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(ANN) Proposed Charter for LegalRuleML Technical Committee

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2011-11-28T13:31:59+00:00
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(ANN) Proposed Charter for LegalRuleML Technical Committee
To OASIS Members:

A draft TC charter has been submitted to establish the LegalRuleML  
Technical Committee. In accordance with the OASIS TC Process Policy section  
2.2: (http://www.oasis-open.org/committees/process-2009-07-30.php#formation)  
the proposed charter is hereby submitted for comment. The comment period  
shall remain open until 11:45 pm ET on 12 December 2011.

OASIS maintains a mailing list for the purpose of submitting comments on  
proposed charters. Any OASIS member may post to this list by sending email  
to: . All messages will be publicly  
archived at: http://lists.oasis-open.org/archives/oasis-charter-discuss/.  
Members who wish to receive emails must join the group by selecting "join  
group" on the group home page:  
http://www.oasis-open.org/apps/org/workgroup/oasis-charter-discuss/.  
Employees of organizational members do not require primary representative  
approval to subscribe to the oasis-charter-discuss e-mail.

A telephone conference will be held among the Convener, the OASIS TC  
Administrator, and those proposers who wish to attend within four days of the  
close of the comment period. The announcement and call-in information will be  
noted on the OASIS Charter Discuss Group Calendar.

We encourage member comment and ask that you note the name of the proposed  
TC (LegalRuleML) in the subject line of your email message.

=== Proposed Charter

1.a Name of the TC:

LegalRuleML Technical Committee

1.b Statement of Purpose:

The goal of the LegalRuleML TC is to extend RuleML [RuleML 2011] with  
features specific to the formaliztion of norms, guidelines, and legal  
reasoning.

Legal texts are the source of norms, guidelines, and rules that often feed  
into different concrete (usually XML-based) Web applications. Legislative  
documents typically provide general norms and specific procedural rules for  
eGovernment and eCommerce environments, while contracts specify the  
conditions of services and business rules (e.g. service level agreements for  
cloud computing), and judgments provide information about arguments and  
interpretation of norms that establish concrete case-law.

The ability to have proper and expressive conceptual models of the various  
and multifaceted aspects of norms, guidelines, and general legal knowledge is  
a key factor for the development and deployment of successful  
applications.

The LegalRuleML TC aims to produce a rule interchange language for the  
legal domain. This will enable modeling and reasoning such that implementers  
can structure, evaluate, and compare legal arguments constructed using the  
rule representation tools provided.

1.c Scope of Work:

The Artificial Intelligence (AI) and Law communities have converged in the  
last twenty years on modeling legal norms and guidelines using logic and  
other formal techniques [Ashley 2011]. Existing methods begin with the  
analysis of a legal text by a Legal Knowledge Engineer who extracts the norms  
and guidelines, applies models and a theory within a logical framework, and  
finally represents the norms using a particular formalism. In the last  
decade, several Legal XML standards were proposed to describe legal texts  
[Lupo et al. 2007] with XML-based rules (RuleML, SWRL, RIF, LKIF, etc.)  
[Gordon et al. 2009; Gordon 2008]. In the meantime, the Semantic Web, in  
particular Legal Ontology research combined with semantic norm extraction  
based on Natural Language Processing (NLP) [Francesconi et al. 2010], gave a  
great impulse to the modeling of legal concepts [Boer et al. 2008; Benjamins  
2005; Breuker 2006].

Based on this, the work of the LegalRuleML Technical Committee will focus  
on three specific needs:

1. Closing the gap between natural language text description and semantic  
norm modeling, in order to realize an integrated and self-contained  
representation of legal resources that can be made available on the Web as  
XML representations [Palmirani 2009]. This formal underpinning can then  
foster Semantic Web technologies such as: NLP, Information Retrieval (IR),  
graph representation, as well as Web ontologies and rules.

