P ORTOLAN: a Model-Driven Cartography Framework

Processing large amounts of data to extract useful information is an essential task within companies. To help in this task, visualization techniques have been commonly used due to their capacity to present data in synthesized views, easier to understand and manage. However, achieving the right visualization display for a data set is a complex cartography process that involves several transformation steps to adapt the (domain) data to the (visualization) data format expected by visualization tools. To maximize the benefits of visualization we propose Portolan, a generic model-driven cartography framework that facilitates the discovery of the data to visualize, the specification of view definitions for that data and the transformations to bridge the gap with the visualization tools. Our approach has been implemented on top of the Eclipse EMF modeling framework and validated on three different use cases

Model Driven Tool Interoperability in Practice

International audienceModel Driven Engineering (MDE) advocates the use of models, metamodels and model transformations to revisit some of the classical operations in software engineering. MDE has been mostly used with success in forward and reverse engineering (for software development and better maintenance, respectively). Supporting system interoperability is a third important area of applicability for MDE. The particular case of tool interoperability is currently receiving a lot of interest. In this paper, we describe some experiments in this area that have been performed in the context of open source modeling efforts. Taking stock of these achievements, we propose a general framework where various tools are associated to implicit or explicit metamodels. One of the interesting properties of such an organization is that it allows designers starting some software engineering activity with an informal light-weight tool and carrying it out later on in a more complete or formal context. We analyze such situations and discuss the advantages of using MDE to build a general tool interoperability framework

Inter-DSL coordination support by combining megamodeling and model weaving

Model-Driven Engineering (MDE) advocates the use of models at every step of the software development process. Within this context, a team of engineers collectively and collaboratively contribute to a large set of interrelated models. Even if the main focus can be on a single model (e.g. a class diagram model), related elements in other models (e.g. a requirement model) often have to be considered and/or accessed. Moreover, all the involved models do not necessarily conform to the same metamodel and thus may have been built using different independent DomainSpecific Languages (DSLs). Such a situation has already been frequently observed in many large-scale industrial deployments of MDE. Manually coordinating all the involved models, i.e. being able to both manage and use the links existing between them, can become a cumbersome and difficult task. As a proposal to solve this inter-DSL coordination issue, we introduce in this paper a generic and extensible inter-model traceability and navigation environment based on the complementary use of megamodeling and model weaving. We illustrate our solution with a concrete working example.status: publishe

Inter-dsl coordination support by combining megamodeling and model

Model-Driven Engineering (MDE) advocates the use of models at every step of the software development process. Within this context, a team of engineers collectively and collaboratively contribute to a large set of interrelated models. Even if the main focus can be on a single model (e.g. a class diagram model), related elements in other models (e.g. a requirement model) often have to be considered and/or accessed. Moreover, all the involved models do not necessarily conform to the same metamodel and thus may have been built using different independent Domain-Specific Languages (DSLs). Such a situation has already been frequently observed in many large-scale industrial deployments of MDE. Manually coordinating all the involved models, i.e. being able to both manage and use the links existing between them, can become a cumbersome and difficult task. As a proposal to solve this inter-DSL coordination issue, we introduce in this paper a generic and extensible inter-model traceability and navigation environment based on the complementary use of megamodeling and model weaving. We illustrate our solution with a concrete working example

Le jardinage urbain : le défi de la qualité des sols urbains pour les collectivités

