Ontologías jurídicas y la segunda generación de Servicios Web
Jornadas sobre Derecho y Tecnología
Zaragoza 4-5 Mayo 2009
Pompeu Casanovas
Índice• El futuro de Internet (Web 3.0)• Obstáculos al desarrollo de Internet• Una web de servicios (2ª generación de Web
Semántica)• Ontologías jurídicas para servcios Web• Algunas ideas: (i) ITLaw + ITLawyers, (ii) derecho
relacional, (iii) justicia relacional, (iv) estrategias híbridas en la construcción de ontologías (v) algunos retos (multimedia, e.g. o la adquisición de conocimiento)
WEB
• Web 1.0: Internet• Web 2.0: Expresividad (Tags): Flikr,
YouTube, Wikipedia, Facebook…• Web 3.0: Expresividad + Semántica (web de
objetos vinculados –”linkados” – y no de páginas Web)
Internet de Services
A multitude of connected IT services, which are offered, bought, sold, used, repurposed, and composed
by a worldwide network of service providers, consumers, aggregators,
and brokers
- resulting in -
a new way of offering, using, and organising IT supported
functionality.
Fuente: John Domingue (2008)
GOVERNMENTeGovernment, eEnergy,eHealth, Public Security
BUSINESS/SCIENCECluster/SME, new Service and
Business Models
CITIZEN/CONSUMER/EMPLOYEE
“Digital Lifestyle”, New Media, Communities, Collaboration
INTERNETOF THINGS
MULTIMEDIACONTENT
SERVICE-ORIENTEDSOFTWARE
APPLICATIONS
The Big Picture
Adapted from Prof. Wahlster, 2007
Modelo democrático
• Los autores han subrayado que la Web 2.0 implica un modelo democrático de participación e interacción. La gente puede compartir sus ideas y cooperar en una construcción en común (Motta, 2006) Enriquecer con semántica el proceso parece una consecuencia natural desde la perspectiva de la WS. Pero… no es tan fácil!
(1) Obstáculos: falta de conocimiento
• “Because no systemic measurements activities exist for collecting rigorous empirical Internet data, in many ways, we don’t really know what the Internet actually is. Thus, we don’t know the total amounts and patterns of data traffic, the Internet’s growth rate, the extent and locations of congestion, patterns and distribution of ISP interconnectivity, and many other things that are critical if we’re to understand what actually works in the Internet. These data are hidden because ISPs consider such information proprietary and worry that competitors could use it to steal customers or otherwise harm their business. The information might not even be collected because no economic incentive exists to do so, nor do any regulations require this collection” (Claffy et al. 2007).
(2) Efectos sociales indeseados
(3) Actuación jurídica oclusiva!
SEKT-D12.5.5
Porcentajes día/abogados Poblet, Benjamins, Casanovas Fuente: SEKT SEKT D12.5.5
Uso creciente de Internet I
• En 2008, un40% de los despachos iindicaban un gasto de aprox. $ 8.000-$ 17.000 por. 72% de los encuestados decían que accedían electrónicamente a los juzgados, un cecimiento de más del 55% sobre la encuesta del 2007.
Source: ABA-2008 Tech Survey Report
Uso creciente de Internet II
• E-MAIL: e-mail attachments (92%, sobre el 80% en 2007)
• MOBILIDAD: Casi todos los abogados indican que pueden consultar el e-mail fuera del despacho (98%) vía Smartphone/BlackBerry (59%).
Fuente: ABA 2008 Tech Survey Report
(4) Problemas Técnicos
• “Why has the Semantic Web had so little effect on search services? And, even more worrying, why does it have such little presence in the agendas of fundamental information-retrieval research programs, search engine designers, and search startups? What’s stopping researchers in the IR and Semantic Web communities from moving more bravely in the direction of promised next-generation search engines? (Baeza-Yates et al. Yahoo, 2008)”
Respuesta
• “We put forward three possible reasons:• First, this integration is an extremely hard
scientific problem;• Second, the Web imposes hard scalability and
performance restrictions;• Third, there’s a cultural divide between the
Semantic Web and Information Retrieval disciplines”
Niveles de lenguajes de la WS Berners-Lee Cody Burleson (2007).
