vgi4bio

Méthodes d’analyse des indicateurs de biodiversité dans le contexte agricole centrés données et utilisateurs VGI

ANR-17-CE04-0012

Mots clés : Agriculture; Biodiversité; Données participatives; Décision de group

Le projet a eu le soutien du Laboratoire Innovation Territoriale Grandes Cultures en Auvergne


La conservation de la biodiversité et sa relation avec les pratiques agricoles représente actuellement un défi majeur, car elle affecte les caractéristiques environnementales, sociales, économiques et autres activités humaines. Les données d’observation peuvent être nécessaires à grande échelle spatiale ou temporelle pour englober un large éventail de situations afin d’obtenir des résultats significatifs.

Cela implique que des centaines ou des milliers d’observateurs doivent être mobilisés, à un coût qui serait prohibitif s’ils devaient être payés. Par conséquent, dans ce projet, nous définirons un ensemble d’outils statistiques et de modèles de comportement d’observateurs pour extraire et visualiser des données précises et pertinentes à partir de la masse de données opportunistes (données Volunteer Geographic Information – VGI) afin de produire des indicateurs significatifs de la biodiversité.

De plus, comme les systèmes VGI ne fournissent pas d’outils d’analyses complexes, nous utiliserons l’OLAP spatial (SOLAP) pour analyser ces bio-indicateurs agricoles. Étant donné que les utilisateurs finaux sont différents et nombreux, nous définirons une nouvelle méthodologie de conception de participative pour l’implémentation des modèles SOLAP pour les bio-indicateurs agricoles.

Notre poster à AGILE 2018, Lund Suède, présente les thématiques de recherche abordées par le projet.

Visualisation cartographique à la volée pour les cubes OLAP pour les données d’agro-biodiversité

Un exemple d’implémentation en cours pour l’analyse des indicateurs de biodiversité en milieu agricole avec notre outil Spatial OLAP qui intègre des affichages cartographiques interactives au client OLAP Saiku

https://www.youtube.com/watch?v=Ww0LGj2iZwA&feature=youtu.be

Conception participatives des cubes OLAP pour les données d’agro-biodiversité

Plus de détails dans notre articles ER2018

The conservation of biodiversity currently represents a major challenge, since it impacts environmental, social, economical and other human activities features. Observation data may be needed at large spatial or temporal scales to encompass a wide range of situations in order to achieve meaningful results.

This implies that hundreds or thousands of observers need to be mobilized, at a cost which would be prohibitive if they had to be paid. Therefore, in this project we will define an R package offering a set of frequentist and bayesian statistical tools and observer behavior modeling to extract and visualize accurate and relevant data from the mass of opportunistic data (VGI data), in order to produce meaningful biodiversity indicators.

Moreover, since VGI systems do not provide advanced analysis tools, we will use Spatial OLAP to analyze those bioindicators. Since final users are different and numerous, we will define a new group decision-making SOLAP design methodology to implement Spatial OLAP models for bioindicators.

Projet PRCE (http://www.agence-nationale-recherche.fr/AAPG2017)

Challenge 1 « Gestion sobre des ressources et adaptation au changement climatique«

Application « Smart Monitoring » de l’axe 4 “Innovations scientifiques et tech.

Orientation 1 “Suivi intelligent du système terre

Budget 431 000 Eur

Durée 48 mois

Début: 1 Décembre 2017


Partners

Coordinateur: Irstea, TSCF, Clermont Ferrand

Responsable: Sandro Bimonte

The Technologies and Information Systems for Agricultural System (TSCF) research unit consists of 5 teams and a total of 70 agents across 3 sites: the Cézeaux University Science Center in Clermont Ferrrand (63), the Research and Experimentation Site in Montoldre (03) and the Irstea Center in Antony (92). The research unit uses the engineering sciences in addition to information and communication sciences and technologies to conduct research on methods and tools used to design agricultural environmental systems. It also

conducts research, tests and appraisals on the safety and performance of agricultural equipment to help improve safety in agriculture and reduce agricultural pollution. Thanks to its technological research, TSCF provides concrete solutions for eco-friendly, productive agriculture and environmental management.

Membres:

  • Sandro Bimonte

  • Francois Pinet

  • Geraldine André

  • Lucile Sautot

  • Frederic Archaux

  • Firdaous El Guennouni (financé par CAP2025, Université Clermont)

  • Hifdi Yassine (financé par CAP2025, Université Clermont)

IRIT

The IRIT (Institut de Recherche en Informatique de Toulouse – Toulouse Institute of Computer Science Research) represents one of the major potential of the French research in computer science, with a workforce of more than 600 members including 250 researchers and teachers 244 PhD students, 14 post-doc and researchers under contract and also 43 engineers and administrative employees.

