licenses. Moreover, Smith (2003) also indicates that “the lessons drawn from information systems ontology can support the efforts of those philosophers who have concerned themselves not only with the development of ontological theories, but also – in a field sometimes called ’applied ontology’ (such as does Koepsell (2000)) – with the application of such theories in domains such as law, or commerce, or medicine.”
- 97.
e-Court European Project (IST-2000-28199). “The e-COURT project is a European project 2 that aims at developing an integrated system for the acquisition of audio/video depositions within courtrooms, the archiving of legal documents, information retrieval and synchronized audio/video/text consultation. The University of Amsterdam is responsible for the role of (legal) ontologies in the e-COURT system” (Breuker et al. 2002a). Partners: Project Automation S.p.A. (Italy), Ministero della Giustizia (Italy), SchlumbergerSema (Spain), CRYPTOMAThiC A/S (Denmark), INTRASOFT International S.A. (Luxembourg), Consiglio Nazionale delle Ricerche (Italy), Université Paul Sabatier (Toulouse 3, France), Universiteit van Amsterdam (The Netherlands), Ministry Of Justice (Poland).
- 98.
See, for example, Asaro and Nissan (2001) on the Daedalus Project.
- 99.
For example, “the UCLC Ontology [Upper Level Core Contract Ontology] defines the generic concepts and semantic relationships between contracts, its participants the actors, the roles they undertake within the scope of the contract, the object for which they undertake the contract. Consideration, the commitments they make, obligations, the expected business actions that will fulfill the obligations, performance” (Kabilan et al. 2005).
- 100.
“We tested our conceptual models on novices to software design principles including legal experts and business strategy and policy makers. Proof-of-concept implementation for transformation of UML conceptual models into machine-understandable ontology formats like RDFS and DAML have been carried out successfully” (Kabilan 2003).
- 101.
The ontology is described in http://dip.semanticweb.org/documents/D9.3Annex-eGovermentontologyOCML.pdf, retrieved August 18, 2010. Recent development are described in Gugliotta et al. (2008). Information on the Operational Conceptual Modelling Language (OCML) language may be found at http://technologies.kmi.open.ac.uk/ocml/, retrieved August 18, 2010.
- 102.
A example (demonstration) may be found at: http://pi.informatik.uni-siegen.de/whois/BDSG_Ontology_Demo, retrieved August 18, 2010.
- 103.
The REIMDOC Spanish Project aims at developing “tools that allow the legal document to be modelled in electronic support and its semantic retrieval to facilitate the government-citizen document transaction” Gómez-Pérez et al. (2005). Visit: http://reimdoc.atosorigin.es
- 104.
The EGODO ontology (based on the EGO Ontology Model) was not listed in the original 11 Real-estate Transaction Ontologies. See (Ortiz-Rodríguez 2007) for a detailed account of the Documentation Ontology.
- 105.
The PATExpert project: http://www.patexpert.org. Ontologies are available at: http://mklab.iti.gr/project/patexpert, retrieved August 18, 2010.
- 106.
Developers: The Law Department, European University Institute and CIRSFID, University of Bologna, Italy. See Sartor (2006) and Rubino et al. (2006, 2007).
- 107.
More information on the Legal Taxonomy Syllabus may be found at: http://www.eulawtaxonomy.org, retrieved August 18, 2010.
- 108.
RIAM Program 2005–2008 (http://www.medialex-digitalrights.org). Developers: Université de Technologie de Compiègne (Centre de Recherche de Royallieu), CERSA-CNRS (University Paris 2) and Direction de la Recherche et de l’Expérimentation (Institut National de l’Audiovisuel). Previous work may be found in de Rosnay (2003).
- 109.
DALOS (DrAfting Legislation with Ontology-bases Support) e-Participation project (01-01-2007/30-04-2008) website: http://www.dalosproject.eu
- 110.
The separate ontologies Legal Issue Ontology (hierarchy of legal issues within each category of legal statutes) and Legal Role Ontology (role duties and rights in legal cases) are not further described in Shen et al. (2008). Developers: Department of Computer Systems, Faculty of Information Technology, University of Technology, Sydney (Australia). The Legal Case Ontology development is inspired by the results of SALOMON (Moens et al. 1997) and JUSTICE (Osborn and Sterling 1999b), which “proposed a data model using DTD (Document Type Definition) in their legal case knowledge base. The concepts such as jurisdiction, judge, parties and facts are extracted from case head-notes or abstract to form a case descriptor. The case knowledge base is composed of marked up XML or SGML instances based on the proposed DTD. However, their data models that are built on the DTD can only achieve limited semantics annotation due to the fact that XML only provides a surface syntax for structured documents, but imposes no semantic constraints on the meaning of these documents” (Shen et al. 2008). A Legal Case Ontology (LegalCase.dtd) was also developed for the JUSTICE system, which consisted of 76 concepts covering possible concepts in legal case headnotes (including facts, law and order) (Osborn and Sterling 1999a, b).
- 111.
ALIS, Automated Legal Intelligent System, Project (IST-IST-2004-2.4.9), and is a STREP Project funded by the European Commission under the 6th Framework. The Consortium is coordinated by ORT France and the project partners are: Imperial College London, Sineura SPA, Atos Origin SA, CBKE (Research Centre for Legal and Economical Aspects of Electronic Communication), SIVECO Romania SA, Exalead SA, Technical University Darmstadt, Alma Consulting Group, CIRSFID (University of Bologna), and the Gesica Paris Friedland law firm. For more information, visit: http://www.alisproject.com
- 112.
This ontology is available at: http://www.man.poznan.pl/~jolac/MinimalModel/MinimalModel.owl, retrieved August 18, 2010.
- 113.