Web Semántica
Qué es una ontología? (Breuker)
• `formal specification of conceptualization’ (Gruber 94)
• “An ontology defines the terms used to describe and represent an area of knowledge” (Jeff Heflin, OWL-Use cases,
http://www.w3.org/TR/2004/REC-webont-req-20040210/ ) •
– terms: concept (= meaning)– knowledge representation: from informal (e.g text) to
machine interpretable (via formalization)– ontology: `what is’ ≈ what we know
Ontologías jurídicas (hasta el 2002)• LLD [Language for Legal Discourse, L.T. McCarty, 1989]:
– Atomic formula, Rules and Modalities.• NOR [Norma, R.K. Stamper, 1991, 1996]:
– Agents Behavioral invariants, Realizations.• LFU [Functional Ontology for Law, R.W. van Kranlinger; P.R.S. Visser, 1995]:
– Normative Knowledge, World knowledge, Responsibility knowledge, Reactive knowledge and Creative knowledge.
• FBO [Frame-Based Ontology of Law, A. Valente, 1995]: – Norms, Acts and Concepts Descriptions].
• LRI-Core Legal Ontology [J. Breuker et al., 2002]: – Objects, Processes, Physical entities, Mental entities, Agents, Communicative
Acts.• IKF-IF-LEX Ontology for Norm Comparaison [A. Gangemi et al., 2001]:
– Agents, Institutive Norms, Instrumental provisions; Regulative norms; Open-textured legal notions, Norm dynamics.
Trojahn, Quaresma and Vieira Table of Legal Ontologies (2008)
Ontology or Project Application Type Role Character Construction
Language
McCarty’s Language of Legal Discourse
General language for expressing legal knowledge
Knowledge representation, highly structured
Understand a domain General Manual English
Valente & Breuker’s Functional Ontology of Law
General architecture for legal problem solving
Knowledge base in Ontolingua, highly structured
Understand a domain, reasoning and problem solving
General Manual English
Van Kralingen & Visser’s Frame Ontology
General language for expressing legal knowledge, legal KBSs
Knowledge representation, moderately structured (also as a knowledge base in Ontolingua)
Understand a domain General Manual English
Mommer’s Knowledge-based Model of Law
General language for expressing legal knowledge
Knowledge base in English very highly structured
Understand a domain General Manual English
Breuker & Hoekstra’s LRI-Core Ontology
Support knowledge acquisition for legal domain ontologies
Knowledge base inDAML+OIL/RDF using Protege (converted into OWL)
Understand a domain General Manual English
Hoekstra & Breuker’s LKIF-Core Ontology
Support knowledge acquisition for legal domain ontologies
Knowledge base in OWL, highly structured
Understand a domain General Manual English
Gangemi, Sagri & Tiscornia’s JurWordNet
Extension to the legal domain of WordNet
Lexical Knowledge base in DOLCE (DAML), lightly structured
Organize and structure information
General Manual Italian
Benjamins, Casanovas et al. Ontologiy of Professional Legal Knowledge (OPLK)
Intelligent FAQ system (information retrieval) for judges (Iuriservice)
RDF.. Knowledge base in Protégé, highly structured (converted in OWL)
Semantic indexing and search
Domain Semi-automa
ted
Spanish
Casellas, N. et al. Ontology of Professional Judicial Knowledge (OPJK)
i-FAQ for judges (Iuriservice, second version)
Last version in OWL. Knowledge base in Protégé, highly structured
Semantic indexing and search
Domain Manual Spanish
Lame’s ontologies of French Codes
Legal information retrieval
NLP oriented (lexical), knowledge base, lexical, lightly structured
Semantic indexing and search
Domain Automated
French
Leary, Vanderverghe & Zeleznikow’s Financial Fraud Ontology
Ontology for representing financial fraud cases
Knowledge base (schema) in UML, lightly structured
Semantic indexing and search
Domain Manual English
Asaro et al.’s Italian Crime Ontology
Schema for representing crimes in Italian law
Knowledge base (schema) in UML, lightly structured
Organize and structure information
Domain Manual Italian
Boer, Hoekstra & Winkel’s CLIME Ontology
Legal advice system for maritime law
Knowledge base in Protégé and RDF, moderately structured
Reasoning and problem solving
Domain Manual English
Lehman, Breuker & Brouwer’s Legal Causation Ontology
Representation of causality in the legal domain
Knowledge base lightly structured
Understand a domain Domain Manual English
Delgado et al’s IPROnto (Intellectual Property Rights Ontology)
Integrating XML DTDs and Schemas that define Rights Expression Languages and Rights Data Dictionaries
Knowledge base: first version in DAML+OIL (2001), current version OWL (2008)
Interoperability between Digital Rights Management (DRM) systems
Domain Manual English
Teodoro, Binefa et al. e-Sentencias (Procedural Ontology for Multimedia in Courts)
Ontology for Representing Procedural Stages of Spanish Civil Hearings
RDF. Procedural Knowledge within Spanish Civil Hearings (typology)
Diarization and Content Classification of the Official Video Recordings (image and audio)
Domain Manual Spanish
J. Saias, P. Quaresma, Portuguese Attorney Office Ontology
Ontology to semantically enriching legal texts
OWL and logic programming (ISCO and EVOLP)
Organize and structure information
Domain Automated
Portuguese
M.Klein, E.Uijttenbroek, A. Lodder, Laymen Ontology
Ontology to represent laymen knowledge on liability cases
OWL and NLP. Knowledge base in laymen natural language
Understand a domain (tort law) and interoperability between NL and legal concepts
Domain Semi-automa
ted
Dutch
J. Breuker, A. Elhag’sCrime.NL
Ontology of Dutch Criminal Law
OKBC Main structure of (Dutch) criminal law; for comparing European CL
Domain/General Manual Dutch/English
S Despres, S. SzulzmanMicro-ontology
Ontology to represent concepts in European Directives
OWL and NLP (TERMINAE method)
Understand a domain Domain Semi-automa
ted
French/English
UCC OntologyJ. Shaheed, A. Yip, J. Cunningham
Ontology to represent top-level concepts (e.g. ownership)
NML Top-level ontology based on NM
Organize and structure information
Domain (top -level)
Manual English
E.Schweighofer, D. Liebwald’sCLO (Comprehensive Legal Ontology)
Ontology for information management
Some frame representation General Manual with
support of legal
core ontologi
es
English?
