Caractérisation et logique d'une situation collaborative

Initié en 2009, le projet MISE 2.0 (deuxième itération du projet Mediation Information System Engineering) s’articule autour d’une approche BPM (pour Business Process Management) et d’une vision MDE (pour Model-Driven Engineering). La réalisation d’une démarche BPM classique au sein d’une organisation nécessite de recueillir une connaissance couvrant à la fois les aspects structurel, informationnel et fonctionnel afin de définir des modèles de processus caractéristiques du comportement de l’organisation. Concernant le projet MISE 2.0, l’approche BPM considérée concerne un ensemble d’organisations collaboratives. Quant à la composante MDE, elle est destinée à faciliter l’automatisation des différentes étapes de la démarche : i) Recueil de la connaissance (caractérisation de la situation) : Il s’agit de collecter les information concernant la situation collaborative considérée, ii) Déduction de la cartographie de processus collaboratifs (définition de la solution) : il s’agit de définit les processus collaboratifs adaptés à la situation collaboratives caractérisée au niveau précedent and iii) Déploiement du SI de médiation (implémentation de la solution) : il s’agit d’implémenter le SI de médiation sous la forme d’une plateforme informatique capable d’orchestrer les processus collaboratif définis. La problématique scientifique relève des deux transitions entre ces trois niveaux d’abstractions : la première transition est prise en charge au niveau abstrait de la démarche MISE 2.0 alors que la seconde est traitée au niveau concret. Les travaux de thèse dont il est ici question se focalisent sur le niveau abstrait : déduction d’une cartographie de processus collaboratifs satisfaisant la situation collaborative considérée. Ce type d’objectif relève généralement d’activités entièrement manuelles qui nécessitent une importante quantité de travail afin d’obtenir les modèles de processus escomptés. Les travaux de recherches présentés ambitionnent d’automatiser cette démarche. Le principe est le suivant : (i) recueil, sous la forme de modèles, de la connaissance nécessaire à la caractérisation de la situation collaborative (informations sur les partenaires, les fonctions qu’ils partagent et leurs objectifs), (ii) déduction de la connaissance complémentaire relative à la dynamique collaborative qui pourrait satisfaire ces objectifs selon les moyens disponibles (cette phase s’appuie sur un métamodèle collaboratif, sur l’ontologie associée et sur des règles de transformation) et (iii) structuration de cette connaissance générée sous la forme d’une cartographie de processus collaboratifs (grâce à des algorithmes dédiés). ABSTRACT : MISE 2.0 (for Mediation Information System Engineering, second iteration) project has been launched in 2009. The MISE 2.0 engineering approach is based on BPM (Business Process Management) and MDE (Model-Driven Engineering). Running a regular BPM approach on a specific organization consists in gathering structural, informational, and functional knowledge in order to design cartography of processes covering the behavior of the modeled organization. Regarding the MISE 2.0 project the BPM approach concerns a set of organizations and MDE helps in automatizing the different steps: i) Knowledge gathering (situation layer): collect information concerning the collaborative situation, ii) Processes cartography design (solution layer): design the processes according to the knowledge gathered and iii) MIS deployment (implementation layer): implement an IT structure able to run the processes cartography. Both the transitions between these layers are the hard-points of this approach: The first gap is managed at the abstract level of MISE 2.0 while the second one is managed at the concrete level of MISE 2.0. The current PhD is focused on the first issue: designing a relevant processes cartography from the modeled collaborative situation. However, this is usually a manual activity, which requires a large amount of work to draw the processes and their links. The current research works aim at building such collaborative process cartography in an automated manner. Our principles are (i) to gather the essential and minimum initial collaborative knowledge (e.g. partners, shared functions and collaborative objectives) in models, ii) to deduce the missing knowledge with the help of a collaborative metamodel, an associated ontology and transformation rules and iii) to structure the deduced knowledge in a collaborative process cartography thanks to dedicated algorithms