2. To provide an expressive XML standard for modeling normative rules that  
is able to satisfy the legal domain requirements. This will enable use of a  
legal reasoning level on top of the ontological layer that aligns with the  
W3C envisioned Semantic Web stack. This approach seeks also to fill the gap  
between regulative norms, guidelines and business rules in order to capture  
and model the processes embedded in those guidelines and make them usable for  
the workflow and business layer [Governatori 2010; Rotolo 2009; Grosof  
2004];

3. Supporting the Linked Open Data [Berners-Lee 2010] approach to modeling  
regarding not only the semantics of raw data (acts, contracts, court files,  
judgments, etc.), but also of rules in conjunction with their functionality  
and

usage. Without rules or axioms, legal concepts constitute just a taxonomy  
[Sartor 2009].

The LegalRuleML TC work will address these three main goals and provide  
means for modeling norms, guidelines, judgements, and contracts using a  
semantic approach.

In particular, the LegalRuleML work will extend the existing RuleML, RIF  
and related Web rule work by improved modeling as well as representing and  
capturing the legal knowledge embedded in legal texts.

Specifically, the LegalRuleML work will facilitate the following  
functionalities.

A) Support for modeling different types of rules:

- CONSTITUTIVE RULES, which define concepts or constitute activities that  
cannot exist without such rules (especially Legal definitions such as  
'property').

- TECHNICAL RULES, which state that something has to be done in order for  
something else to be attained (especially Rules governing taxation).

- PRESCRIPTIVE RULES, which regulate actions by making them obligatory,  
permitted, or prohibited (especially obligations in contracts).

B) Implementing ISOMORPHISM [Bench-Capon-Coenen 1992]. To ease validation  
and maintenance, there should be a one-to-one correspondence between the  
rules in the formal model and the units of (controlled) natural language text  
that express the rules in the original legal sources, such as sections of  
legislation.

C) Manage the REIFICATION [Gordon 1995] of rules that are objects with  
properties, such as Jurisdiction, Authority, Temporal attributes [Palmirani  
2010; Governatori 2009; Governatori 2005]. These elements have to be added to  
the current RuleML to enable effective legal reasoning.

D) Represent NORMATIVE EFFECTS and VALUES. There are many normative  
effects that follow from applying rules, such as obligations, permissions,  
prohibitions, and also more articulated effects such as those introduced.  
Usually, some values are promoted by legal rules as well.

F) Implement DEFEASIBILITY [Gordon 1995, Prakken 1996, Sartor 2005]. When  
the antecedent of a rule is satisfied by the facts of a case (or via other  
rules), the conclusion of the rule presumably holds, but is not necessarily  
true. The

defeasibility of legal rules breaks down into the following issues: Conflicts  
and Exclusionary rules.

Lastly, the LegalRuleML work will also aim to model legal procedural  
rules. Rules not only regulate the procedures for resolving legal conflicts,  
but also are used for arguing or reasoning about whether or not some action  
or state complies with other, substantive rules. In particular, rules are  
required for procedures which regulate methods for detecting violations of  
the law, i.e., which determine the normative effects triggered by norm  
violations, such as reparative obligations, which are meant to repair or  
compensate violations. Note that these constructions can give rise to very  
complex rule dependencies, because the violation of a single rule can  
activate other (reparative) rules, which in turn, in case of their violation,  
refer to other rules, and so forth.

In this case, the Deliberation RuleML and Reaction RuleML parts [Boley et  
al. 2010] are coordinated within the LegalRuleML module to produce benefits  
for applications and reasoning engines (avoiding redundancy in the rules as  
well as

facilitating coordination, synchronisation, and cooperation.)

Compatibility: Compatibility with the RuleML 1.0 schemas [Athan et al.  
2011; Boley 2011; Boley et al. 2010; Wagner et al. 2004; Boley et al. 2001]  
and interoperability with the main languages for rule modeling, mainly Common  
Logic, RIF, and SWRL.

