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Subject: Call for Participation: LegalRuleML Technical Committee (LegalRuleML) TC

OASIS members & interested parties,

A new OASIS technical committee is being formed. The OASIS LegalRuleML
Technical Committee has been proposed by the members of OASIS listed
in the charter below. The TC name, statement of purpose, scope, list
of deliverables, audience, IPR mode and language specified in the
proposal will constitute the TC's official charter. Submissions of
technology for consideration by the TC, and the beginning of technical
discussions, may occur no sooner than the TC's first meeting.

The eligibility requirements for becoming a participant in the TC at
the first meeting are:

(a) you must be an employee of an OASIS member organization or an
individual member of OASIS, and

(b) you must join the Technical Committee, which members may do by
using the "Join this TC" button on the TC's home page at [a].

To be considered a voting member at the first meeting, you must:

(a) join the Technical Committee at least 7 days prior to the first
meeting (on or before 12 January 2012); and

(b) you must attend the first meeting of the TC, at the time and date
fixed below (19 January 2012).

Participants also may join the TC at a later time. OASIS and the TC
welcome all interested parties.

Non-OASIS members who wish to participate may contact us about joining
OASIS [b]. In addition, the public may access the information
resources maintained for each TC: a mail list archive, document
repository and public comments facility, which will be linked from the
TC's public home page.

Please feel free to forward this announcement to any other appropriate
lists. OASIS is an open standards organization; we encourage your

[a] http://www.oasis-open.org/committees/legalruleml/
[b] See http://www.oasis-open.org/join/


OASIS LegalRuleML Technical Committee

The charter for this TC is as follows.

=== 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 formalisation of norms, guidelines, and legal

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

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 modelling 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 modelling, in order to realise 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 modelling 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

Specifically, the LegalRuleML work will facilitate the following

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

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

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

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

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 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.


Once the TC has completed work on a deliverable that has become an
OASIS Standard, the TC will enter "maintenance mode" for the

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)

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

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

1.g Language:

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


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):65-86, 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'01, The first
Semantic Web Working Symposium, pages 381-401, 2001.
9. Boley H.: A RIF-Style Semantics for RuleML-Integrated
Positional-Slotted, Object-Applicative Rules. RuleML Europe 2011:
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'05, 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,
23. Palmirani M., Contissa G., Rubino R.: Fill the Gap in the Legal
Knowledge Modelling. 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 legalreasoning. 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
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.


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 and XACML
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 19 January
2012 at 7:00pm UTC, 2:00pm (U.S. EST), 11:00am (U.S. PDT) 20:00 (CET)
6:00am (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, monica.palmirani@unibo.it, CIRSFID, University of
Bologna, Italy

2. Guido Governatori, guido.governatori@nicta.com.au, NICTA,
Queensland Laboratory, Australia, and RuleML director

3. Antonino Rotolo, antonino.rotolo@unibo.it, CIRSFID, University of
Bologna, Italy, and RuleML director

4. Carl Mattocks,carlmattocks@gmail.com, Individual Member

5. Joseph D.K. Wheeler,jdw@mtgmc.com, MTG Management Consultants, L.L.C.

6. Mark Proctor, mproctor@redhat.com, Red Hat Inc.

2.e Primary Representative Approval Statements:

Monica Palmirani, monica.palmirani@unibo.it, 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, guido.governatori@nicta.com.au, 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, jwheeler@mtgmc.com, 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.

Mark Little, mlittle@redhat.com, Red Hat Inc.:
As Red Hat'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, monica.palmirani@unibo.it, 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 Ensign
Director of Standards Development and TC Administration
OASIS: Advancing open standards for the information society

Primary: +1 973-378-3472
Mobile: +1 201-341-1393

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