The primary goal of the General Data Protection Regulation (GDPR) is to regulate the rights and duties of citizens and organizations over personal data protection. Implementing the GDPR is recently gaining much importance for legal reasoning and compliance checking purposes. In this work, we aim to capture the basics of GDPR in a well-founded legal domain modular ontology named OPPD (Ontology for the Protection of Personal Data). Ontology-Driven Conceptual Modeling (ODCM), ontology layering, modularization, and reuse processes are applied. These processes aim to support the ontology engineer in overcoming the complexity of the legal knowledge and developing an ontology model faithful to reality. ODCM is used for grounding OPPD in the Unified Foundational Ontology (UFO). Ontology modularization and layering aim to simplify the ontology building process. Ontology reuse focuses on selecting and reusing Conceptual Ontology Patterns (COPs) from UFO and the legal core ontology UFO-L. OPPD intends to overcome the lack of a representation of legal procedures that most ontologies encountered. The potential use of OPPD is proposed to formalize the GDPR rules by combining ontological reasoning and Logic Programming.

In this paper, we present an ontology-based liability decision support task in the international maritime law, specifically the domain of carriage of goods by sea. We analyze the liabilities of the involved legal agents (carriers and shippers) in case of loss or damage of goods. Thus, a well-founded legal domain ontology, named CargO-S, is used. CargO-S has been developed using an ontology-driven conceptual modeling process, supported by reusing foundational and legal core ontologies. In this work, we demonstrate the usability of CargO-S to design and implement a set of chained rules describing the procedural aspect of the liabilities legal rules. Finally, we employ these rules in a liability rule-based decision support task using a real case study.

The ontology engineering community is facing several key challenges about the development of domain ontologies. One major challenge is the building of well-founded domain ontologies. This concept has raised recently and it refers to ontologies that are grounded in validated foundational ontologies. This paper addresses the effective contribution of ontology-driven conceptual modeling process (ODCM) for developing such ontologies in the legal domain. A case study in the domain of carriage of goods by sea is presented.

International audience

International audience

This research aims to define an integrated strategy for modelling legal norms in the criminal domain for supporting the legal reasoning. For this purpose, OWL-DL criminal domain ontology is captured from legal texts, using a middle-out approach, and legal rules are then formalized based on the ontology. The goal is to construct a legal rule-based decision support system for the Lebanese criminal domain, grounded on the integration of the criminal domain ontology and set of logic rules which are defined using the expressive ability of SWRL rule language.

This article describes some tools to improve the foresight process and help the watchers to identify interesting information, in order to detect early warnings on threats or opportunities in open sources. A formal model of scenario is proposed to represent the expert knowledge about the potential situations in the environment and their links. The ontology Scenari Onto allows the scenario exploitation to collect interesting documents on the Web and presents them to the watchers for a manual analysis. A Graphic User Interface (GUI) component has been developed to build scenarios graphically. To exploit the capitalized knowledge, WebLab services have been developed. Finally, an experimentation has been set up to evaluate the system, showing encouraging results.

In this paper we describe an original computational model for solving different types of distributed constraint satisfaction problems (DCSP). The proposed model is called controller-agents for constraints solving (CACS). This model is intended to be used which is an emerged field from the integration between two paradigms of different nature: multi-agent systems (MAS) and the constraint satisfaction problem paradigm (CSP) where all constraints are treated in central manner as a black-box. This model allows grouping constraints to form a subset that will be treated together as a local problem inside the controller. Using this model allows also handling non-binary constraints easily and directly so that no translating of constraints into binary ones is needed. This paper presents the implementation outlines of a prototype of DCSP solver, its usage methodology and overview of the CACS application for timetabling problems.

Current research in autonomous agents and multi-agent systems (MAS) has reached a level of maturity sufficient enough for MAS to be applied as a technology for solving problems in an increasingly wide range of complex applications. Our aim in this paper is to define a simple, extendible, and formal framework for multi-agent cooperation, over which businesses may build their business frameworks for effecting cooperative business strategies using distributed multi-agent systems. It is a simple, fair and efficient model for orchestrating effecting cooperation between multiple agents.

The distributed constraint satisfaction problem (DCSP) which is an emerged field from the integration between two paradigms of different nature: multi-agent systems (MAS) that is characterized by the autonomy and the distribution of its entities and the constraint satisfaction problem paradigm (CSP) where all constraints are treated in central manner as a black-box. In this paper we aim to propose a model called controller-agents for constraints solving or CACS for short to be used for solving DCSP. We aim in this paper to present a model called CACS for (controller-agent for constraints solving). A controller role is to encapsulate and verify some constraints assigned to it. This model allows grouping constraints to form a subset that will be treated together as a local problem inside the controller. Using this model allows also handling non-binary constraints easily and directly so that no translating of constraints into binary ones is needed. Based on CACS, a prototype of DCSP solver is built. This paper presents the implementation outlines of that prototype and its usage methodology. The prototype is built in Java using general interfaces of both MAS and CSP platforms. These interfaces allow users to use the platforms of their choice providing that they implement these interfaces with the chosen platforms.

Multi-agent simulation has been looked as an efficient tool for urban dynamic traffic services. However, the main problem is how to build an agent-based model for it. This research presents a multi-agent based demand responsive transport (DRT) services model, which adopts a practical multi-agents planning approach for urban DRT services control that satisfies the main constraints: minimize total slack time, travel time, waiting time, clientpsilas special requests, and using minimum number of vehicle. In this paper, we propose an agent based multi-layer distributed hybrid planning model for the real-time problem which can solve this question. In the proposed method, an agent for each vehicle finds a set of routes by its local search, and selects a route by cooperation with other agents in its planning domain. By computational experiments, we examine the effectiveness of the proposed method.