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International audience; 1. Neutral landscape models have many applications in ecology, such as supporting spatially-explicit simulations, developing, and evaluating landscape indices. However, current approaches provide few options to produce large landscapes with controlled composition and fragmentation indices. 2. We introduce flsgen (Fragmented Landscape Generator), a new neutral landscape generator that address this limitation by providing a high level of control over 14 landscape indices. The main novelty of flsgen is the decomposition of landscape generation into two steps: the solving of a constraint satisfaction problem and the generation of a landscape raster with a stochastic algorithm. The latter relies on a continuous environmental gradient that influences the landscape’s spatial configuration. 3. flsgen can generate fine-grained artificial landscapes in small amounts of time, which makes it suited to produce large landscape series systematically. We demonstrate the features of flsgen through three illustrative use cases. 4. flsgen is a practical and efficient tool that expand the current possibilities of neutral landscape models and widen their potential applications. To facilitate its uptake, flsgen is available as free and open-source software through a Java API, a command-line interface, or an R package.

International audience; In silico chromosome painting is a technique by which contributions of distinct genetic groups are represented along chromosomes of hybrid individuals. This type of analysis is used to study the mechanisms by which these individuals were formed. Such techniques are well adapted to identify genetic groups contributing to these individuals as well as hybridization events. It can also be used to follow chromosomal recombinations that occurred naturally or were generated by selective breeding. Here, we present GeMo, a novel interactive web-based and user-oriented interface to visualize in a linear-based fashion results of in silico chromosome painting. To facilitate data input generation, a script to execute analytical commands is provided and an interactive data curation mode is supported to ensure consistency of the automated procedure. GeMo contains preloaded datasets from published studies on crop domestication but can be applied to other purposes, such as breeding programs Although only applied so far on plants, GeMo can handle data from animals as well. Database URL: https://gemo.southgreen.fr/

International audience; CONTEXT: Coffee leaf rust (CLR) epidemics on Coffea arabica have led to severe socio-economic crises in Latin America starting in 2008. Until now, the scattered nature of scientific and empirical knowledge of the highly complex CLR-coffee pathosystem has been an obstacle to the development of CLR forecasting models. OBJECTIVE: To help prevent new severe epidemics, we built ExpeRoya, a qualitative model, based on a review of the scientific literature and expert opinion, to forecast the risk of a monthly increase in the incidence of CLR at plot and landscape levels. METHODS: We adopted the IPSIM (Injury Profile SIMulator) framework, a qualitative and aggregative modeling approach that describes the effects of the cropping system and the plot environment on injuries, thereby making it possible to incorporate scattered knowledge on the system and all its complexity in a simplified way. Involving experts makes this approach powerful and robust because it builds on empirical knowledge based on a very large number of field observations. We argue that broad expert knowledge provides more accurate information on the manifold interactions in the system than existing quantitative models can. The structure of ExpeRoya was discussed with coffee sector experts in 19 workshops and validated in an online survey with 17 CLR experts. RESULTS AND CONCLUSIONS: ExpeRoya successfully integrates in a simple way 229 multiple interactions that exist within the CLR-coffee pathosystem based on only 12 input variables easily acquired in the field: one incidence monitoring variable; two meteorological variables (temperature and rainfall), four crop management variables (management of shade cover, fungicide application, nutrition and pruning of coffee trees) and five coffee tree characteristics (dates of flowering, beginning and end of harvest, fruit load and cultivar genetic resistance). Coffee institutes in Honduras and Nicaragua now use ExpeRoya, hosted by the platform Pergamino (https://www.redpergamino.net/app-experoya), to assist them in preparing their monthly CLR warning bulletins for growers. ExpeRoya is an improved forecasting model of CLR by fully incorporating the main biophysical factors affecting CLR at the plot and landscape levels.SIGNIFICANCE: ExpeRoya is both a framework and a proof of concept that improves both forecasting and the comprehensive modeling of CLR. ExpeRoya is a powerful yet user-friendly model designed for all actors of the coffee sector, particularly smallholder farmers and extension agents. ExpeRoya is adaptable: users can modify the model according to advances in knowledge and/or their own expertise of the system. ExpeRoya can help prevent future socio-economic crises.

