Visite École des Mines de Saint-Étienne

12 février 2018, Clermont-Ferrand

Nous accueillons plusieurs invités :

  • Omar Alqawasmeh - 2nd yr Ph.D. candidate EMSE
  • Noorani Bakerally - 3rd yr Ph.D. candidate ANR OpenSensingCity EMSE
  • Olivier Boissier - Professeur des Mines
  • Raúl García-Castro de l'Ontology Engineering Group de l'Universidad Politécnica de Madrid,
  • Maxime Lefrançois - Maître Assistant École des Mines de Saint-Étienne (EMSE),
  • Antoine Zimmermann - Maître Assistant de l'EMSE.

Présents

  • Tayeb Abderrahmani Ghorfi - 1st yr Ph.D. candidate TSCF/LIPN
  • Jean-Pierre Chanet - IR Directeur du laboratoire TSCF
  • Kun Mean Hou - Prof Limos délégation à TSCF
  • Myoung-Ha Kang - MCF Limos
  • Quang Duy Nguyen - 2nd yr Ph.D. candidate TSCF
  • François Pinet - DR animateur de l'équipe Copain
  • Catherine Roussey - CR équipe Copain

Localisation et Horaire

  • Salle C0-Chambon de 9H30 à 14H (batiment C au rez de chaussée)
  • Salle C1-Aydat de 14H à 18H (batiment C au premier étage)

Programme

09H30: Accueil

Café du matin en attendant nos invités

10H00: Presentation de TSCF, de l'équipe Copain et de l'AgroTechnoPole

Francois Pinet - Dr Irstea

Au sein de laboratoire Technologies et Systèmes d’information pour les agrosystèmes - Clermont-Ferrand (TSCF), l'équipe COPAIN travaille sur les systèmes d’information communicants et agri-environnementaux. Il s'agit d'une équipe de 17 personnes, incluant 7 docteurs (4 HDR). AgroTechnoPole: Irstea experimental farm located at Montoldre.

10H15: Presentation of the Connected Intelligence team of the Laboratoire Hubert Curien (10 minutes)

Olivier Boissier - Professeur des Mines

10H30: Knowledge base engineering method from alignements between reference ontologies: agricultural use case based on french alert bulletins

Tayeb Abderrahmani Ghorfi - 1st yr Ph.D. candidate TSCF/LIPN

Semantic Web provides methods and techniques for modeling, formalizing and acquiring knowledge from heterogeneous source of data. In this presentation, I will introduce our methodology for the construction of knowledge bases in the agricultural domain in order to detect agricultural alerts. I will present in particular the annotation process of the “Bulletin de santé du végétal” which is an archive of agricultural alert bulletins already published on the LOD, i will present also some semantic resources dealing with the field of agriculture and necessary for our method , and finally the use of SOSA ontology to depict crop plot.

References

  • H. ZARGAYOUNA, C. ROUSSEY, S. OUARDANI. Annotation sémantique à partir de textes : Cas des observations dans les Bulletins de Santé du végétal. Dans les actes du 9es atelier Recherche d'Information SEmantique (RISE 2017) adossé à la conférence IC 2017 de la Plateforme Francophone d'Intelligence Artificielle, 4 juillet 2017, Caen, 8 pages
  • F. AMARGER, J-P. CHANET, O. HAEMMERLE, N. HERNANDEZ, C. ROUSSEY. Knowledge Engineering Method Based on Consensual Knowledge and Trust Computation : the MUSKA System. In Proceedings of 22nd International Conference on Conceptual Structures (ICCS 2016) 5-7 july 2016, Annecy, France. LNAI 9717 Graph Based representation and Reasoning p 177-190. http://link.springer.com/chapter/10.1007/978-3-319-40985-6_14
  • C. ROUSSEY, J-P CHANET, V. CELLIER, F AMARGER. Agronomic Taxon. In Proceedings of second international Workshop on Open Data (WOD 2013), 3 june 2013, BNF Paris.

