Towards a Semantic-based Approach for Modeling Regulatory Documents in Building Industry

Regulations in the Building Industry are becoming increasingly complex and involve more than one technical area. They cover products, components and project implementation. They also play an important role to ensure the quality of a building, and to minimize its environmental impact. In this paper, we are particularly interested in the modeling of the regulatory constraints derived from the Technical Guides issued by CSTB and used to validate Technical Assessments. We first describe our approach for modeling regulatory constraints in the SBVR language, and formalizing them in the SPARQL language. Second, we describe how we model the processes of compliance checking described in the CSTB Technical Guides. Third, we show how we implement these processes to assist industrials in drafting Technical Documents in order to acquire a Technical Assessment; a compliance report is automatically generated to explain the compliance or noncompliance of this Technical Documents

Challenges in the specification of full contracts

Partially supported by the Nordunet3 project “COSoDIS”.The complete specification of full contracts - contracts which include tolerated exceptions, and which enable reasoning about the contracts themselves, can be achieved using a combination of temporal and deontic concepts. In this paper we discuss the challenges in combining deontic and other relevant logics, in particular focusing on operators for choice, obligations over sequences, contrary-to-duty obligations, and how internal and external decisions may be incorporated in an action-based language for specifying contracts. We provide different viable interpretations and approaches for the development of such a sound logic and outline challenges for the future.peer-reviewe

Legal compliance by design (LCbD) and through design (LCtD) : preliminary survey

1st Workshop on Technologies for Regulatory Compliance co-located with the 30th International Conference on Legal Knowledge and Information Systems (JURIX 2017). The purpose of this paper is twofold: (i) carrying out a preliminary survey of the literature and research projects on Compliance by Design (CbD); and (ii) clarifying the double process of (a) extending business managing techniques to other regulatory fields, and (b) converging trends in legal theory, legal technology and Artificial Intelligence. The paper highlights the connections and differences we found across different domains and proposals. We distinguish three different policydriven types of CbD: (i) business, (ii) regulatory, (iii) and legal. The recent deployment of ethical views, and the implementation of general principles of privacy and data protection lead to the conclusion that, in order to appropriately define legal compliance, Compliance through Design (CtD) should be differentiated from CbD

FLACOS’08 Workshop proceedings

The 2nd Workshop on Formal Languages and Analysis of Contract-Oriented Software (FLACOS’08) is held in Malta. The aim of the workshop is to bring together researchers and practitioners working on language-based solutions to contract-oriented software development. The workshop is partially funded by the Nordunet3 project “COSoDIS” (Contract-Oriented Software Development for Internet Services) and it attracted 25 participants. The program consists of 4 regular papers and 10 invited participant presentations

PriCL: Creating a Precedent A Framework for Reasoning about Privacy Case Law

We introduce PriCL: the first framework for expressing and automatically reasoning about privacy case law by means of precedent. PriCL is parametric in an underlying logic for expressing world properties, and provides support for court decisions, their justification, the circumstances in which the justification applies as well as court hierarchies. Moreover, the framework offers a tight connection between privacy case law and the notion of norms that underlies existing rule-based privacy research. In terms of automation, we identify the major reasoning tasks for privacy cases such as deducing legal permissions or extracting norms. For solving these tasks, we provide generic algorithms that have particularly efficient realizations within an expressive underlying logic. Finally, we derive a definition of deducibility based on legal concepts and subsequently propose an equivalent characterization in terms of logic satisfiability.Comment: Extended versio

Semi-Automated Methods for Measuring Practice Conformance for Capital Projects

The goal of this thesis is to explore semi-automated methods for measuring practice conformance for capital projects. Thorough measurement of practice conformance for capital projects typically requires manual audits. Surveys that may assist can often be subjective, non-repeatable and unverifiable, since they are self-reported. However, some of the tasks assigned to auditors are also non-repeatable, and they may be costly, time-consuming, tedious, and error-prone. Tools for assisting practice conformance measurements are in high demand in the construction domain. In response, various information technology-based and web deployed Benchmarking and Metrics (BM&M) programs have been introduced to reduce time and costs, to assist in providing repeatable and accurate results, and to increase efficiency and productivity of reporters and auditors. Moreover, moves toward automated practice conformance measurement are expected to reduce time and cost. Past studies have also resulted in significant advances in data mining, natural language processing, machine learning, computer vision and other artificial intelligence-based approaches toward complete automation, but technical limitations exist that constrain complete automation or make it impractical. An approach is needed to support practical, net beneficial, incremental steps toward automation of practice conformance measurement for capital projects that would assist capital project participants to improve project performance over time. To address this need, a new approach is proposed in this thesis. Additionally, a framework to beneficially increase automation is presented. Toolsets are explored that may make practice conformance measurement cheaper, faster, easier, repeatable, and more accurate for capital project participants. This framework and the toolsets are validated through the development of a practice conformance model, case studies on real project data, and application experiments. It is concluded that the proposed semi-automated framework for measuring practice conformance for capital projects is practical to implement in the near term. These results provide a basis on which capital project participants can implement efficacious practice conformance measurement to support capital project performance improvement programs

An Automated Framework for the Extraction of Semantic Legal Metadata from Legal Texts

Semantic legal metadata provides information that helps with understanding and interpreting legal provisions. Such metadata is therefore important for the systematic analysis of legal requirements. However, manually enhancing a large legal corpus with semantic metadata is prohibitively expensive. Our work is motivated by two observations: (1) the existing requirements engineering (RE) literature does not provide a harmonized view on the semantic metadata types that are useful for legal requirements analysis; (2) automated support for the extraction of semantic legal metadata is scarce, and it does not exploit the full potential of artificial intelligence technologies, notably natural language processing (NLP) and machine learning (ML). Our objective is to take steps toward overcoming these limitations. To do so, we review and reconcile the semantic legal metadata types proposed in the RE literature. Subsequently, we devise an automated extraction approach for the identified metadata types using NLP and ML. We evaluate our approach through two case studies over the Luxembourgish legislation. Our results indicate a high accuracy in the generation of metadata annotations. In particular, in the two case studies, we were able to obtain precision scores of 97.2% and 82.4% and recall scores of 94.9% and 92.4%