Functional–structural plant models (FSPMs) are powerful tools to explore the complex interplays between plant growth, underlying physiological processes and the environment. Various modelling platforms dedicated to FSPMs have been developed with limited support for collaborative and distributed model design, reproducibility and dissemination. With the objective to alleviate these problems, we used the Jupyter project, an open-source computational notebook ecosystem, to create virtual modelling environments for plant models. These environments combined Python scientific modules, L-systems formalism, multidimensional arrays and 3D plant architecture visualization in Jupyter notebooks. As a case study, we present an application of such an environment by reimplementing V-Mango, a model of mango tree development and fruit production built on interrelated processes of architectural development and fruit growth that are affected by temporal, structural and environmental factors. This new implementation increased model modularity, with modules representing single processes and the workflows between them. The model modularity allowed us to run simulations for a subset of processes only, on simulated or empirical architectures. The exploration of carbohydrate source–sink relationships on a measured mango branch architecture illustrates this possibility. We also proposed solutions for visualization, distant distributed computation and parallel simulations of several independent mango trees during a growing season. The development of models on locations far from computational resources makes collaborative and distributed model design and implementation possible, and demonstrates the usefulness and efficiency of a customizable virtual modelling environment.

The mobile application is an effective tool for data collection of performance in agriculture, particularly for small and geographically scattered farms. This study aimed to develop an economical and straightforward application to monitor small dairy herds performance with the flexibility to collect data remotely. The developed mobile application was designed using the MIT App Inventor. Where, the application explores icons of different farm management practices that are reported by farmers through touching the screen. Each icon is linked with an informative SMS, which was received by the mobile phone of the collection technician. We randomly selected and followed 18 farmers to test the application for one year. The main results were recognized the false SMS decreased as farmers took enough time for training in the software. Furthermore, most of sent SMS were for milk yield event. Age, level of education and land size had no significant effect on correct SMS sent by farmers, while herd size showed a significant effect. In Conclusion, mobile application could be developed for continuous data collection and following up small dairy farms in rural areas. Also, the validity test for the developed mobile application confirmed that farmers were able to use the new technology regardless their age and educational level.

In this article, firstly we briefly summarise the sud4science project and data collection (http://sud4science.org), ensuing processing/analysing stages, and the resulting corpus, 88milSMS (http://88milsms.huma-num.fr), through a synthesis of quotes and references to previous articles (§ 1). Secondly, we provide a state of the art on some research initiatives that use 88milSMS in various domains and frameworks, which will enable future cross-disciplinary insight (§ 2). Then, we present other usages of the 88milSMS corpus we identified through surveys (§ 3). Finally, we suggest future paths for textual data collection and analysis. Dans cet article, nous décrivons synthétiquement le projet sud4science et la collecte de données associée (http://sud4science.org), les étapes de traitement/analyse qui en découlent et le corpus en résultant, 88milSMS (http://88milsms.huma-num.fr). Nous donnons d'abord un aperçu des travaux réalisés dans le cadre de ce projet à travers quelques citations et références (§ 1). Ensuite, nous fournissons un état de l'art sur des initiatives de recherche s'appuyant sur 88milSMS qui s'inscrivent dans des domaines et cadres de travail variés, ce qui ouvre la voie à de nouvelles perspectives interdisciplinaires (§ 2). Puis, nous présentons d'autres usages du corpus 88milSMS que nous avons identifiés via un sondage (§ 3). Enfin, nous faisons quelques propositions pour la collecte et l’analyse de données textuelles.

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 44th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six fully revised and extended papers selected from the 35th conference on Data Management – Principles, Technologies and Applications, BDA 2019. The topics covered include big data, graph data streams, workflow execution in the cloud, privacy in crowdsourcing, secure distributed computing, machine learning, and data mining for recommendation systems.