Membres:

  • Pascale Zaraté

  • Guy Camilleri

  • Amir Sakka (Doctorant 2018-2021)

CESCO

The Centre d’Ecologie et des Sciences de la Conservation (CESCO, UMR 7204, MNHN) focuses on the ecological foundations of biodiversity management and conservation biology, mobilizing evolutionary, ecological and interdisciplinary approaches with social sciences (politics, management , psychology). All components of biodiversity are targeted, from rare and charismatic to common species. A large part of this research is based on data collected by volunteers in several biodiversity monitoring schemes managed by the CESCO team. As such, CESCO is the leading French research organization on biodiversity-oriented citizen sciences.

Membres:

  • Benoit Fontaine

  • Romain Juillard

  • Emmanuelle Porcher

  • Rose-Line Preud’homme

  • Karine Princé

  • Ali Hassan (Ing. 2018)

  • Iandry RAKOTONIAINA (Ing. 2018-2019)

LPO

LPO Aquitaine is a local NGO, dedicated to preserving biodiversity. We are working on three axes: Knowledge and expertise, Protection of species and habitats, and Valorization of the action towards all publics. In particular, LPO AQUITAINE strives to explore the field of participatory sciences through collaborative web tools and to collaborate with research laboratories (MNHN, INRA, CNRS, etc.). We wish to go further and further in the association of citizens, and the scentific valorisation of the data they produce.

Membres:

  • Laurent Couzi

  • Aurélien Besnard

GEOSYSTEMS France

GEOSYSTEMS France SARL is a private company created in 2006 by Patrice Lemire with the purpose: to provide a quality and proximity technological response to the geomatic and non geomatic communities, more particularly to users who are looking for solutions to acquire, measure, analyze, and present geospatial data for informed decision making. GEOSYSTEMS France offers the best solutions to accompany clients on all stages of the geospatial data life cycle: (1) HEXAGON GEOSPATIAL software such as ERDAS IMAGINE for imagery processing, ERDAS APOLLO for big data cataloguing and publishing, Smart M.Apps for cloud web mapping and processing and other software including mobile applications and Web GIS solutions; (2) eCognition solutions dedicated to the interpretation of images at any scale; (3) LP360 for ArcGIS, an extension for LIDAR data users in an ArcGIS environment; (4) Leica Geosystems mobile GNSS GPS for GIS; (5) and more recently a complete offer for DRONES workflows.

Membres:

  • Elodie Edoh-Alove

  • Patrice Lemire

Publications, data, tools

Pubblications

  1. Sandro Bimonte, Ali Hassan, Lucile Sautot: Entreposage et analyse en ligne des données de biodiversité. Atelier DEMO, SAGEO 2017, 6 Novembre 2017, ROUEN, France

  2. Bimonte, S. Besnard, A., Edoh-Alove, E., Hassan, A., Prince, K., Sakka, A., Zarate, P. VGI users & data centered methods for the analysis of farmland biodiversity indicators open issues. AGILE 2018, AGILE 2018 – Lund, June 12-15, 2018

  3. Vincenzo Del Fatto, Sandro Bimonte, Ali Hassan, Monica Sebillo:
    A Preliminary Study of Metrics and Methods for Readable Spatial OLAP Maps: VGI4Bio Case Study. IV 2018: 303-308

  4. Sandro Bimonte, Amir Sakka, Lucile Sautot. 2018. From crowdsourced requirements to analysis of VGI data: Open issues. Inforsid 2018 workshop Data Intelligence

  5. Sandro Bimonte, Amir Sakka, Lucile Sautot. 2018. A new methodology for Elicitation of Data Warehouse Requirements based on the Pivot Table Formalism. EDA18, Tanger Maroc

  6. Amir Sakka, Sandro Bimonte, Lucile Sautot, Guy Camilleri, Pascale Zaraté, Aurelien Besnard: A Volunteer Design Methodology of Data Warehouses. ER 2018: 286-300

  7. Sakka, A., Bimonte, S., Zaraté, P., Camilleri, G., Sautot, L., Besnard, Résolution collaborative des conflits des besoins d’analyse OLAP Spatial des données issues des observatoires citoyens. SAGEO 2018, Montpellier, France, p.77-82

  8. Bimonte, S. S. Rizzi, Sautot, L., Fontaine, B. Volunteered multidimensional design to the test: The Farmland Biodiversity VGI4Bio project’s experiment. DOLAP2019

  9. Porcher E, Vermeersch R.L., Billaud O, Pinard C. 2019. Observer pour comprendre les interactions de la biodiversité avec les pratiques agricoles : premiers résultats de l’Observatoire Agricole de la Biodiversité. Innovations Agronomiques, volume 75 (to appear)