Business and logic charateristic in an collaborative situation

MISE 2.0 (for Mediation Information System Engineering, second iteration) project has been launched in 2009. The MISE 2.0 engineering approach is based on BPM (Business Process Management) and MDE (Model-Driven Engineering). Running a regular BPM approach on a specific organization consists in gathering structural, informational, and functional knowledge in order to design cartography of processes covering the behavior of the modeled organization. Regarding the MISE 2.0 project the BPM approach concerns a set of organizations and MDE helps in automatizing the different steps: i) Knowledge gathering (situation layer): collect information concerning the collaborative situation, ii) Processes cartography design (solution layer): design the processes according to the knowledge gathered and iii) MIS deployment (implementation layer): implement an IT structure able to run the processes cartography. Both the transitions between these layers are the hard-points of this approach: The first gap is managed at the abstract level of MISE 2.0 while the second one is managed at the concrete level of MISE 2.0. The current PhD is focused on the first issue: designing a relevant processes cartography from the modeled collaborative situation. However, this is usually a manual activity, which requires a large amount of work to draw the processes and their links. The current research works aim at building such collaborative process cartography in an automated manner. Our principles are (i) to gather the essential and minimum initial collaborative knowledge (e.g. partners, shared functions and collaborative objectives) in models, ii) to deduce the missing knowledge with the help of a collaborative metamodel, an associated ontology and transformation rules and iii) to structure the deduced knowledge in a collaborative process cartography thanks to dedicated algorithms

An ontology-based collaborative business service selection: contributing to automatic building of collaborative business process

International audienceWith worldwide inter-enterprise collaboration and interoperability background, automatic collaborative business process deduction is a crucial researching subject. We have designed a methodology of deducing collaborative process by only collecting collaborative objectives and partners’ business services. The two key problems are (i) selecting corresponding business services for a set of collaborative objectives and (ii) ordering business services with serializations and parallelization. This paper aims to present a solution of business service selection and the following business process extraction. In order to solve the problem, we have defined a collaborative ontology, which contains numerous instances of business services and processes from the MIT process handbook. The collaborative ontology contains essential concepts in collaborative situations and process-deducing rules and algorithms. We provide a brief illustration of implementation within a SaaS toolkit called Mediator Modeling 2ool

Collaborative Knowledge Framework for Mediation Information System Engineering

With the worldwide interenterprise collaboration and interoperability background, automatic collaborative business process deduction is crucial and imperative researching subject. A methodology of deducing collaborative process is designed by collecting collaborative knowledge. Due to the complexity of deduction methodology, a collaborative knowledge framework is defined to organize abstract and concrete collaborative information. The collaborative knowledge framework contains three dimensions: elements, levels, and life cycle. To better define the framework, the relations in each dimension are explained in detail. They are (i) relations among elements, which organize the gathering orders and methods of different collaborative elements, (ii) relations among life cycle, which present modeling processes and agility management, and (iii) relations among levels, which define relationships among different levels of collaborative processes: strategy, operation, and support. This paper aims to explain the collaborative knowledge framework and the relations inside

A physics-based theory to navigate across risks and opportunities in the performance space: Application to crisis management

This article presents an original theory for system management, based on physics principles. That theory considers that risks and opportunity can be seen as forces pushing or pulling a system with regards to its objective and its KPIs. Based on that proposal, this article presents the theory, based on (i) identification of susceptibility of systems to internal and external characteristics (danger, favorable conditions), thus creating forces (risks and opportunities), and (ii) evaluation of the sensibility of systems to these forces, thus creating consequences (damages or benefits). This article also presents the practical vision of that theory by detailing the way to observe the force-inducted trajectory of the considered system with regards to its KPIs. An illustrative example and discussions about the perspectives conclude the article

A Tentative Framework for Risk and Opportunity Detection in A Collaborative Environment Based on Data Interpretation

This article deals with the question of risk and opportunity identification based on data management as one main step of the convergence of artificial intelligence and industrial engineering. Two main subjects are addressed in this article: (i) the data management framework that could be the backbone for the whole approach, and (ii) the modeling theoretical background that could be used as a basement for the definition of a formal system for risk and opportunity modeling. The general principles presented in the article are used to define outlooks and to organize them as milestone of a roadmap

An AI framework and a metamodel for collaborative situations: Application to crisis management contexts

Identifying, designing, deploying and maintaining accurate collaborative networks of organizations (e.g. responders in a crisis situation) are key activities in nowadays ecosystems. However, there is a lack regarding formal approaches dedicated to characterize collaborative networks of organizations. Formal descriptions of collaborative situations, that could be used, transformed, computed and exploited would be of great benefit for the quality of such collaborative networks. This article presents a model‐based AI framework for describing collaborative situations and the associated formal metamodel dedicated to be instantiated to characterize collaborative situations in a very wide range of application domains. This metamodel (describing collaborative situation between organizations) is structured according to four complementary dimensions: the context (social, physical and geographical environment), the partners (the involved organizations, their capabilities resources and relations), the objectives (the aims of the network, the goals to be the achieved and the risks to avoid, etc.) and the behaviour (the collaborative processes to be implemented by the partners to achieve the objectives in the considered context). Besides, this metamodel can be extended for some precise application domains. This article focuses on this mechanism in the specific context of crisis management

