Éditeur(s) : HAL CCSD
Résumé : International audience
It is now well recognized that information management systems often deal with geographic information even if they often do not take advantage of it. In these systems, requirements engineering (RE) is becoming more and more important in helping stakeholders to model their requirements regarding the quality of the data.However, to date, few RE projects take geographic information and geographic constraints into account. We thus propose to study in this paper the question of managing such geographic constraints in the framework of RE. We propose an extension of the RE model and its implementation within the KAOS framework, and the use of geographic ontologies
2nd International Conference on Knowledge Management, Information and Knowledge Systems
Hammamet, Tunisia

lirmm-01230140
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01230140

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon. We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections. The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with people's way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3°C, mean incidence rates during epidemics could double. In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a step by step guide to model dengue spatial heterogeneity in other countries.
ISSN: 1935-2727

Droits : http://creativecommons.org/licenses/by/
pasteur-01247037
https://hal-riip.archives-ouvertes.fr/pasteur-01247037
https://hal-riip.archives-ouvertes.fr/pasteur-01247037/document
https://hal-riip.archives-ouvertes.fr/pasteur-01247037/file/journal.pntd.0004211.pdf
DOI : 10.1371/journal.pntd.0004211

Éditeur(s) : HAL CCSD Universidad de Malaga
Résumé : International audience
The development of information systems follows a long and complex process in which various actors are involved. We report an experiment in which we observe the evolution of the analysis model of an information system through 15 successive versions. We use indicators on the underlying concept lattices built by applying Relational Concept Analysis (RCA) to each version. RCA is an extension of FCA which groups entities based on characteristics they share, including links to other entities. It here helps in analyzing their evolution. From this experience, we establish recommendations to monitor and verify the proper evolution of the analysis process.
CLA'2012: 9th International Conference on Concept Lattices and Applications
Fuengirola (Málaga), Spain

ISBN : 978-84-695-5252-0
lirmm-00743886
http://hal-lirmm.ccsd.cnrs.fr/lirmm-00743886
http://hal-lirmm.ccsd.cnrs.fr/lirmm-00743886/document

Éditeur(s) : HAL CCSD
Résumé : International audience
Semantic web standards, tools, ontologies and related technologies have considerably matured in the recent years. Nowadays, accessing a wide catalogue of biological, social, environmental, and ecological data sources helps stakeholders working on biodiversity to answer their complex questions. Will the real time access to web resources effectively support the definition of strategies to conserve and manage biodiversity? How might semantic web technologies help us to handle the complex and heterogeneous big data related to biodiversity? The workshop aims to identify the key challenges faced by the bioinformatics community, discuss potential solutions and identify the opportunities emerging from the trans-disciplinary interactions between Plant Science and Informatics experts. Therefore, we expect the bioinformatics experts to explain how they apply semantic web standards and tools to their scientific topic, from biology, agriculture, agro-ecology, genomics, environmental studies, to social sciences, citizen sciences. Research papers presenting various aspects of semantic web technologies applied to biodiversity data, ranging from position papers to implemented systems descriptions and their evaluation, will be selected. We are particularly interested in the use of the semantic technologies to design and develop systems that supports research on agricultural and wild biodiversity conservation and management for food security. Examples may include strategies for resilience to climate change pressures, sustainability of productive ecosystems, ecosystems services monitoring or territories management, rather than systems supporting only research on climate patterns or soil erosion.
http://hal-lirmm.ccsd.cnrs.fr/lirmm-00831757

lirmm-00831757
http://hal-lirmm.ccsd.cnrs.fr/lirmm-00831757
http://hal-lirmm.ccsd.cnrs.fr/lirmm-00831757/document

Éditeur(s) : HAL CCSD
Résumé : Séminaire de Synthèse du Projet FPPSM "Forêts, Parcs, Pauvreté au Sud de Madagascar"
A Madagascar, la déforestation mobilise toutes les recherches, mais il manque encore une base de données complète, référencée et réactualisable sur les dynamiques forestières. Une solution est la valorisation d'images satellitaires multidates qui, de ce fait, sont issues de capteurs différents en termes de résolution spatiale, radiométrique et temporelle (Spot, Landsat, Modis). Ces données géolocalisées sont volumineuses, elles doivent être normalisées puis stockées et finalement traitées. Face à l'hétérogénéité des données et traitements, l'interopérabilité des ressources est assurée par le standard ISO (International Standard Organisation) et la spécification OGC (Open Geospatial Consortium). Le traitement de séries chronologiques de la couverture forestière exige un outil réutilisable qui s'adapte à de nouvelles données satellitaires : des chaînes de traitement pour les données simples, des workflows pour les gros volumes de données. La modélisation du workflow est illustrée par la construction de sa base de connaissance en utilisant un contexte de travail.
https://hal.archives-ouvertes.fr/hal-01370017