11H00: Adaptability and robustness of wireless sensors network protocols in a agro-environmental monitoring system

Quang Duy Nguyen - 2nd yr Ph.D. candidate TSCF

In the last decade, the Internet of Things (IoT) is known as one of the most appealing technology trend in the research world. IoT covers many application domains such as smart home, smart city, health-care, environment and agriculture. Using IoT technologies in agriculture domain enable to build agricultural decision systems that manage agricultural services like irrigation system. These systems are solutions to increase productivity, enhance yield and reduce environmental footprint. This presentation addresses to 4 agriculture IoT platforms/frameworks in order to overview the contributions of IoT in high-tech agriculture system.

References

  • J. SUN, G. DE SOUSA, C. ROUSSEY, J-P. CHANET, F. PINET, K.-M. HOU. A New Formalisation for Wireless Sensor Network Adaptive Context-aware System: Application to an Environmental Use Case. In Proceedings of the Tenth International Conference on Sensor Technologies and Applications SENSORCOMM 2016, 24-28 July 2016, Nice, France. http://www.thinkmind.org/index.php?view=article&articleid=sensorcomm_2016_3_20_10048
  • Nicolas Seydoux, Khalil Drira, Nathalie Hernandez, Thierry Monteil: Capturing the contributions of the semantic web to the IoT: a unifying vision. CoRR abs/1709.03576 (2017). https://arxiv.org/pdf/1709.03576.pdf

11H30: irstea data archive published on the LOD related to agricultural domain

Catherine Roussey - CR équipe Copain

Irstea has published several datasets on the LOD: two archives of weather data and a corpus of agricultural alert bulletins. This presentation will describe the schema used for each dataset and the workflow transformation of these datasets.

References

  • C. ROUSSEY, S. BERNARD, G. ANDRE, O. CORCHO, G. de SOUSA, D. BOFFETY, J-P CHANET: Weather Station Data Publication at Irstea: an Implementation Report. In Proceedings of the 7th International Workshop on Semantic Sensor Networks (SSN 2014) in conjunction with the 13th International Semantic Web Conference (ISWC 2014), Rida Del Garda, Italia, October 20, 2014, 16 pages. The paper is available online at http://ceur-ws.org/Vol-1401/paper-07.pdf.
  • C. ROUSSEY, S. BERNARD, F. PINET, X. REBOUD, V. CELLIER, I. SIVADON, D. SIMONNEAU, A-L. BOURIGAULT. A Methodology for the Publication of Agricultural Alert Bulletins as LOD. in Computers and Electronics in Agriculture. Volume 142, Part B, November 2017, p. 632-650. DOI: https://doi.org/10.1016/j.compag.2017.10.022

URL: http://www.sciencedirect.com/science/article/pii/S0168169917306361

11H45: Pause de Midi

13H00 : Towards semantic interoperability in the Web of Data

Raúl García-Castro

This talk will cover different research topics in the broad scenario of dealing with semantic interoperability in the Web of Data, also taking into account their application to use cases in different projects covering several domains. We will cover how to define shared ontologies to support this task (not only from the human perspective, but also from the machines' one) and how data can be interlinked and reused across organizational boundaries instead of being data silos used by a single organization.

13H30: Collaborative ontology Development: focus on bootstrapping capabilities

Omar Alqawasmeh - 2nd yr Ph.D. candidate

Ontologies provide a common definition of basic concepts in a specific domain and relations among them. The development process of ontologies can adapt to several methodologies. These methodologies follow several bootstrapping techniques: a) manual, b) semi- automatic or c) fully automatic. Moreover, in most cases, ontologies are developed by several parties (e.g. knowledge engineers, domain experts, and computer systems). Which requires to have a collaborative environment in order to handle and manage the development process between these several parties. In this presentation, I will provide an overview of collaborative ontology editing focusing on collaborative ontology bootstrapping. I will present the motivation of studying this problem, state of the art techniques, and some possible methods to overcome the problem.