Business and logic charateristic in an collaborative situation

Initié en 2009, le projet MISE 2.0 (deuxième itération du projet Mediation Information System Engineering) s articule autour d une approche BPM (pour Business Process Management) et d une vision MDE (pour Model-Driven Engineering). La réalisation d une démarche BPM classique au sein d une organisation nécessite de recueillir une connaissance couvrant à la fois les aspects structurel, informationnel et fonctionnel afin de définir des modèles de processus caractéristiques du comportement de l organisation. Concernant le projet MISE 2.0, l approche BPM considérée concerne un ensemble d organisations collaboratives. Quant à la composante MDE, elle est destinée à faciliter l automatisation des différentes étapes de la démarche : i) Recueil de la connaissance (caractérisation de la situation) : Il s agit de collecter les information concernant la situation collaborative considérée, ii) Déduction de la cartographie de processus collaboratifs (définition de la solution) : il s agit de définit les processus collaboratifs adaptés à la situation collaboratives caractérisée au niveau précedent and iii) Déploiement du SI de médiation (implémentation de la solution) : il s agit d implémenter le SI de médiation sous la forme d une plateforme informatique capable d orchestrer les processus collaboratif définis. La problématique scientifique relève des deux transitions entre ces trois niveaux d abstractions : la première transition est prise en charge au niveau abstrait de la démarche MISE 2.0 alors que la seconde est traitée au niveau concret. Les travaux de thèse dont il est ici question se focalisent sur le niveau abstrait : déduction d une cartographie de processus collaboratifs satisfaisant la situation collaborative considérée. Ce type d objectif relève généralement d activités entièrement manuelles qui nécessitent une importante quantité de travail afin d obtenir les modèles de processus escomptés. Les travaux de recherches présentés ambitionnent d automatiser cette démarche. Le principe est le suivant : (i) recueil, sous la forme de modèles, de la connaissance nécessaire à la caractérisation de la situation collaborative (informations sur les partenaires, les fonctions qu ils partagent et leurs objectifs), (ii) déduction de la connaissance complémentaire relative à la dynamique collaborative qui pourrait satisfaire ces objectifs selon les moyens disponibles (cette phase s appuie sur un métamodèle collaboratif, sur l ontologie associée et sur des règles de transformation) et (iii) structuration de cette connaissance générée sous la forme d une cartographie de processus collaboratifs (grâce à des algorithmes dédiés).MISE 2.0 (for Mediation Information System Engineering, second iteration) project has been launched in 2009. The MISE 2.0 engineering approach is based on BPM (Business Process Management) and MDE (Model-Driven Engineering). Running a regular BPM approach on a specific organization consists in gathering structural, informational, and functional knowledge in order to design cartography of processes covering the behavior of the modeled organization. Regarding the MISE 2.0 project the BPM approach concerns a set of organizations and MDE helps in automatizing the different steps: i) Knowledge gathering (situation layer): collect information concerning the collaborative situation, ii) Processes cartography design (solution layer): design the processes according to the knowledge gathered and iii) MIS deployment (implementation layer): implement an IT structure able to run the processes cartography. Both the transitions between these layers are the hard-points of this approach: The first gap is managed at the abstract level of MISE 2.0 while the second one is managed at the concrete level of MISE 2.0. The current PhD is focused on the first issue: designing a relevant processes cartography from the modeled collaborative situation. However, this is usually a manual activity, which requires a large amount of work to draw the processes and their links. The current research works aim at building such collaborative process cartography in an automated manner. Our principles are (i) to gather the essential and minimum initial collaborative knowledge (e.g. partners, shared functions and collaborative objectives) in models, ii) to deduce the missing knowledge with the help of a collaborative metamodel, an associated ontology and transformation rules and iii) to structure the deduced knowledge in a collaborative process cartography thanks to dedicated algorithms.TOULOUSE-INP (315552154) / SudocSudocFranceF