SmaRT Visualization of Legal Rules for Compliance

Slides:



Advertisements
Similar presentations
Event and Process Semantics will Rule RuleML, 2008 Paul Haley Automata, Inc. (412) Copyright © 2008, Automata, Inc.
Advertisements

Dr. Leo Obrst MITRE Information Semantics Information Discovery & Understanding Command & Control Center February 6, 2014February 6, 2014February 6, 2014.
Language Technologies Reality and Promise in AKT Yorick Wilks and Fabio Ciravegna Department of Computer Science, University of Sheffield.
Mitsunori Ogihara Center for Computational Science
CILC2011 A framework for structured knowledge extraction and representation from natural language via deep sentence analysis Stefania Costantini Niva Florio.
Financial Industry Semantics and Ontologies The Universal Strategy: Knowledge Driven Finance Financial Times, London 30 October 2014.
Building and Analyzing Social Networks Web Data and Semantics in Social Network Applications Dr. Bhavani Thuraisingham February 15, 2013.
Research topics Semantic Web - Spring 2007 Computer Engineering Department Sharif University of Technology.
IR & Metadata. Metadata Didn’t we already talk about this? We discussed what metadata is and its types –Data about data –Descriptive metadata is external.
Semantic Web and Web Mining: Networking with Industry and Academia İsmail Hakkı Toroslu IST EVENT 2006.
Semantic Web Presented by: Edward Cheng Wayne Choi Tony Deng Peter Kuc-Pittet Anita Yong.
Breakout Session 5 Languages (operators and rules) for specifying constraints, mappings, and policies governing financial instruments.
Semantic Mediation & OWS 8 Glenn Guempel
Artificial Intelligence Research Centre Program Systems Institute Russian Academy of Science Pereslavl-Zalessky Russia.
Redefining Perspectives A thought leadership forum for technologists interested in defining a new future June COPYRIGHT ©2015 SAPIENT CORPORATION.
OMAP: An Implemented Framework for Automatically Aligning OWL Ontologies SWAP, December, 2005 Raphaël Troncy, Umberto Straccia ISTI-CNR
Some Thoughts to Consider 6 What is the difference between Artificial Intelligence and Computer Science? What is the difference between Artificial Intelligence.
Ontology Alignment/Matching Prafulla Palwe. Agenda ► Introduction  Being serious about the semantic web  Living with heterogeneity  Heterogeneity problem.
revised CmpE 583 Fall 2006Discussion: OWL- 1 CmpE 583- Web Semantics: Theory and Practice DISCUSSION: OWL Atilla ELÇİ Computer Engineering.
Learning Object Metadata Mining Masoud Makrehchi Supervisor: Prof. Mohamed Kamel.
The 7th International Web Rule Symposium: Research Based and Industry Focused (RuleML 2013) July 11-13, 2013, Seattle, USA.
Recording application executions enriched with domain semantics of computations and data Master of Science Thesis Michał Pelczar Krakow,
MPEG-7 Interoperability Use Case. Motivation MPEG-7: set of standardized tools for describing multimedia content at different abstraction levels Implemented.
NLP And The Semantic Web Dainis Kiusals COMS E6125 Spring 2010.
Towards an ecosystem of data and ontologies Mathieu d’Aquin and Enrico Motta Knowledge Media Institute The Open University.
Ontology Summit 2015 Track C Report-back Summit Synthesis Session 1, 19 Feb 2015.
Confidential 111 Financial Industry Business Ontology (FIBO) [FIBO– Business Entities] Understanding the Business Conceptual Ontology For FIBO-Business.
Coastal Atlas Interoperability - Ontologies (Advanced topics that we did not get to in detail) Luis Bermudez Stephanie Watson Marine Metadata Interoperability.