E. Melz & A. Valente’s IRC ontology
Ontology of Internal Revenue Code (USA)
OWL Reasoning about tax cases
Domain Manual English
Asaro et al.’s Italian Crime Ontology
Schema for representing crimes in Italian law
Knowledge base (schema) in UML, lightly structured
Organize and structure information
Domain Manual Italian
Boer, Hoekstra & Winkel’s CLIME Ontology
Legal advice system for maritime law
Knowledge base in Protégé and RDF, moderately structured
Reasoning and problem solving
Domain Manual English
Lehman, Breuker & Brouwer’s Legal Causation Ontology
Representation of causality in the legal domain
Knowledge base lightly structured
Understand a domain Domain Manual English
Delgado et al’s IPROnto (Intellectual Property Rights Ontology)
Integrating XML DTDs and Schemas that define Rights Expression Languages and Rights Data Dictionaries
Knowledge base: first version in DAML+OIL (2001), current version OWL (2008)
Interoperability between Digital Rights Management (DRM) systems
Domain Manual English
Teodoro, Binefa et al. e-Sentencias (Procedural Ontology for Multimedia in Courts)
Ontology for Representing Procedural Stages of Spanish Civil Hearings
RDF. Procedural Knowledge within Spanish Civil Hearings (typology)
Diarization and Content Classification of the Official Video Recordings (image and audio)
Domain Manual Spanish
J. Saias, P. Quaresma, Portuguese Attorney Office Ontology
Ontology to semantically enriching legal texts
OWL and logic programming (ISCO and EVOLP)
Organize and structure information
Domain Automated
Portuguese
M.Klein, E.Uijttenbroek, A. Lodder, Laymen Ontology
Ontology to represent laymen knowledge on liability cases
OWL and NLP. Knowledge base in laymen natural language
Understand a domain (tort law) and interoperability between NL and legal concepts
Domain Semi-automa
ted
Dutch
J. Breuker, A. Elhag’sCrime.NL
Ontology of Dutch Criminal Law
OKBC Main structure of (Dutch) criminal law; for comparing European CL
Domain/General Manual Dutch/English
S Despres, S. SzulzmanMicro-ontology
Ontology to represent concepts in European Directives
OWL and NLP (TERMINAE method)
Understand a domain Domain Semi-automa
ted
French/English
UCC OntologyJ. Shaheed, A. Yip, J. Cunningham
Ontology to represent top-level concepts (e.g. ownership)
NML Top-level ontology based on NM
Organize and structure information
Domain (top -level)
Manual English
E.Schweighofer, D. Liebwald’sCLO (Comprehensive Legal Ontology)
Ontology for information management
Some frame representation General Manual with
support of legal
core ontologi
es
English?
E. Melz & A. Valente’s IRC ontology
Ontology of Internal Revenue Code (USA)
OWL Reasoning about tax cases
Domain Manual English
Cognitive Modeling. C.W.Chang (2003)
Cognitive Modeling.C.W.Chang (2003)
Organización jerárquica por niveles
Fuente: Breuker et al.; in A. Gangemi, J. Breuker (2002: 29).