BackgroundRice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci (QTL) discovery and molecular marker development. Comparative sequence analyses across QTL regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non-computer savvy rice researchers.FindingsWe adopted the Galaxy framework to build the federated Rice Galaxy resource, with shared datasets, tools, and analysis workflows relevant to rice research. The shared datasets include high density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from nine published rice genomes. Rice Galaxy includes tools for designing single nucleotide polymorphism (SNP) assays, analyzing genome-wide association studies, population diversity, rice-bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented.ConclusionsRice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science.

AGAP : équipe ID; International audience; Background: Exploring the structure of genomes and analyzing their evolution is essential to understanding theecological adaptation of organisms. However, with the large amounts of data being produced by next-generationsequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This isparticularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendlydata exploration solutions.Description: Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore largeamounts of genotyping data by filtering it not only on the basis of variant features, including functionalannotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalabilityproperties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. Inaddition, it provides a wide range of popular export formats.Conclusions: The Gigwa application is suitable for managing large amounts of genomic variation data. Itsuser-friendly web interface makes such processing widely accessible. It can either be simply deployed on aworkstation or be used to provide a shared data portal for a given community of researchers.

International audience; With the development of new technologies more and more information is stored in log files. Analyzing such logs can be very useful for the decision maker. One of the probably best known example is the Web log file analysis where lots of efficient tools have been proposed to extract the top-k accessed pages, the best users or even the patterns describing the behaviors of users on a Web site. These tools take advantages of the well-formed structures of the data. Unfortunately, logs files from the industrial world have very heterogeneous complex structures (e.g., tables, lists, data blocks). For experts, analyzing logs to find messages helping to better understand causes of a failure, if a problem have already occurred in the past or even knowing the main consequences of a failure is a hard, tedious, time-consuming and error-prone task. There is thus a need for new tools helping the experts to easily recognize the appropriate part in logs. Passage retrieval methods have proved to be very useful for extracting relevant parts in documents. In this paper we propose a new approach for automatically split logs files into relevant segments based on their logical units. We characterize the complex logical units found in logs according to their syntactic characteristics. We also introduce the notion of generalized vs-grams which is used to automatically extract the syntactic characteristics of special structures found in log files. Conducted experiments are performed on real datasets from the industrial world to demonstrate the efficiency of our proposal on the recognition of complex logical units.

Accès sur le site éditeur : http://aob.oxfordjournals.org/cgi/content/abstract/93/5/591; Background and Aims Physiological and architectural plant models have originally been developed for different purposes and therefore have little in common, thus making combined applications dif®cult. There is, however, an increasing demand for crop models that simulate the genetic and resource-dependent variability of plant geometry and architecture, because man is increasingly able to transform plant production systems through combined genetic and environmental engineering. d Model GREENLAB is presented, a mathematical plant model that simulates interactions between plant structure and function. Dual-scale automaton is used to simulate plant organogenesis from germination to maturity on the basis of organogenetic growth cycles that have constant thermal time. Plant fresh biomass production is computed from transpiration, assuming transpiration ef®ciency to be constant and atmospheric demand to be the driving force, under non-limiting water supply. The fresh biomass is then distributed among expanding organs according to their relative demand. Demand for organ growth is estimated from allometric relationships (e.g. leaf surface to weight ratios) and kinetics of potential growth rate for each organ type. These are obtained through parameter optimization against empirical, morphological data sets by running the model in inverted mode. Potential growth rates are then used as estimates of relative sink strength in the model. These and other `hidden' plant parameters are calibrated using the non-linear, least-square method. d Key Results and Conclusions The model reproduced accurately the dynamics of plant growth, architecture and geometry of various annual and woody plants, enabling 3D visualization. It was also able to simulate the variability of leaf size on the plant and compensatory growth following pruning, as a result of internal competition for resources. The potential of the model's underlying concepts to predict the plant's phenotypic plasticity is discussed.