  10. Princé, K., Coron, C., Fontaine, B., Porcher, E. Capitalizing on opportunistic data to refine bird population estimates. Bird Numbers 2019 Conference, 8-13 Avril 2019, Évora, Portugal

  11. Sakka, A., Bosetti, G., Grigera, J., Camilleri, G., Fernández, A., Zaraté, P., Bimonte, S., Sautot, L.
    UX Challenges in GDSS: An Experience Report. GDN 2019: 67-79

  12. SAUTOT, L., BIMONTE, S., JOURNAUX. A semi-automatic design methodology for Data Warehouse and Big Data Warehouse transforming facts into dimensions. Transactions on Knowledge and Data Engineering (To appear)

  13. Bimonte, S., Pinet. F. Une nouvelle méthodologie pour l’anonymisation des entrepôts de données spatiales : application aux données debiodiversité dans le contexte agricole. EDA 2019. Revue des Nouvelles Technologies de l’Information vol.RNTI-B-15, pp.15-30

  14. Edoh-Alove, E., Besnard, A., Brenon, C., Bimonte, S., Fontaine, B., Hassan, A., Hifdi, Y., Preud’homme, R., Rakotoniaina, I., Sakka, A. Analyse en ligne des données de biodiversité en milieu agricole. SAGEO 2019

  15. Bimonte, S., Hifdi, Y., Maliari, M., Rizzi S , Patrick M. To Each His Own: Accommodating Data Variety by a Multimodel Star Schema. DOLAP 2020

  16. Deguines, N., Princé, K., Prévot, A-C., Fontaine, B. Assessing the emergence of pro-biodiversity practices in citizen scientists of a backyard butterfly survey. Science of The Total Environment (To appear)

  17. Bimonte, S., L. Antonelli, S., Rizzi. Requirement-Driven Data Warehouse Design Based on Enhanced Pivot Tables. Journal Requirements Engineering (To appear)

  18. Bimonte, S. Volunteer design of Data Warehouse (Tutorial). CAISE 2020

  19. Bimonte, S., Ren, L., Koueya, N. A linear programming-based framework for handling missing data in multi-granular data warehouses. Data & Knowledge Engineering (To appear)

  20. Plazas, J., Bimonte, S., Schneider, M., de Vaulx, C., Corrales, J. C.. A New Design Methodology for Self-Service Business Intelligence over On-Demand IoT Data. 24th European conference on Advances in Databases and Information Systems (ADBIS 2020) (To appear)

  21. Bimonte S., Flouvat, F., Fontaine, B., Hassan, A., Rouillier, N., Billaud, O. Collect and analysis of agro-biodiversity data in a participative context: A Business Intelligence Framework. Ecological Informatics (To appear)

  22. Julián Eduardo Plazas, Sandro Bimonte, Christophe de Vaulx, Michel Schneider, Quang-Duy Nguyen, Jean-Pierre Chanet, Hongling Shi, Kun Mean Hou, Juan Carlos Corrales:
    A Conceptual Data Model and Its Automatic Implementation for IoT-Based Business Intelligence Applications. IEEE Internet Things J. 7(10): 10719-10732 (2020)

  23. Bimonte, S., Gallinucci, E., Marcel, P., Rizzi, S. Data Variety, Come As You Are in Multi-model Data Warehouses. Information Systems (to appear)

  24. Sakka, A., Bimonte, S., Rizzi, S., Sautot, L., Pinet, F., Bertolotto, M., Besnard, A., Rouillier, N. A profile-aware methodological framework for collaborative multidimensional modeling. Data & Knowledge Engineering Journal (to appear)

  25. Sakka, A., Bimonte, S., Sautot, L., Pinet, F. Volunteer Data Warehouse: State of Art. International Journal of Data Warehousing and Mining (to appear)

  26. Princé, Karine, Calenge Clément, Giraud Christophe, Julliard Romain. Le « quality data » pour calibrer le « big data » : application aux suivis de biodiversité. (in review)

  27. Bimonte, S., Edoh-Alove, E., Coulibaly, A.F. Map4OLAP: A web-based tool for interactive map visualization of OLAP queries. Workshop Big Spatial Data 2021 at 2021 IEEE International Conference on Big Data 2021 (Demo paper)

Tools

  • ProtOLAP. ProtOLAP: a software for automatic generation of Postgres SQL and XML Mondrian from UML profile ICSOLAP with Magic Draw 19.0 Download here

  • Map4OLAP.Map4OLAP: A web-based tool for interactive map visualization of OLAP queries. A video here

Data

  • Multi-Model Data Warehouse dataset Download here

  • All Data Warehouses developped are available here