International audienceUrban gardening is a booming trend. Local authorities are actively taking part in this movement in response to the demand of inhabitants but also because they see it as a way of addressing many of the challenges of the sustainable city. As a result, they are confronted with the issue of soil quality. Urban soils, as an environmental component, are rarely highlighted yet they are subjected to many constraints such as loss of agronomic potential or pollution. Based on experiments in Nantes, the article explores the process by which municipalities establish a diagnosis and intervene on soil quality, addressing the questions regarding the tools employed and the interactions with community gardeners. The approach adopted based on the landscape makes it possible to simultaneously address and, if necessary, establish the interrelations between the many challenges faced by communities in understanding urban soils, the skills required, and the difficulties in addressing the technical and political dimensions.Le jardinage urbain est aujourd’hui en plein essor. Les collectivités prennent part à cette dynamique pour répondre à la demande des habitants mais aussi parce qu’elles y voient une solution à de nombreux enjeux de la ville durable. De ce fait, elles sont confrontées à celui de la qualité des sols. Compartiment de l’environnement rarement mis en avant, les sols urbains sont en effet soumis à de nombreuses contraintes : perte de potentialités agronomiques ou pollutions. Basé sur des expériences nantaises, l’article explore le processus par lequel les villes établissent un diagnostic puis interviennent sur la qualité des sols, abordant à la fois les outils et les interactions avec les habitants-jardiniers. L’approche paysagère adoptée permet d’aborder conjointement, et le cas échéant de relier, les nombreux défis de l’appréhension des sols par les collectivités à la fois par les inconnues qui persistent sur les sols urbains, les compétences et enfin la difficulté à articuler les dimensions technique et politique

Data FAIRification in a cross-institutional governance framework : recommendations from the ANR-BRIDGE project

International audienceOpen science is a priority for the European Commission, fostering research data management policies and infrastructures. In France, the Second National Plan for Open Science aims to ensure that open science becomes a common and shared practice, encouraged by the entire international ecosystem of higher education, research, and innovation.One challenge is that French research is mainly organized into joint research units: within a same laboratory, project or publication datasets can be managed by different research organizations, necessitating choosing between several institutional and disciplinary data repositories that can cause data scattering.In addition to these repositories, the French Ministry of Research is building a national federated data repository: Recherche Data Gouv, as part of its Open Science Plan.In this context, three French research organizations, each maintaining an institutional data repository based on Dataverse software, initiated the BRIDGE project funded by the French National Research Agency following a special Open Science call..

Galaxy clustering in harmonic space from the dark energy survey year 1 data: compatibility with real-space results

ABSTRACT We perform an analysis in harmonic space of the Dark Energy Survey Year 1 Data (DES-Y1) galaxy clustering photometric data using products obtained for the real-space analysis. We test our pipeline with a suite of lognormal simulations, which are used to validate scale cuts in harmonic space as well as to provide a covariance matrix that takes into account the DES-Y1 mask. We then apply this pipeline to DES-Y1 data taking into account survey property maps derived for the real-space analysis. We compare with real-space DES-Y1 results obtained from a similar pipeline. We show that the harmonic space analysis we develop yields results that are compatible with the real-space analysis for the bias parameters. This verification paves the way to performing a harmonic space analysis for the upcoming DES-Y3 data

Integrating artificial intelligence into lung cancer screening: a randomised controlled trial protocol

Introduction Lung cancer (LC) is the most common cause of cancer-related deaths worldwide. Its early detection can be achieved with a CT scan. Two large randomised trials proved the efficacy of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk populations. The decrease in specific mortality is 20%–25%.Nonetheless, implementing LCS on a large scale faces obstacles due to the low number of thoracic radiologists and CT scans available for the eligible population and the high frequency of false-positive screening results and the long period of indeterminacy of nodules that can reach up to 24 months, which is a source of prolonged anxiety and multiple costly examinations with possible side effects.Deep learning, an artificial intelligence solution has shown promising results in retrospective trials detecting lung nodules and characterising them. However, until now no prospective studies have demonstrated their importance in a real-life setting.Methods and analysis This open-label randomised controlled study focuses on LCS for patients aged 50–80 years, who smoked more than 20 pack-years, whether active or quit smoking less than 15 years ago. Its objective is to determine whether assisting a multidisciplinary team (MDT) with a 3D convolutional network-based analysis of screening chest CT scans accelerates the definitive classification of nodules into malignant or benign. 2722 patients will be included with the aim to demonstrate a 3-month reduction in the delay between lung nodule detection and its definitive classification into benign or malignant.Ethics and dissemination The sponsor of this study is the University Hospital of Nice. The study was approved for France by the ethical committee CPP (Comités de Protection des Personnes) Sud-Ouest et outre-mer III (No. 2022-A01543-40) and the Agence Nationale du Medicament et des produits de Santé (Ministry of Health) in December 2023. The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations.Trial registration number NCT05704920