Cloud computing is a technological paradigm that permits computing services to be offered over the Internet. This new service model is closely related to previous well-known distributed computing initiatives such as Web services and grid computing. In the current socio-economic climate, the affordability of cloud computing has made it one of the most popular recent innovations. This has led to the availability of more and more cloud services, as a consequence of which it is becoming increasingly difficult for service consumers to find and access those cloud services that fulfil their requirements. In this paper, we present a semantically-enhanced platform that will assist in the process of discovering the cloud services that best match user needs. This fully-fledged system encompasses two basic functions: the creation of a repository with the semantic description of cloud services and the search for services that accomplish the required expectations. The cloud service's semantic repository is generated by means of an automatic tool that first annotates the cloud service descriptions with semantic content and then creates a semantic vector for each service. The comprehensive evaluation of the tool in the ICT domain has led to very promising results that outperform state-of-the-art solutions in similarly broad domains.

Ontology-based annotation and retrieval of services in the cloud

Creating a semantically-enhanced cloud services environment through ontology evolution

Time is a pervasive dimension of reality as everything evolves as time elapses. Therefore, Web-based information systems and knowledge representation tools at least mirror, and often have to capture, the time-varying and evolutionary nature of the phenomena they model and of the activities they support. This aspect has been acknowledged and long studied in the field of temporal databases [Jensen and Snodgrass 2009] but it truly applies also to the World Wide Web and Semantic Web in particular. Several papers addressing, in an explicit or implicit way, the representation and management of time and evolution in the Semantic Web appeared recently and, on some aspects, showed a clear upward trend in last years, witnessing a sustained and/or growing research interest. Reflecting and acknowledging such interest, we started in 2011 to collect references concerning the handling of time and evolution issues in Semantic Web research. As it was for [Grandi 2003], the purpose of this collection was to compile a bibliography which could be of help, in particular, to students and young researchers. As a result of such almost endless work, we wrote an annotated bibliography [Grandi 2012], whose latest version is available on the Web at URL:

/pdf/introducing-an-annotated-bibliography-on-temporal-and-j1r0ujrhlh.pdf

Introducing an annotated bibliography on temporal and evolution aspects in the semantic web

Analytical study on design deficiencies in the envelope projects of healthcare buildings in spain

Les patients atteints de SLA necessitent un accompagnement pluridisciplinaire au cours de leur parcours. La pathologie provoque de nombreuses incapacites et situations de handicaps. Cette prise en charge complexe peut amener a des situations de rupture de parcours par l’absence, l’arret ou des difficultes de prise en charge, cependant les causes de ces ruptures ne sont pas connues. Le reseau de coordination ville hopital SLA Ile-de-France dispose d’une base textuelle de coordination, sur laquelle les besoins et les demandes des patients sont decrits tout au long de leurs parcours. A cette fin, nous proposons d’analyser cette base pour en extraire de la connaissance et decrire les parcours patients. Pour cela nous utilisons un outil d’annotation semantique qui utilise comme ressource une ontologie du domaine que nous avons cree OntoParon. OntoParon est une ontologie modulaire composee d’un module medical, d’un module socio-environnemental, d’un module de coordination, d’un module noyau et d’un module de consolidation. Ces modules ontologiques permettent de prendre en compte les dimensions intervenant dans les parcours des patients. Des concepts definis, rendant compte de thematiques importantes comme l’epuisement de l’aidant ou bien encore la presence de problemes sociaux ont ete crees pour detecter les difficultes rencontrees. L’annotation de 931 dossiers patients a permis de voir que tous les patients ne presentent pas les memes besoins ni les memes demandes, certaines thematiques s’expriment differemment en fonction de l’âge, de la forme de pathologie ou du mode de vie des personnes.