International audience; : Background and AimsAutomatic acquisition of plant architecture is a major challenge for the construction of quantitative models of plant development. Recently, 3-D laser scanners have made it possible to acquire 3-D images representing a sampling of an object's surface. A number of specific methods have been proposed to reconstruct plausible branching structures from this new type of data, but critical questions remain regarding their suitability and accuracy before they can be fully exploited for use in biological applications.MethodsIn this paper, an evaluation framework to assess the accuracy of tree reconstructions is presented. The use of this framework is illustrated on a selection of laser scans of trees. Scanned data were manipulated by experienced researchers to produce reference tree reconstructions against which comparisons could be made. The evaluation framework is given two tree structures and compares both their elements and their topological organization. Similar elements are identified based on geometric criteria using an optimization algorithm. The organization of these elements is then compared and their similarity quantified. From these analyses, two indices of geometrical and structural similarities are defined, and the automatic reconstructions can thus be compared with the reference structures in order to assess their accuracy.Key ResultsThe evaluation framework that was developed was successful at capturing the variation in similarities between two structures as different levels of noise were introduced. The framework was used to compare three different reconstruction methods taken from the literature, and allowed sensitive parameters of each one to be determined. The framework was also generalized for the evaluation of root reconstruction from 2-D images and demonstrated its sensitivity to higher architectural complexity of structure which was not detected with a global evaluation criterion.ConclusionsThe evaluation framework presented quantifies geometric and structural similarities between two structures. It can be applied to the characterization and comparison of automatic reconstructions of plant structures from laser scanner data and 2-D images. As such, it can be used as a reference test for comparing and assessing reconstruction procedures.

Modelling plant structure and growth has undergone major changes in the last decades along two major lines: the integration of ecophysiological knowledge in process-based models which often lack a description of plant topology and geometry, and the generation of 3-D virtual plants using morphogenetic models which simulate the architectural development in a stable and homogeneous environment. There is now a trend to merge these two approaches, that is to link plant architecture and functioning. This trend is based on the recognition that plant structure: (i) is the joint output of the physiological processes (water and carbon balance, etc.) and the morphogenetic programme of the plant, (ii) determines the external environment of the trees which itself regulates their functioning (competition for space, light attenuation, etc.), and (iii) directly conditions the physiological processes within the tree (hydraulic structure, self shading, allocation of photosynthates, etc.). Such models can be used in agronomy and forestry in various ways: to investigate the effects, local and global, immediate and delayed, of the biophysical environment on plant morphogenesis and yield; to study light attenuation through the canopy, to analyse the transport of water and the allocation of photosynthates within the plant; to analyse the competitive interactions among different plants in the same stand; to calibrate remote sensing techniques and to visualize large landscapes. (Resume d'auteur)

Based on 10 years of participatory modeling experience, the authors developed a multilevel participatory modeling process that links national policy makers, local councils, and grassroots stakeholders using a combination of games and computerized simulations. The challenge was to allow the target groups to design and evaluate collective adaptations to climate change that combine new collective rules for local, regional, and national regulations. This article details and highlights the novelty of the methodological process, which allows stakeholders to codesign frameworks for their own behaviors and rules. The experiment uses games and models with soft rules and the stakeholders themselves incorporate their own perceptions both in the board and computerized games. This was shown to be an efficient way to reach assessments and proposals that are shared between local stakeholders and policy makers, and should thus help improve the design of policies to face up to climate changes.

International audience; The study of plant development requires increasingly powerful modeling tools to help understand and simulate the growth and functioning of plants. In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development. Previous implementations of this formalism were made based on static languages, i.e., languages that require explicit definition of variable types before using them. These languages are often efficient but involve quite a lot of syntactic overhead, thus restricting the flexibility of use for modelers. In this work, we present an adaptation of L-systems to the Python language, a popular and powerful open-license dynamic language. We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture. We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom.

