Ontologías jurídicas y la segunda generación de Servicios

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, You. Tube, 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)

The Big Picture GOVERNMENT BUSINESS/SCIENCE CITIZEN/CONSUMER/ EMPLOYEE e. Government, e. Energy, e. Health, Public Security Cluster/SME, new Service and Business Models “Digital Lifestyle”, New Media, Communities, Collaboration MULTIMEDIA CONTENT INTERNET OF THINGS SERVICE-ORIENTED SOFTWARE APPLICATIONS 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-D 12. 5. 5

Porcentajes día/abogados Poblet, Benjamins, Casanovas Fuente: SEKT D 12. 5. 5

Uso creciente de Internet I • En 2008, un 40% 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/Black. Berry (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”

Web Semántica Niveles de lenguajes de la WS Berners-Lee Cody Burleson (2007).

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. w 3. 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. Mc. Carty, 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 Constru ction Langua ge Mc. Carty’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 Knowledgebased 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 LRICore Ontology Support knowledge acquisition for legal domain ontologies Knowledge base in DAML+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 Jur. Word. Net Extension to the legal domain of Word. Net 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 Semiautomat ed 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 Automat ed French Leary, Vanderverghe & Zeleznikow’s Financial Fraud 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 Legal advice system for Knowledge base in Protégé and Reasoning and problem 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 to semantically enriching legal texts OWL and logic programming (ISCO and EVOLP) Organize and structure information Domain Automat ed Portugue se M. Klein, E. Uijttenbroek, A. Lodder, Laymen 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 Semiautomat ed Dutch J. Breuker, A. Elhag’s Crime. NL Ontology of Dutch Criminal Law OKBC Main structure of (Dutch) criminal law; for comparing European CL Domain/General Manual Dutch/En glish S Despres, S. Szulzman Micro-ontology Ontology to represent concepts in European Directives OWL and NLP (TERMINAE method) Understand a domain Domain Semiautomat ed French/E nglish UCC Ontology. J. Shaheed, A. Yip, J. Cunningham Ontology to represent toplevel concepts (e. g. ownership) NML Top-level ontology based on NM Organize and structure information Domain (top -level) Manual English E. Schweighofer, D. Liebwald’s CLO (Comprehensive Legal Ontology) Ontology for information management Some frame representation General Manual with support of legal core ontologie s English? E. Melz & A. Valente’s IRC ontology Ontology of Internal Revenue Code (USA) OWL Domain Manual English Reasoning about tax cases

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 e. Bay, the online auction company. In the 13 years since it was founded, e. Bay 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 e. Bay 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. e. Bay users trade almost every kind of item imaginable, in more than 50, 000 categories. On e. Bay, 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 e. Bay 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 e. Bay 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)

Citizens Web 2. 0 Suite for ODR Internet Service Bus ODR Ontologies Environment Storage ODR Service Execution ODR Service Definition Family Healthcare Administration ODR Web Platform Management Tools …

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/icail 2009/ • http: //www. simposiummediacio. com/ • http: //idt. uab. es/IVRXXIV-aicol 09/

GRACIAS!