Mining Structured vs. Unstructured Data Where is the structure and where did the semantics go? Rahim Yaseen SAP Labs LLC.
Logics for Data and Knowledge Representation Applications of ClassL: Lightweight Ontologies.
©Ferenc Vajda 1 Semantic Grid Ferenc Vajda Computer and Automation Research Institute Hungarian Academy of Sciences.
GTRI.ppt-1 NLP Technology Applied to e-discovery Bill Underwood Principal Research Scientist “The Current Status and.
Jan 9, 2004 Symposium on Best Practice LSA, Boston, MA 1 Comparability of language data and analysis Using an ontology for linguistics Scott Farrar, U.
GREGORY SILVER KUSHEL RIA BELLPADY JOHN MILLER KRYS KOCHUT WILLIAM YORK Supporting Interoperability Using the Discrete-event Modeling Ontology (DeMO)
SemantEco Annotator for Linked Data Generation and Generalized Semantic Mapping Session: Technologies, Reasoning, and Annotation Methods of the Semantics.
For Monday Read chapter 26 Last Homework –Chapter 23, exercise 7.
PHS / Department of General Practice Royal College of Surgeons in Ireland Coláiste Ríoga na Máinleá in Éirinn Knowledge representation in TRANSFoRm AMIA.
Working with Ontologies Introduction to DOGMA and related research.
WEB PAGE CONTENTS VERIFICATION AGAINST TAGS USING DATA MINING TOOL IKNOW VІI scientific and practical seminar with international participation "Economic.
For Friday Finish chapter 23 Homework –Chapter 23, exercise 15.
1 Open Ontology Repository initiative - Planning Meeting - Thu Co-conveners: PeterYim, LeoObrst & MikeDean ref.:
Approach to building ontologies A high-level view Chris Wroe.
updated CmpE 583 Fall 2008Discussion: Rules & Markup- 1 CmpE 583- Web Semantics: Theory and Practice DISCUSSION: RULES & MARKUP Atilla.
A Portrait of the Semantic Web in Action Jeff Heflin and James Hendler IEEE Intelligent Systems December 6, 2010 Hyewon Lim.
An Ontological Approach to Financial Analysis and Monitoring.
For Monday Read chapter 26 Homework: –Chapter 23, exercises 8 and 9.
GoRelations: an Intuitive Query System for DBPedia Lushan Han and Tim Finin 15 November 2011
Of 24 lecture 11: ontology – mediation, merging & aligning.
An Ontology-based Automatic Semantic Annotation Approach for Patent Document Retrieval in Product Innovation Design Feng Wang, Lanfen Lin, Zhou Yang College.
Semantic Web. P2 Introduction Information management facilities not keeping pace with the capacity of our information storage. –Information Overload –haphazardly.
Semantic Web Technologies Readings discussion Research presentations Projects & Papers discussions.
Food and Agriculture Organization of the UN GILW Library and Documentation Systems Division Food, Nutrition and Agriculture Ontology Portal.
Trends in NL Analysis Jim Critz University of New York in Prague EurOpen.CZ 12 December 2008.
Consumers of FDTF standards
DOMAIN ONTOLOGY DESIGN
Ontology From Wikipedia, the free encyclopedia
Kenneth Baclawski et. al. PSB /11/7 Sa-Im Shin
Lecture #11: Ontology Engineering Dr. Bhavani Thuraisingham
Presented by: Hassan Sayyadi
Semantic Web Technologies
Event and Process Semantics will Rule
Taxonomies, Lexicons and Organizing Knowledge
Analyzing and Securing Social Networks
Exploring Scholarly Data with Rexplore
Property consolidation for entity browsing
Chatbots for Dummies José 12/05/2018 Immersion
Information Networks: State of the Art
CS246: Information Retrieval
Information Retrieval
Co-champions: Mike Bennett, Andrea Westerinen
Presentation transcript:

SmaRT Visualization of Legal Rules for Compliance Selja Seppälä Marcello Ceci Hai Huang Leona O’Brien Tom Butler

Contents The Issue The Regulatory Interpretation Methodology SBVR and Mercury Visualizing Verb Concepts and Keywords Visualizing Rules Neo4j Visualization

New Technologies Need New Techniques The complexity of regulation In the aftermath of the Financial Crisis The complexity and ambiguity of legalese Automatic extraction of requirements from legal texts is not reliable Information Systems of the Financial Industry are lagging behind There is a natural resistance against new (semantic) technologies that must be tackled An open approach to translating regulative rules No closed list of logical sentences Allow for multiple interpretations of the same legal text Vocabulary is created as you go For Constitutive Rules, legal concept patterns are used (e.g. commencement, definition) Relies on tools (Demo of Ganesha 0.1 later on)

Regulatory Interpretation Methodology Subject-Matter Expert Legal Text ? Rule Language RDF Business Processes (BPMN) Ontology Semantic Technology Expert

SBVR Business Rules and Business Vocabulary It is prohibited that an Investment Firm that operates an OTF engages in Matched Principal Trading. Rulebook Vocabulary Investment Firm operates OTF Investment Firm engages in Matched Principal Trading Verb concepts Noun concepts Investment Firm OTF Matched Principal Trading

The Mercury Knowledge Base Every rule has a unambiguous logical formulation in propositional logics: (for each Investment Firm, OTF and Matched Principal Trading) if an investment firm operates an OTF then it is forbidden that that same investment firm engage in matched principal trading It is prohibited that an Investment Firm that operates an OTF engages in Matched Principal Trading.

FIRO Financial Industry Regulatory Ontology http://www.grctc.com/platform-research/firo/ It is prohibited that an Investment Firm that operates an OTF engages in Matched Principal Trading. What requirements are breached by Event x?  Query:  PREFIX onto:<http://www.GRCTC.com/Ontologies/FIRO/FIRO-H-v2#> SELECT ?rs WHERE { ?rs rdf:type onto:RegulatoryStatement. onto:x onto:breaches ?rs } Visualization: It is prohibited that Investment Firm engages in Matched Principal Trading Investment Firm operates OTF

Visualizing Keywords /1 Original sentence: market operator makes public credits and debt  Semantics: market operator makes public credits and same market operator makes public debts 

Visualizing Keywords /2 Original sentence: market operator operating a trading venue makes public credits  Semantics: market operator makes public credits and same market operator operates trading venue 

Visualizing Regulative Rules /1 Original sentence: It is obligatory that a market operator that operates a trading venue makes public credits and debts.

Visualizing Regulative Rules /2 Semantics: If some market operator operates some trading venue then it is obligatory that the same market operator makes public each debt and the same market operator makes public each credit. 

Neo4j Visualization

Future Work Automatic graph generation from RDF Cover other keywords Negation Quantifiers Automatic RDF generation from graph Visualizing constitutive rules

Thank you! Contacts: selja.seppala@ucc.ie marcello.ceci@ucc.ie hai.huang@ucc.ie Ceci, M., Al Khalil, F., O’Brien, L., and Butler, T., (2016) Requirements for an Intermediate Language Bridging Legal Text and Rules, December 2016, Workshop on Mining and Reasoning with Legal texts (MIREL), At Nice, France Al Khalil, F., Ceci, M., Yapa, K. and O’Brien, L., (2016), July. SBVR to OWL 2 Mapping in the Domain of Legal Rules. In International Symposium on Rules and Rule Markup Languages for the Semantic Web (pp. 258-266). Springer International Publishing. Ceci, M., Al Khalil, F. and O’Brien, L., (2016) Making Sense of Regulations with SBVR. RuleML 2016 Challenge, Doctoral Consortium and Industry Track hosted by the 10th International Web Rule Symposium (RuleML 2016).

Vocabulary Entries Advanced management of definitions: It is prohibited that an Investment Firm that operates an OTF engages in Matched Principal Trading. Noun concepts (entities) and actions can be aligned to business entities and activities in business policies and processes. Advanced management of definitions: Distinguish legal vs. non-legal definitions Distinguish definitions as (structural) rules from definitions in free text Identify the context Use different vocabulary entries for concepts with same designation but different definitions and/or domains (business/legal) Investment Firm Definition: [text or rule] Source: MiFID art. 4 Context: MiFID Investment Firm Definition: [text or rule] Source: Business Policy “X”, p. 1 Context: Business Policy “X” Investment Firm Definition: [text or rule] Source: MiFIR art. 3 Context: MiFIR

Mercury/FIRO Features Vocabulary potentialities Alignment to taxonomies Expressing semantics of definitions Classifying Disambiguating with context Rulebook potentialities Representing logical formulation of the rule Graph representation Alignment to business processes Automatic reasoning on compliance