Summary: We developed a controller that is compliant with the Chado database schema, GBrowse and genome annotation-editing tools such as Artemis and Apollo. It enables the management of public and private data, monitors manual annotation (with controlled vocabularies, structural and functional annotation controls) and stores versions of annotation for all modified features. The Chado controller uses PostgreSQL and Perl. Availability: The Chado Controller package is available for download at http://www.gnpannot.org/content/chado-controller and runs on any Unix-like operating system, and documentation is available at http://www.gnpannot.org/content/chado-controller-doc The system can be tested using the GNPAnnot Sandbox at http://www.gnpannot.org/content/gnpannot-sandbox-form Contact: valentin.guignon@cirad.fr; stephanie.sidibe-bocs@cirad.fr Supplementary information: Supplementary data are available at Bioinformatics online.

National audience; L’étude des systèmes complexes dynamiques est une problématique de plus en plus importante dans le cadre de l’activité scientifique. L’étude de tels systèmes nécessite fréquemment l’emploi d’un cadre de modélisation et de simulation avec des outils mathématiques etinformatiques suffisamment évolués pour prendre en compte la diversité de ces systèmes. En effet, l’une des particularités des systèmes complexes est que leur étude est interdisciplinaire et par conséquent, les paradigmes ou formalismes employés par les différentes communautés sonthétérogènes. Dans cet article, nous présentons une démarche de modélisation basée sur la théorie systémique et sur le formalisme à événements discrets DEVS qui supporte le couplage de modèles hétérogènes. Nous développons les bases théoriques de notre plate-forme VLE (VirtualLaboratory Environment) issue des travaux sur DEVS ainsi que ses caractéristiques techniques. Finalement, nous illustrons notre démarche sur deux exemples développés à l’aide de VLE.

Modular frameworks for crop modelling have evolved through simultaneous progress in crop science and software development but differences among these frameworks exist which are not well understood, resulting in potential misuse for crop modelling. In this paper we review differences and similarities among different developed frameworks and identify some implications for crop modelling. We consider three modelling frameworks currently used for crop modelling: CROSPAL (CROp Simulator: Picking and Assembling Libraries), APES (Agricultural Production and Externalities Simulator) and APSIM (Agricultural Production Systems sIMulator). The frameworks are implemented differently and they provide more or less flexibility and guidance, to facilitate assembly of crop model from model components. We underline the importance of systematic approaches to facilitate the selection of appropriate model structure and derive suggestions to facilitate it. We particularly stress the need for better documentation of the under- lying assumptions of the modules on simulated processes and on the criteria applied in the selection of these modules for a particular simulation objective. Such documentation should help to point out the sources of uncertainties associated with the development of crop models and to reinforce the role of the crop modeller as an intermediary between the software engineer, coding the modules, and the end users, agronomists or crop physiologists using the model for a specific objective. Finally, the key contribu- tions of modelling frameworks in the crop modelling domain are discussed and we draw conclusions for the prospects of such frameworks in the crop modelling field which should continue to reside on the prin- ciples of systems analysis but combined with up-to-date advances in software engineering techniques.

Les sciences qui traitent de la réalité, qu'elles soient naturelles, de la société ou de la vie, fonctionnent avec des modèles. Une partie de ces modèles décrivent les relations entre certaines grandeurs mesurables de la réalité, sans aller jusqu'au détail des interactions entre les éléments qui la composent. D'autres modèles décrivent ces interactions en prenant le point de vue des individus qui constituent le système, le comportement global n'est alors plus décrit à priori, mais observé à posteriori. Nous faisons le constat que dans les deux cas le scientifique a peu de liberté pour d'écrire les structures, en particulier spatiales, susceptibles de porter ces interactions. Nous proposons une approche de modélisation que l'on peut situer à mi-chemin entre les deux, et qui incite à étudier un système à travers la nature de ses interactions et des structures de graphes qui peuvent les porter. En plaçant au même niveau les relations spatiales, fonctionnelles, sociales ou hiérarchiques, nous tentons aussi de nous affranchir des contraintes induites par le choix effectué souvent à priori d'une forme de représentation de l'espace. Nous avons formalisé les concepts de base de cette approche, et ceux-ci ont constitué les éléments d'un langage métier, nommé Ocelet, que nous avons défini. Les outils permettant la mise en oeuvre de ce langage ont été développés et intégrés sous la forme d'un environnement de modélisation et de simulation. Enfin nous avons pu expérimenter notre nouvelle approche de modélisation et le langage Ocelet à travers la réalisation de plusieurs modèles présentant des situations variées de dynamiques paysagères.