hal-01370017
https://hal.archives-ouvertes.fr/hal-01370017
IRD : fdi:010066424

Éditeur(s) : HAL CCSD
Résumé : International audience
Data integration and knowledge capitalization combine data and information coming from different data sources designed by different experts having different purposes. In this paper, we propose to assist the underlying model merging activity. For close models made by experts of various specialities on the same system, we partially automate the identification of a Greatest Common Model (GCM) which is composed of the common concepts (core-concepts) of the different models. Our methodology is based on Formal Concept Analysis which is a method of data analysis based on lattice theory. A decision tree allows to semiautomatically classify concepts from the concept lattices and assist the GCM extraction. We apply our approach on the EIS-Pesticide project, an environmental information system which aims at centralizing knowledge and information produced by different research teams.
14th International Conference on Enterprise Information Systems (ICEIS 2012)
Wroclaw, Poland

lirmm-01319858
http://hal-lirmm.ccsd.cnrs.fr/lirmm-01319858
DOI : 10.1007/978-3-642-40654-6_5

Éditeur(s) : HAL CCSD
Résumé : International audience
GEOBIA 2012
Rio de Janeiro, France

hal-01107866
https://hal.archives-ouvertes.fr/hal-01107866

Éditeur(s) : HAL CCSD
Résumé : LPSC14037
Scientific data collected with modern sensors or dedicated detectors exceed very often the perimeter of the initial scientific design. These data are obtained more and more frequently with large material and human efforts. A large class of scientific experiments are in fact unique because of their large scale, with very small chances to be repeated and to superseded by new experiments in the same domain: for instance high energy physics and astrophysics experiments involve multi-annual developments and a simple duplication of efforts in order to reproduce old data is simply not affordable. Other scientific experiments are in fact unique by nature: earth science, medical sciences etc. since the collected data is "time-stamped" and thereby non-reproducible by new experiments or observations. In addition, scientific data collection increased dramatically in the recent years, participating to the so-called "data deluge" and inviting for common reflection in the context of "big data" investigations. The new knowledge obtained using these data should be preserved long term such that the access and the re-use are made possible and lead to an enhancement of the initial investment. Data observatories, based on open access policies and coupled with multi-disciplinary techniques for indexing and mining may lead to truly new paradigms in science. It is therefore of outmost importance to pursue a coherent and vigorous approach to preserve the scientific data at long term. The preservation remains nevertheless a challenge due to the complexity of the data structure, the fragility of the custom-made software environments as well as the lack of rigorous approaches in workflows and algorithms. To address this challenge, the PREDON project has been initiated in France in 2012 within the MASTODONS program: a Big Data scientific challenge, initiated and supported by the Interdisciplinary Mission of the National Centre for Scientific Research (CNRS). PREDON is a study group formed by researchers from different disciplines and institutes. Several meetings and workshops lead to a rich exchange in ideas, paradigms and methods. The present document includes contributions of the participants to the PREDON Study Group, as well as invited papers, related to the scientific case, methodology and technology. This document should be read as a "facts finding" resource pointing to a concrete and significant scientific interest for long term research data preservation, as well as to cutting edge methods and technologies to achieve this goal. A sustained, coherent and long term action in the area of scientific data preservation would be highly beneficial.
http://hal.in2p3.fr/in2p3-00959072

in2p3-00959072
http://hal.in2p3.fr/in2p3-00959072
http://hal.in2p3.fr/in2p3-00959072/document
http://hal.in2p3.fr/in2p3-00959072/file/PREDON_Scientific_Data_Preservation_2014.pdf