Apports de la modélisation ontologique pour l’analyse des ruptures de parcours de soins dans la Sclérose Latérale Amyotrophique

EVONTO - Joint Evolution of Ontologies and Semantic Annotations

According to Knight, uncertainty signifies deviations from the expected states, which prevent us from the use of any probability for the determination of a result for a given action or decision [1] This paper describes the phenomenon of uncertainty in the face of technological megatrends and challenges associated with them The article focuses on the analysis of the uncertainty in one of the most important technology trends – the Internet of Things (IoT) – on the example of Healthcare The right decisions are not always equivalent to good results Sometimes, the decision taken in accordance with general rules brings worse results than the one who breaks them Such a situation is possible as a result of the uncertainty accompanying the predictions of the future In this article the concept of the IoT is treated as a big, complex, dynamic system with specific characteristics, dimensions structures and behaviors The aim of the article is to analyze the factors that may determine the uncertainty and ambiguity of such systems in the context of the development of Healthcare, and recommendations are made for future research directions

/pdf/uncertainty-in-iot-for-smart-healthcare-challenges-and-bhm9xrn0o6.pdf

Uncertainty in IoT for Smart Healthcare: Challenges, and Opportunities

Dans un environnement dynamique, les ressources termino-ontologiques et les annotations semantiques qu'elles permettent de construire doivent etre modifiees regulierement et en coherence pour s'adapter a l'evolution du domaine sur lequel elles portent et des collections documentaires annotees. En support a un environnement d'annotation automatique de documents (TextViz), nous avons developpe EvOnto pour faciliter l'evolution d'une ressource termino-ontologique en tenant compte des annotations semantiques definies avec celle-ci. EvOnto permet de formuler une demande de changement, d'evaluer l'impact de ce changement sur la ressource termino-ontologique et sur les annotations semantiques, et finalement de decider de la mise en oeuvre de ce changement. Cet article presente les principes d'EvOnto et une etude de cas qui illustre son apport a l'evolution d'ontologie.

EvOnto : un outil d’évolution de ressource termino-ontologique pour l’annotation sémantique

The Medical information is one of the types of information that are characterized by the multiplicity and diversity of its sources. This diversity contributes to the emergence of many problems; of which the most important is the difficulty of communication and interaction between systems. This is what is called the problem of interoperability. In this context, we propose in this paper a new mediator semantic that we call the Medical Project Management System. Based on ontological components and an XML data exchange format, this mediator allows the user to have a unified representation of the information originally distributed on several different and heterogeneous sites and which are related to a specific project. In addition, it helps the user to interact with a large number of medical projects and to research similar projects and comparing them to take advantage of best practices and shared experiences to improve the quality of treatment.

The medical project management (MPM) system

Un des enjeux du web semantique est de produire des caracterisations formelles de contenus documentaires, ou annotations semantiques, de qualite. Or dans un environnement dynamique, les ressources termino-ontologiques et les annotations semantiques qu'elles permettent de construire doivent etre modifiees regulierement et en coherence pour s'adapter a l'evolution du domaine concerne et des collections documentaires annotees. Notre contribution est une methode qui permet de gerer conjointement l'evolution d'une ressource termino-ontologique et d'annotations semantiques produites a partir de cette ressource. La methode definit les types de changements applicables (elementaires ou complexes), ainsi que des strategies d'evolution de la ressource et des annotations. Cette methode est mise en œuvre par le logiciel EvOnto qui s'integre a l'environnement d'annotation automatique de documents TextViz defini dans le cadre du projet ANR DYNAMO. L'originalite d'EvOnto est de s'adapter a plusieurs scenarios d'evolution suivant que ce soit l'ontologie, la collection documentaire ou les annotations qui soient modifiees. EvOnto assure un support a l'ontologue en le guidant interactivement pour formuler une demande de changement, evaluer son impact (effets supplementaires) sur la ressource termino-ontologique et aussi sur les annotations semantiques, et decider ensuite de leur mise en œuvre. Il fournit des informations a l'ontologue pour qu'il decide d'une evolution en connaissant ses consequences, et qu'il l'adapte pour minimiser les effets negatifs, les impacts non souhaitables ou les couts correspondants sur la ressource elle-meme et son utilisation dans des annotations.

https://tel.archives-ouvertes.fr/tel-02360665/document

Anis Tissaoui

Papers

EVONTO - Joint Evolution of Ontologies and Semantic Annotations

Uncertainty in IoT for Smart Healthcare: Challenges, and Opportunities

EvOnto : un outil d’évolution de ressource termino-ontologique pour l’annotation sémantique

The medical project management (MPM) system

Évolution cohérente des ressources termino-ontologiques et des annotations sémantiques