A large amount of data is being produced by current genome sequencing projects. Sequence annotations and analyses need to be organized into databases and widely accessible. Like other species, sugarcane would benefit from centralized and innovative systems to study its genome. The GNPAnnot community annotation system (CAS) could be particularly relevant to the SUGESI sequencing project. It consists in a system for structural and functional annotations supported by comparative genomics allowing both automatic predictions and manual curations of genes and transposable elements. The core of the GNPAnnot CAS dedicated to tropical plants is made of GMOD components.The Chado database can be browsed using the Generic Genome Browser (GBrowse) which provides links to genome editors (ie. Artemis and Apollo). We developed the Chado controller in order to manage public and private annotation projects. It also provides an annotation history page for each gene or transposable element and an annotation inspector that automates several tasks and reports annotation mistakes. GNPAnnot CAS has already been used to annotate sugarcane BAC clones sequences and could be useful to facilitate the annotation of novel sugarcane sequences.

International audience; Among the world's living species, there are approximately 300,000 species of plants. Accurate knowledge of their identity, geographic distribution and use, underpins the success of the world sustainable agriculture with advanced research in agronomy, and biodiversity conservation. Unfortunately, the quality and quantity of plant information is poorest in the regions that could use it the most: Mediterranean and tropical countries. It's for this reason that plant identification, sharing of and access to plant information play a crucial but little understood role in modern society. In this context, Agropolis Fondation (http://www.agropolisfondation. fr/) is supporting its first Flagship Programme called Pl@ntNet. This programme involves a large international partnership jointly led by the AMAP Joint Research Unit (http://umramap.cirad.fr), the IMEDIA Research Team (http://www-rocq.inria.fr/imedia/), and the non-governmental organization Tela Botanica (http://www.tela-botanica.org/). The Pl@ntNet project aims to set up a web-oriented scientific, informative and educational software platform dedicated to plant identification and to the collaborative gathering, share and use of large, multi-disciplinary datasets on plants. Free, open-source, easy-access software programs, based Among the world's living species, there are approximately 300,000 species of plants. Accurate knowledge of their identity, geographic distribution and use, underpins the success of the world sustainable agriculture with advanced research in agronomy, and biodiversity conservation. Unfortunately, the quality and quantity of plant information is poorest in the regions that could use it the most: Mediterranean and tropical countries. It's for this reason that plant identification, sharing of and access to plant information play a crucial but little understood role in modern society. In this context, Agropolis Fondation (http://www.agropolisfondation. fr/) is supporting its first Flagship Programme called Pl@ntNet. This programme involves a large international partnership jointly led by the AMAP Joint Research Unit (http://umramap.cirad.fr), the IMEDIA Research Team (http://www-rocq.inria.fr/imedia/), and the non-governmental organization Tela Botanica (http://www.tela-botanica.org/). The Pl@ntNet project aims to set up a web-oriented scientific, informative and educational software platform dedicated to plant identification and to the collaborative gathering, share and use of large, multi-disciplinary datasets on plants. Free, open-source, easy-access software programs, based on previously developed prototypes will function on-line on internet, or directly in the field, and will be adapted to the various working conditions of potential users (natural resources managers, foresters, agronomists, teachers, scientists or citizens). Plant identification tools will be based on the use of morphological, ecological or geographical characters, as well as on visual image recognition system. As an initiative of major scientific and strategic importance, Pl@ntNet is expected to bring scientific breakthrough and demonstrate the degree and extent by which the know-how, expertise and competencies of various research units and their partners are mobilized and put into use in order to contribute in addressing major challenges of our time.

