OASIS LegalRuleML Technical Committee

The official charter for this Technical Committee is provided below. (For additional information, see the Call for Participation that was issued when this TC was formed.)

  1. Name of the TC

    LegalRuleML Technical Committee

  2. 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 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 modelling and reasoning such that implementers can structure, evaluate, and compare legal arguments constructed using the rule representation tools provided.

  3. Scope of Work

    The Artificial Intelligence (AI) and Law communities have converged in the last twenty years on modelling 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 modelling 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 modelling 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 modelling as well as representing and capturing the legal knowledge embedded in legal texts.

    Specifically, the LegalRuleML work will facilitate the following functionalities.

    1. Support for Modelling 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).
    2. 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.
    3. 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.
    4. 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.
    5. 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 modelling, 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.)

  4. Deliverables

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

    1. LegalRuleML semantic level (e.g. temporal dimension) drafts – within six months of the first TC meeting
    2. LegalRuleML logic level (e.g. defeasibility, deontic, and argumentation) drafts – within eight months of the first TC meeting
    3. LegalRuleML integration with business and process rule drafts – within ten months of the first TC meeting
    4. Pilot use cases – within twelve months of the first TC meeting
    5. 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.

  5. 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.

  6. 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 modelling 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.
  7. Language

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


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