Out of Scope: Developing tools for LegalRuleML. (This will be started by  
the supporters of this proposal and others independently once a first stable  
version of LegalRuleML exists.)

1.d Deliverables

The LegalRuleML TC will provide XML representations that address the  
aforementioned requirements and support interchange with the business rule  
domain.

The following deliverables are expected:

D1. LegalRuleML semantic level (e.g. temporal dimension) drafts - within  
six months of the first TC meeting

D2. LegalRuleML logic level (e.g. defeasibility, deontic, and argumentation)  
drafts - within eight months of the first TC meeting

D3. LegalRuleML integration with business and process rule drafts - within  
ten months of the first TC meeting

D4. Pilot use cases - within twelve months of the first TC meeting

D5. Tutorials and general documentation - continuously produced and updated  
during the entire process

The semantic and logic levels constitute the core part of the LegalRuleML  
functionality. They define the principles of design, the architecture of the  
syntax, the main elements for managing patterns, abstract types, groups of  
attributes, general classes, ontology-level connections, and rule-level  
connections.

Maintenance: Once the TC has completed work on a deliverable that has  
become an OASIS Standard, the TC will enter "maintenance mode" for the  
deliverable. The purpose of maintenance mode is to provide minor revisions to  
previously adopted deliverables to clarify ambiguities, inconsistencies, and  
obvious errors. Maintenance mode is not intended to enhance a deliverable or  
to extend its functionality.

The TC will collect issues raised against the deliverables and  
periodically process those issues. Issues that request or require new or  
enhanced functionality shall be marked as enhancement requests and set aside.  
Issues that result in the clarification or correction of the deliverables  
shall be processed. The TC shall maintain a list of these adopted  
clarifications and shall periodically create a new minor revision of the  
deliverables including these updates. Periodically, but at least once a year,  
the TC shall produce and vote upon a new minor revision of the  
deliverables.

1.e IPR Model

This TC will operate under the "RF (Royalty Free) on Limited Terms" IPR mode  
as defined in the OASIS Intellectual Property Rights (IPR) Policy.

1.f Anticipated Audience

The anticipated audience for this work includes:

1. Vendors and service providers offering products and/or services in the  
legal domain (e.g. eGovernment, cloud computing SLAs, contracting, and  
legislation)

2. Authors of other specifications that require rule language standards for  
legal, regulatory and policy representations

3. Software architects who design, write, integrate, and deploy rule engines  
in the legal domain

4. End users modeling legal rules that require an interoperable solution  
using a standard language

5. The U.S. NIEM community for government domain rule management and  
representation

6. The OASIS LegalXML MS and other OASIS entities that are providing input  
for and/or are planning to refer to LegalRuleML from their  
specifications.

1.g Language:

The output documents will be written in (US) English. TC meetings shall be  
conducted in English.

References:

1. Ashley Kevin D., van Engers Tom M. (Eds.): The 13th International  
Conference on Artificial Intelligence and Law, Proceedings of the Conference,  
June 6-10, 2011, Pittsburgh, PA, USA. ACM 2011

2. Athan T., Boley H.: Design and Implementation of Highly Modular Schemas  
for XML: Customization of RuleML in Relax NG. RuleML America 2011: 17-32

3. Bench-Capon T. and Coenen F.: Isomorphism and legal knowledge based  
systems. Artificial Intelligence and Law, 1(1):65, 1992.

4. Benjamins V. R., Casanovas P., Breuker J., and Gangemi A., editors. Law  
and the Semantic Web: Legal Ontologies, Methodologies, Legal Information  
Retrieval and Applications. Springer-Verlag, 2005.

5. Berners-Lee T.: Long Live the Web: A Call for Continued Open Standards and  
Neutrality, Scientific America, 2010.

6. Boer A., Radboud W., Vitali F.: MetaLex XML and the Legal Knowledge  
Interchange Format, in Computable Models of the Law, Springer, 2008.