A stochastic model of growth and branching was developed in previous studies, and applied to apricot trees (#Prunus armeniaca# L.). Growth was considered as a succession of metamers, and modelled using a renewal process. Branching was studied through the series of branched or unbranched nodes. This paper presents complementary results obtained by applying the same model to various cultivars. Trees of "Rouge du Roussillon", "Modesto" and "Rose de Fournes", grafted on apricot clonal seedling "GF1236" and Plum "Brompton" were studied at two research stations. Similarities and differences are discussed, with comparison of the distribution of the total number of metamers per growth unit. (Resume d'auteur)

Dans le cadre du séquençage des génomes, divers systèmes d'annotation ont été développés tel que celui proposé par le projet international Generic Model Organism Database (GMOD). Le projet GNPAnnot a pour but de développer un système d'annotation communautaire (CAS) pour les plantes, les champignons et les insectes basé sur des composants GMOD. Le Chado Controller fait parti des apports du projet GNPAnnot qui complète le coeur du CAS GMOD: base de données Chado, navigateur de génome GBrowse et éditeur Apollo ou Artemis. Le Chado Controller qui permet de gérer la confidentialité, d'améliorer la qualité des annotations manuelles et de les tracer, comporte trois modules: la restriction des droits d'accès des utilisateurs aux "features", l'inspecteur et l'historique des annotations manuelles. Le module de restriction des droits d'accès permet non seulement de limiter l'accès d'un utilisateur à tout ou partie des données mais également de choisir son niveau d'accès (visualisation seulement ou modification). Pour améliorer la qualité des annotations, l'inspecteur emploie du vocabulaire contrôlé et facilite le travail de l'annotation manuelle en contrôlant le travail du curateur. Il rapporte les incohérence des annotations par rapport à des règles (e.g. structure incorrecte, propriété non ou mal renseignée) et met à jour automatiquement certains champs suite à l'enregistrement des modifications de l'annotateur (e.g. le nom de l'annotateur). Enfin, le module d'historique permet de garder une trace de toutes les modifications apportées aux annotations, quelque soit le type de "feature" (e.g. gène, élément transposable) modifiée et quelque soit l'éditeur utilisé. L'historique des annotations d'une "feature" peut être visualisé à l'aide d'une page Web. Le Chado Controller, destiné aux bases de données Chado (PostgreSQL), est principalement composé de scripts SQL embarqués dans la base, garantissant ainsi son contrôle global des données. Des parties secondaires du Chado Controller ont été intégrées aux outils GBrowse 1.70 (fenêtre de login, page d'historique) et Artemis (utilisation de l'inspecteur d'annotation). L'intégration de l'inspecteur à un logiciel comme Apollo est aussi simple que d'effectuer des requêtes SQL à partir de celui-ci. Enfin, le Chado Controller est rétro-compatible avec les outils existants et ses différents modules peuvent être activés ou désactivés indépendamment. Le Chado Controller du projet GNPAnnot est déjà utilisé sur six CAS installé sur la plate-forme South Green (plate-forme de bioinformatique montpelliéraine): sorgho, bananier, canne à sucre, palmier, cacaoyer et caféier. Il a déjà permis l'annotation manuelle de qualité, confidentiellement via le Web, de 964 gènes et de 479 éléments transposables (TE) qui peuvent être facilement exportée dans divers formats à l'aide d'un extracteur.

Agent-Based Models are useful to describe and understand social, economic and spatial systems' dynamics. But, beside the facilities which this methodology offers, evaluation and comparison of simulation models are sometimes problematic. A rigorous conceptual frame needs to be developed. This is in order to ensure the coherence in the chain linking at the one extreme the scientist's hypotheses about the modeled phenomenon and at the other the structure of rules in the computer program. This also systematizes the model design from the thematician conceptual framework as well. The aim is to reflect upon the role that a well defined ontology, based on the crossing of the philosophical and the computer science insights, can play to solve such questions and help the model building. We analyze different conceptions of ontology, introduce the 'ontological test' and show its usefulness to compare models. Then we focus on the model building and show the place of a systematic ABM ontology. The latter process is situated within a larger framework called the 'knowledge framework' in which not only the ontologies but also the notions of theory, model and empirical data take place. At last the relation between emergence and ontology is discussed.