Éditeur(s) : HAL CCSD SciTePress
Résumé : International audience
Data integration and knowledge capitalization combine data and information coming from different data sources designed by different experts having different purposes. In this paper, we propose to assist the underlying model merging activity. For close models made by experts of various specialities, we partially automate the identification of a Greatest Common Model (GCM) which is composed of the common concepts (core concepts) of the different models. Our methodology is based on Formal Concept Analysis which is a method of data analysis based on lattice theory. A decision tree allows to semi-automatically classify concepts from the concept lattices and assist the GCM extraction. We apply our approach on the EIS-Pesticide project, an environmental information system which aims at centralizing knowledge and information produced by different specialized teams.
ICEIS 2012: 14th International Conference on Enterprise Information Systems
Wroclaw, Poland

lirmm-00727009
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00727009

Éditeur(s) : HAL CCSD
Résumé : Given the technological development of embedded satellite sensors, the potential of available satellite images increases so that the question now arises of their most efficient exploitation possible. This is the purpose of the CARTAM-SAT project to fluidize the processing workflow from satellite images to users. The thesis is part of this framework.Processing operations relating to images have evolved over the years. Low-resolution images were processed by a so-called pixel approach while the high-resolution has allowed the development of a so-called object approach. The latter focuses on analysing not about the isolated pixels, but about groups of pixels representative of concrete objects on the ground. Thus, in principle, these are groups of pixels with a domain-specific remote sensing semantics.Along with satellite imagery, knowledge representation has evolved. The standards of representation have benefited from the expansion of the web to give rise to standards like OWL. This one is widely based on description logics that allow the use of automated reasoners able to infer implicit knowledge.This thesis is at the junction of these two sciences and provides an ontological approach for analysing satellite images. The aim is to formalize different types of knowledges and conceptualizations implicitly used by image processing programs and by remote sensing experts, and then reasoning automatically on an image description to obtain one semantic interpretation.This general principle may have numerous technical variations. The implementation consisted in a prototype combining a satellite image analysis library and an ontology-based reasoner. The implementation proposed in the thesis allows to explore four technical variations of the principle that lead to discussions on the complementarity of pixel and object analysis paradigms, the representation of some of the spatial relations and the role of knowledge in relation to processing.
Étant donnée l'évolution technologique des capteurs embarqués à bord des satellites, le potentiel d'images satellitaires accessible s'accroît de telle manière que se pose maintenant la question de son exploitation la plus efficace possible. C'est l'objectif du projet CARTAM-SAT que de fluidifier la chaîne de traitement depuis les satellites jusqu'aux utilisateurs des images. La thèse s'inscrit dans ce cadre. Les traitements relatifs aux images ont évolué au cours des années. Les images basse résolution étaient traitées par une approche dite pixel alors que la haute résolution a permis le développement d'une approche dite objet. Cette dernière s'attache à analyser non plus des pixels isolés, mais des groupes de pixels représentatifs d'objets concrets sur le terrain. Ainsi, en principe, ces groupes de pixels sont dotés d'une sémantique propre au domaine de la télédétection. La représentation des connaissances a évolué parallèlement aux images satellitaires. Les standards de représentation ont profité de l'expansion du web pour donner naissance à des standards comme OWL. Celui-ci repose en grande partie sur les logiques de description qui permettent l'utilisation de raisonneurs automatiques capables d'inférer une connaissance implicite.Cette thèse se place à la jonction de ces deux sciences et propose une approche ontologique d'analyse des images satellitaires. Il s'agit de formaliser différents types de connaissances et de conceptualisations implicitement utilisés par les logiciels de traitement d'image et par les experts en télédétection, puis de raisonner automatiquement sur la description d'une image pour en obtenir une interprétation sémantique.Ce principe général est susceptible de nombreuses déclinaisons techniques. La mise en œuvre a consisté en la réalisation d'un prototype alliant une bibliothèque d'analyse d'images satellitaires et un raisonneur basé sur les ontologies. L'implémentation proposée dans la thèse permet d'explorer quatre déclinaisons techniques du principe qui mènent à des discussions sur la complémentarité des paradigmes d'analyse pixel et objet, la représentation de certaines relations spatiales et la place de la connaissance par rapport aux traitements.
https://tel.archives-ouvertes.fr/tel-00998692

NNT : 2013MON20059
tel-00998692
https://tel.archives-ouvertes.fr/tel-00998692
https://tel.archives-ouvertes.fr/tel-00998692/document

Éditeur(s) : HAL CCSD InTech
Résumé : Le livre est en accès libre. The book is in open access
New Frontiers in Graph Theory

hal-00743343
https://hal.archives-ouvertes.fr/hal-00743343
DOI : 10.5772/35046