14H00: Generation of Linked Data Platforms from existing data sources

Noorani Bakerally - 3rd yr Ph.D. candidate ANR OpenSensingCity

Linked Data Platform 1.0 (LDP) is the W3C Recommendation for exposing linked data in a RESTful manner. While several implementations of the LDP standard exist, deploying an LDP is still complex and tighly coupled to the chosen implementation. As a consequence, the same design (in terms of data organization) is difficult to reuse in different LDP deployments. We propose a language for specifying how existing data should be used to generate LDPs in a way that is independent of and compatible with any LDP implementation and deployable on any of them. We formally describe the syntax and semantics of the language and its implementation. We show that our approach 1) allows the reuse of the same design for multiple deployments, or 2) the same data with different designs, 3) is open to heterogeneous data sources, 4) can cope with hosting constraints and 5) significantly automatizes deployment of LDPs.

References

  • Bakerally, N., Zimmermann, A., Boissier, O. (2017) Towards the automatic deployment of data in Linked Data Platforms. Accepted at ISWC demo track.
  • Bakerally, N. (2017) Towards Automatic Generation of Linked Data Platforms. Accepted at ISWC Doctoral Consortium.

14H30: A SPARQL extension for generating RDF from heterogeneous formats

Antoine Zimmermann - Maître Assistant

RDF aims at being the universal abstract data model for structured data on the Web. While there is effort to convert data in RDF, the vast majority of data available on the Web does not conform to RDF. Indeed, exposing data in RDF, either natively or through wrappers, can be very costly. Furthermore, in the emerging Web of Things, resource constraints of devices prevent from processing RDF graphs. Hence one cannot expect that all the data on the Web be available as RDF anytime soon. Several tools can generate RDF from nonRDF data, and transformation or mapping languages have been designed to offer more flexible solutions (GRDDL, XSPARQL, R2RML, RML, CSVW, etc.). In this presentation, we introduce a new language, SPARQL-Generate, that generates RDF from: (i) a RDF Dataset, and (ii) a set of documents in arbitrary formats. As SPARQL-Generate is designed as an extension of SPARQL 1.1, it can be implemented on top on any existing SPARQL engine, and leverage the SPARQL extension mechanism to deal with an open set of formats.

References

  • Lefrançois, M., Zimmermann, A., Bakerally, N. (2017) A SPARQL extension for generating RDF from heterogeneous formats. In The Semantic Web – 14th International Conference, ESWC 2017, Portorož, Slovenia, May 28 – June 1, 2017, Proceedings Part I. Lecture Notes in Computer Science Vol. 10249 Springer 2017, ISBN 978-3-319-58068-5. p.35-50.

15H00: Modeling knowledge with the SEAS ontologies

Maxime Lefrançois - Maître Assistant École des Mines de Saint-Étienne

Mid-June 2017, the ETSI SmartM2M working group voted two work items, DTR/SmartM2M-103548 and DTS/SmartM2M-103549, with the goal to enhance and augment the SAREF ontology with some of the design, development, and publication choices that have been made in the context of the ITEA2 SEAS (Smart Energy Aware Systems) project. During this presentation I'll provide an overview of these choices and their rationale. In particular, I''ll talk about contributions regarding: (i) the design of the ontology as a set of simple core ontology patterns, that can then be instantiated for multiple engineering-related verticals; (ii) the design and publication of the SEAS modular and versioned ontology in conformance with the publication and metadata best practices, with the additional constraint that every term is defined under a single namespace. These planned additions to SAREF will ease its adoption and extension by industrial stakeholder, while ensuring easy maintenance of its quality, coherence, and modularity. Finally, because the SEAS ontology generalizes the future W3C&OGC SOSA/SSN (Sensor, Observation, Sensing, Actuation / Semantic Sensor Network) ontology, these work items contribute to the convergence of the different reference ontologies relevant for the IoT domain.

References

  • Maxime Lefrançois, Planned ETSI SAREF Extensions based on the W3C&OGC SOSA/SSN-compatible SEAS Ontology Patterns, In Proceedings of Workshop on Semantic Interoperability and Standardization in the IoT, SIS-IoT, Amsterdam, Netherlands, July 2017
  • Armin Haller, Krzysztof Janowicz, Simon Cox, Danh Le Phuoc, Kerry Taylor, and Maxime Lefrançois, Semantic Sensor Network Ontology, W3C Recommendation, W3C, 19 October 2017

15H30: Discussion

Weather data

BSV

AgronomicTaxon

AgroTechnoPôle

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