International audience; The modelling of processes that occur in landscapes is often confronted to issues related to the representation of space and the difficulty of properly handling time and multiple scales. In order to investigate these issues, a flexible modelling environment is required. We propose to develop such a tool based on a Domain Specific Language (DSL) that capitalises on the service-oriented architecture (SOA) paradigm. The modelling framework around the DSL is composed of a model building environment, a code generator and compiler, and a program execution platform. The DSL introduces five language elements (entity, service, relation, scenario and datafacer) that can be combined to offer a wide range of possibilities for modelling in space and time at different scales. When developing a model, model parts are either built using the DSL or taken from libraries of previously built ones, and adapted to the specific model. The practical usage of the DSL is illustrated first with the Lotka-Volterra model, and then with a landscape modelling experiment on the spread of a mosquito-borne disease in the Sahelian region of West Africa. An interesting characteristic of this approach is the possibility of adding new elements into an existing model, and replacing others with more appropriate ones, thus allowing potentially complex models to be built from simpler parts.

International audience; As illustrated by the approaches presented during the 5th FSPM workshop (Prusinkiewicz and Hanan 2007, and this issue), the development of functional-structural plant models requires an increasing amount of computer modeling. All these models are developed by different teams in various contexts and with different goals. Efficient and flexible computational frameworks are required to augment the interaction between these models, their reusability, and the possibility to compare them on identical datasets. In this paper, we present an open-source platform, OpenAlea, that provides a user-friendly environment for modelers, and advanced deployment methods. OpenAlea allows researchers to build models using a visual programming interface and provides a set of tools and models dedicated to plant modeling. Models and algorithms are embedded in OpenAlea components with well defined input and output interfaces that can be easily interconnected to form more complex models and define more macroscopic components. The system architecture is based on the use of a general purpose, high-level, object-oriented script language, Python, widely used in other scientific areas. We briefly present the rationale that underlies the architectural design of this system and we illustrate the use of the platform to assemble several heterogeneous model components and to rapidly prototype a complex modeling scenario.

L'intelligence économique n'est pas née ex-nihilo, elle s'est progressivement structurée par l'évolution des réflexions menées par différentes équipes qui travaillaient dans des domaines connexes sur la gestion de l'information, et ce afin de répondre aux contraintes d'un environnement en perpétuelle évolution. Après une phase de développements compétitifs, l'ensemble de ces approches s'est coordonné en un corpus qui a pu, grâce à sa taille et à son homogénéité constituer une discipline actuellement objet d'enseignements en milieu universitaire. Cet ouvrage, récit d'un certain nombre de pères fondateurs , permet de prendre conscience de la diversité de ces approches, diversité qui en fait toute la complexité mais aussi toute la richesse. Sommaire : Hommage aux contributeurs. Préface A. Juillet. Introduction -J.-P. Bernat. Rassemblement des matériaux de base. Chapitre 1. Des sciences dures à la veille technologique et à l'intelligence économique -H. Dou. Chapitre 2. La réflexion stratégique et la naissance de nouveaux concepts -H. Lesca. Chapitre 3. Du renseignement à la désinformation -J.-P. Bernat. L'époque de la structuration. Chapitre 4. Des premières démarches en collecte de l'information à la naissance d'un réseau national d'intelligence économique -R. Guillaumot. Chapitre 5. Intelligence économique et problématique de puissance -C. Harbulot. L'apport de la dimension cognitive. Chapitre 6. La naissance de l'intelligence informationnelle -D. Bruté de Rémur. Chapitre 7. L'approche humaine : de l'appropriation de l'information à l'intelligence sociale -J. Girardin. Chapitre 8. Voyage dans l'archipel de la connaissance communautaire -P. Fayard, J.-P. Bernat. L'extension de la notion de réseau. Chapitre 9. Le concept du réseau et son efficacité -N. Moinet, C. Marcon. Chapitre 10. La dimension prospective et l'outil homme -S. Sisowath. Conclusion -J.-P. Bernat.