LKIF-Core-Ontology
Web Semántica(Web 3.0)
E. Motta and M. Sabou (2006-2007) identifican diversas características de la nueva generación de WS:
• (i) reusabilidad (vs. generación de datos semánticos)
• (ii) sistemas multi-ontológicos (vs. ontologías singulares)
• (iii) apertura a recursos semánticos de alto nivel (top-level resources)
Web Semántica (Web 3.0)
• (iv) la escalabilidad es tan importante como la calidad de los datos
• (v) apertura respecto a la Web (recursos no semánticos)
• (vi) asunción del paradigma interactivo de la Web 2.0
• (vii) apertura a los servicios Web.
GARTNER Hype Cycle for the implementation of a new technology(2006)
GARTNER Hype Cycle for Legal and Regulatory Information Governance,16 July 2007
Colin Rule (e-Bay): Square-trade• "If you have any doubt that consumers are moving to online
commerce, take a look at eBay, the online auction company. In the 13 years since it was founded, eBay has grown into the largest marketplace in the world. In the first half of 2008, there were more than one billion product listings added to eBay worldwide. At any given moment, there are more than 100 million listings around the world, and approximately 7.1 million listings are added each day. eBay users trade almost every kind of item imaginable, in more than 50,000 categories. On eBay, a pair of shoes sells every 7 seconds, a cell phone sells every 7 seconds, and a car sells every 56 seconds. The daily volume of trade on eBay is greater than the daily volume of the NASDAQ.
• Unsurprisingly, all of these transactions generate a lot of consumer disputes. Even though less than 1 percent of purchases generate a problem, the incredible volume on the site means eBay handles more than 40 million disputes a year, in more than 16 different languages”
Transformación del derecho: justicia relacional (Casanovas, 2009)
• “Relational Justice may be defined as the substantive and formal structure that allows end users, in the broader sense (as citizens, consumers, customers, clients, managers, officials…), to participate in the making of their own regulation and legal outcomes through all the mixed and plural strategies that the Semantic Web framework allows. This implies the coexistence of legal and social norms, rights and duties to be shared by subjects (artificial or natural agents) in a structured environment. Therefore, user centered strategies of the next SW generation fit into a middle-out legal approach in which there are rights to be protected and duties to be put in place. The expressive content of Web 2.0 may be shaped as well by the service-oriented motivation of the Web 3.0. “
Transformación del derecho II: derecho relacional (ibid.)
• “From a more traditional point of view, relational justice may be described as a subset of relational law. This is not a new concept, either in public or private law. Regulatory bonds through the emergence of a shared context are the base of several sociological descriptions (Macauley, 1963) and well-known classifications of contracts ―e.g. the notion of relational exchange norms (Macneil, 1985).”
Libro Blanco de la Mediación en Cataluña
• http://www.llibreblancmediacio.com
1. Definició de mediació (en el vostre àmbit)
ODR
Internet
Web 2.0 Suite for ODR
Service Bus
Ontologies ODR Service Execution
ODR Service Definition
Management Tools
Storage
Citizens
ODR Web Platform
Environment Family Healthcare Administration …
Poblet & Casanovas (2008)
Retos• “Knowledge-acquisition bottleneck” (Feigenbaum, 1977)• Representación de conocimiento (e,g, los procesos judiciales y
su lenguaje no han sido descritos en detalle)• Construcción de ontologías jurídicas (una sola ontología
nuclear?) • Usuarios finales• Interoperabilidad semántica entre lenguajes, sistemas y con los
usuarios• Superación de obstáculos jurídicos y políticos • Adaptación del ciclo de vida de los sistemas al ritmo de
desarrollo de las instituciones
Añadir semántica al derecho significa….
• Comprender las transformaciones del mercado jurídico y de la sociedad (necesidades de la gente como usuarios de la Web)
• Estar atentos a las posibilidades de la nueva generación de aplicaciones de la WS (interoperatividad con el usuario, sea ciudadano o profesional)
• Enfrentarse a los viejos problemas, especialmente los de adquisición de conocimiento y construcción de ontologías
Más en…• R.V. Benjamins, P.Casanovas, J. Breuker, A.
Gangemi (eds.), Law and the Semantic Web, LNAI 3369, Springer, 2005.
• P. Casanovas, G.Sartor, N.Casellas, R.Rubino (eds.), Computable Models of the Law, LNAI 4884, Springer, 2008
• J. Breuker, P.Casanovas, M.Klein, E. Francesconi (eds.), Law, Ontologies and the Semantic Web. Channelling the Legal Information Flood. IOS Press, Amsterdam, 2009.
Eventos
• http://idt.uab.cat/icail2009/
• http://www.simposiummediacio.com/
• http://idt.uab.es/IVRXXIV-aicol09/
GRACIAS!