7. Boley H., Paschke A., Shafiq O.: RuleML 1.0: The Overarching Specification  
of Web Rules. RuleML 2010: 162-178.

8. Boley H., Tabet S., and Wagner G.: Design rationale for RuleML: A markup  
language for Semantic Web rules. In I. F. Cruz, S. Decker, J. Euzenat, and D.  
L. McGuinness, editors, Proc. SWWS, The first Semantic Web Working Symposium,  
pages 381, 2001.

9. Boley H.: A RIF-Style Semantics for RuleML-Integrated Positional-Slotted,  
Object-Applicative Rules. RuleML Europe 2011: 194-211

10. Breuker J., Boer A., Hoekstra R., Van Den Berg C.: Developing Content for  
LKIF: Ontologies and Framework for Legal Reasoning, in Legal Knowledge and  
Information Systems, JURIX 2006, pp.41-50, ISO Press, Amsterdam, 2006.

11. Francesconi E., Montemagni S., Peters W., Tiscornia D.: Semantic  
Processing of Legal Texts: Where the Language of Law Meets the Law of  
Language. Springer 2010.

12. Giovanni S.: Legal concepts as inferential nodes and ontological  
categories. Artif. Intell. Law 17 (3): pp. 217-251, 2009.

13. Gordon T. F., Guido Governatori, Antonino Rotolo: Rules and Guidance:  
Requirements for Rule Interchange Languages in the Legal Domain. RuleML 2009:  
pp. 282-296, 2009.

14. Gordon T. F.: Constructing Legal Arguments with Rules in the Legal  
Knowledge Interchange Format (LKIF). Computable Models of the Law, Languages,  
Dialogues, Games, Ontologies 2008, pp. 162-184, 2008.

15. Gordon T. F.: The Pleadings Game; An Artificial Intelligence Model of  
Procedural Justice. Springer, New York, 1995. Book version of 1993 Ph.D.  
Thesis; University of Darmstadt, 1993.

16. Governatori G. and Rotolo A.: Changing legal systems: Legal abrogations  
and annulments in defeasible logic. The Logic Journal of IGPL, 2010.

17. Governatori G., Rotolo A., and Sartor G.. Temporalised normative  
positions in defeasible logic. In Proc. ICAIL, pages 25-34. ACM Press,  
2005.

18. Governatori G., Rotolo A.: Norm Compliance in Business Process Modeling.  
RuleML 2010: pp. 194-209, 2010

19. Governatori G.: Representing business contracts in RuleML. International  
Journal of Cooperative Information Systems, 14(2-3):pp. 181-216, 2005.

20. Grosof B. Representing e-commerce rules via situated courteous logic  
programs in RuleML. Electronic Commerce Research and Applications, 3(1):2-20,  
2004.

21. http://www.niem.gov/pdf/NIEM_HLVA.pdf

22. Lupo C., Vitali F., Francesconi E., Palmirani M., Winkels R., de Maat E.,  
Boer A., and Mascellani P: General xml format(s) for legal sources - Estrella  
European Project IST-2004-027655. Deliverable 3.1, Faculty of Law, University  
of Amsterdam, Amsterdam, The Netherlands, 2007.

23. Palmirani M., Contissa G., Rubino R.: Fill the Gap in the Legal Knowledge  
modeling. RuleML 2009: 305-314, 2009.

24. Palmirani M., Governatori G. and Contissa G:. Temporal Dimensions in the  
Rules: an Evolution of LKIF Rule, Jurix 2010.

25. Palmirani M., Governatori G., Rotolo A., Tabet S., Boley H., Paschke A.:  
LegalRuleML: XML-Based Rules and Guidance. RuleML America 2011: 298-312

26. Prakken H. and Sartor G.: A dialectical model of assessing conflicting  
argument in legal reasoning. Artificial Intelligence and Law, 4(3-4):331-368,  
1996.