The latest release of the ontology may be found at http://purl.org/derecho/vocabulario#, retrieved August 18, 2010. More information on the Kelsen Project may be found at http://derecho-internet.org/proyectos/kelsen, retrieved August 18, 2010.
- 114.
More information may be found at: http://idi.fundacionctic.org/classifications_endpoint/eurovoc, retrieved August 18, 2010. Also, the description of the semantically enhanced EuroVoc may be found in http://eurovoc.europa.eu/drupal/?q=es/ontology, retrieved August 18, 2010.
- 115.
- 116.
At least 22 of the above-mentioned ontologies have been developed, at some point, with the use of Protégé: CLIME Ont., LRI-Core, CLO, IPROnto, Copyright Ont., LKIF-Core, OPJK, e-Court Ont., Multi Tier Contract Ont., SIAP Legislative Ont., Ontolegis/Ontojuris, Ontology of Fundamental Legal Concepts, US UCC, Legal Case Ont., Oral Hearings Ont., ALIS IP ont., Legal Case Repository of Ont., legLOPD, Minimal Model of Economic Crimes ont., Mediation Core Ont., and NEURONA ontologies. Other tools referred to are: OilEd (the initial BEST ont.), TopBraid Composer (LKIF-Core, ALIS IP ont., BEST ont.), DODDLE (Legal On. with General ont.), WebODE (Real Estate Transactions Ont., or OntoStudio (BDSG ont.)).
- 117.
The survey included 34 projects which involved ontology modelling. “(…) the respondents are representative for the community of users and developers of semantic technologies. They were IT practitioners, researchers and experts from various disciplines, affiliated to industry or academia, who were involved in the last 3–4 years in ontology building projects in areas such as skill management, human resources, medical information systems, legal information systems, multimedia, Web services, and digital libraries” (Paslaru and Tempich 2006).
- 118.
Paslaru and Tempich (2006) discovered from the interviews that 80% of the projects did not follow a particular ontology engineering methodology.
- 119.
The legal system as system, the concept of norm, together with the contributions from deontic logic have influenced these approaches. Hart inspired FBO, FOLaw, and the Knowledge-based Model of Law. Kelsen inspired FBO, FOLaw, the Ontology of Law as Dynamic Interconnected System of States of Affairs, and the Knowledge-based Model of Law. Other relevant and cited contributors were the logicist G.H. von Wright (FBO and the Ontology of Law as Dynamic Interconnected System of States of Affairs), and the Scandinavian realist A. Ross (FBO and the Ontology of Law as Dynamic Interconnected System of States of Affairs), within others.
- 120.
Whilst, within the consulted publications, it was not explicitly stated that legal experts had participated in the development of Jur-IWN, CLO and Consumer Protection Ontology, legal experts did participate in the development of the LOIS database, and, in general, several legal experts were employed by the ITTIG research centre.
- 121.
“Another top-down way to elaborate an ontology can be to get together some experts of the domain and ask them to agree on a unique point of view on their specialities, this unique point of view being the basis of an ontology. The main difficulty is then the time; it is long for experts to agree. The second way to build an ontology is a bottom-up method. This method consists on extracting from appropriate documents all the elements needed to compose an ontology” (Lame 2001).
- 122.
For the developers of LKIF-Core, the view of the citizens is taken into account because this group has to “understand legal sources and legal procedures to plan their activities” (Breuker et al. 2007). “Although these populations have different uses and views on legal concepts, we assumed that the different perspectives involved are not conflicting: the legal system –the ‘professionals’ – and society – the citizens are in permanent interaction. The results of this interaction are not limited to the participants in courtrooms but are a major subject in news reporting. The views of legal scholars are very important because they develop abstract terms that may articulate a legal core ontology” (Breuker et al. 2007). In this case, the knowledge acquisition process was based on asking each partner (either ‘expert citizen’ or ‘legal expert’) to supply their ‘top-20’ legal concepts, together with a combination of terms collected from jurisprudence and legal text-books (without specifying the jurisdiction or legal domain).
- 123.
Either towards knowledge elicitation or as documentation supervision, advice, validation or evaluation.
- 124.
“Perhaps it should not be necessary to include a section which describes some of the fundamental problems of building expert systems in law, yet it is clear that there are a number of systems which have been built or are being built by people whose primary interest and training is in computer science and who fundamentally misunderstand the nature of law and legal reasoning. It is particularly strange that law should suffer in this way, since the standard texts on building expert systems emphasize the importance of capturing the knowledge of an expert in the domain area. Yet, people who would not dream of beginning construction of a medical expert system without the firm support of a medical physician will happily go to work on a legal system. The reason, of course, lies in the widespread misconception that law is a simple system of rules and that legal inference consists of a simple deductive application of these rules. Since most expert systems are rule based, the translation job seems easy” (Greenleaf et al. 1987).
- 125.
“[A] system which fails to include this knowledge is unlikely to be very ‘expert”’ (Greenleaf et al. 1987).
- 126.
“Sergot and others made much of the point that most of the BNA was translated by a student, without any expert legal assistance. Their constant references to the use of non-legal expertise is seen by them to be unproblematic, and to be a virtue rather than a vice. They assume that an expert will only contribute to the ‘accuracy’ of the knowledge base and fail to appreciate that an expert may have a great many useful things to say about how one goes about the process of interpretation including the way in which the knowledge is structured” (Moles 1992).
- 127.
See, regarding the interest for legal theory: Valente and Breuker (1994a, c), Bench-Capon (1994), Brouwer (1994), Gordon (1994), Greinke (1994), den Haan and Winkels (1994) and Wahlgren (1994). Most of these contributions conform the proceedings of the JURIX’94 conference dedicated to ‘The relation with legal theory’.
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Casellas, N. (2011). Legal Ontologies. In: Legal Ontology Engineering. Law, Governance and Technology Series, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1497-7_4
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