27. Rotolo A., Sartor G., and Smith C.: Good faith in contract negotiation  
and performance. International Journal of Business Process Integration and  
Management, 5(4), 2009.

28. RuleML. The Rule Markup Initiative. http://www.ruleml.org, accessed 8th  
November 2011.

29. Sartor G.: Legal reasoning: A cognitive approach to the law. In E.  
Pattaro, H. Rottleuthner, R. Shiner, A. Peczenik, and G. Sartor, editors, A  
Treatise of Legal Philosophy and General Jurisprudence, volume 5. Springer,  
2005.

30. Wagner G., Antoniou G., Tabet S., and Boley H.: The abstract syntax of  
RuleML - towards a general web rule language framework. In Proc. Web  
Intelligence 2004, pages 628-631.

ADDITIONAL INFORMATION:

2.a Identification of similar or applicable work:

The LegalRuleML TC will incorporate definitions and terminologies from OASIS  
standards, especially from which coming from LegalXML TCs, as well as from  
standards work done by non-OASIS organizations. As stated in the charter, the  
TC will use a standard from one non-OASIS organization and may choose to use  
the works of other OASIS TCs and standards from non-OASIS organizations, as  
it sees fit. Liaisons may be established, and the TC may agree to concurrent  
work items with other TCs and organizations, within the scope defined here.  
Among other things, the TC may establish liaisons with W3C (RIF), OMG, and  
other such standards organizations, as it may choose.

2.b The date, time, and location of the first meeting:

The LegalRulML TC will hold its first official meeting on 13 January 2012 at  
6:00pm UTC, 13:00am (U.S. EST), 10:00am (U.S. PDT) 19:00 (CET) 5:00am  
(Australia EDT) by telephone and will use a free conference call service.  
CIRSFID will host the first technical meeting.

2.c The projected on-going meeting schedule for the year:

The TC will meet bi-weekly or as otherwise agreed upon by the members of the  
technical committee.

2.d The names, electronic mail addresses, and membership affiliations of  
at least Minimum Membership who support this proposal:

1. Monica Palmirani, , CIRSFID, University of  
Bologna, Italy

2. Guido Governatori, , NICTA, Queensland  
Laboratory, Australia, and RuleML director

3. Antonino Rotolo, , CIRSFID, University of Bologna,  
Italy, and RuleML director

4. Carl Mattocks,, Individual Member

5. Joseph D.K. Wheeler,, MTG Management Consultants, L.L.C.

2.e Primary Representative Approval Statements:

Monica Palmirani, , CIRSFID, University of  
Bologna, Italy

As CIRSFID's Primary Representative, I approve the LegalXML TC Charter and  
its goals on legal modeling and reasoning, and support our proposers (listed  
above) as a named co-proposer.

Guido Governatori, , NICTA, Queensland  
Laboratory, Australia, and RuleML director

As NICTA's Primary Representative, I approve the LegalXML TC Charter and its  
worthwhile goals, and support our proposers (listed above) as a named  
co-proposer.

Joseph Wheeler, , MTG Management Consultants LLC

As MTG's Primary Representative, I approve the LegalRuleML TC Charter and its  
worthwhile goals, and support our proposers (listed above) as a named  
co-proposer.

2.f Convener:

Monica Palmirani, , CIRSFID, University of Bologna,  
Italy

2.g. Member Section:

The TC intends to be affiliated with the LegalXML MS.

2.h Optional list of anticipated contributions:

The LegalRuleML TC intends to use as a foundation and input the draft RuleML  
specifications (http://ruleml.org/1.0/) provided by the RuleML Inc.  
initiative, as well as any subsequent input documents accepted by the  
LegalRuleML TC.

Best Regards,

/chet

----------------

Chet Ensign

Director of Standards Development and TC Administration

OASIS: Advancing open standards for the information society

http://www.oasis-open.org

Primary: +1 973-378-3472

Mobile: +1 201-341-1393
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