Fouille visuelle de données temporelles avec DataTube2

International audienceNous nous intéressons dans cet article à la fouille visuelle de données temporelles, où les données ont été mises sous la forme de n attributs dont les valeurs sont enregistrées pendant k instants. Après un état de l'art sur les différentes approches de visualisation de telles séries, nous présentons plus particulièrement une approche ayant reçue encore peu d'attention ("DataTube"). DataTube place les données dans un tube dont l'axe représente le temps. Nous étendons ensuite cette approche : tout d'abord nous définissons plusieurs modes de visualisations (couleurs, formes, etc) et nous ajoutons un axe temporel. Ensuite nous introduisons des interactions avec la possibilité de sélectionner des attributs et des instants, afficher des données complexes ou encore insérer des annotations sur la visualisation. Nous ajoutons une étape de classification non supervisée afin de regrouper dans la visualisation les attributs similaires. Enfin nous intégrons cette visualisation dans notre plateforme de fouille de données en réalité virtuelle VRMiner, avec un affichage stéréoscopique et des possibilités de navigation interactive. Nous appliquons cette visualisation sur plusieurs ensembles de données réelles et nous montrons qu'elle peut gérer jusqu'à 1,5 million de valeurs. Nous présentons également une évaluation utilisateur

Interactive visualization of heterogeneous social networks using glyphs

There is a growing need for visualizing heterogeneous social networks as new data sets become available. However, the existing visualization tools do not address the challenge of reading topological information introduced by heterogeneous node and link types. To resolve this issue, we introduce glyphs to node-link diagrams to conveniently represent the multivariate nature of heterogeneous node and link types. This provides the opportunity to visually reorganize topological information of the heterogeneous social networks without losing connectivity information. Moreover, a set of interaction techniques are provided to the analyst to give total control over the reorganization process. Finally, a case study is presented to using InfoVis 2008 data set to show the exploration process

Strategic enterprise management systems : tools for the 21st century

https://egrove.olemiss.edu/aicpa_guides/1228/thumbnail.jp

Granite: A scientific database model and implementation

The principal goal of this research was to develop a formal comprehensive model for representing highly complex scientific data. An effective model should provide a conceptually uniform way to represent data and it should serve as a framework for the implementation of an efficient and easy-to-use software environment that implements the model. The dissertation work presented here describes such a model and its contributions to the field of scientific databases. In particular, the Granite model encompasses a wide variety of datatypes used across many disciplines of science and engineering today. It is unique in that it defines dataset geometry and topology as separate conceptual components of a scientific dataset. We provide a novel classification of geometries and topologies that has important practical implications for a scientific database implementation. The Granite model also offers integrated support for multiresolution and adaptive resolution data. Many of these ideas have been addressed by others, but no one has tried to bring them all together in a single comprehensive model. The datasource portion of the Granite model offers several further contributions. In addition to providing a convenient conceptual view of rectilinear data, it also supports multisource data. Data can be taken from various sources and combined into a unified view. The rod storage model is an abstraction for file storage that has proven an effective platform upon which to develop efficient access to storage. Our spatial prefetching technique is built upon the rod storage model, and demonstrates very significant improvement in access to scientific datasets, and also allows machines to access data that is far too large to fit in main memory. These improvements bring the extremely large datasets now being generated in many scientific fields into the realm of tractability for the ordinary researcher. We validated the feasibility and viability of the model by implementing a significant portion of it in the Granite system. Extensive performance evaluations of the implementation indicate that the features of the model can be provided in a user-friendly manner with an efficiency that is competitive with more ad hoc systems and more specialized application specific solutions

Proposal of an approach for the design and implementation of a data mesh

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de InformaçãoAtualmente existe uma tendência, cada vez mais acentuada, para a utilização de software por parte da esmagadora maioria da população (aplicações de caráter social, software de gestão, plataformas e-commerce, entre outros), identificando-se a criação e armazenamento de dados que, devido às suas características (volume, variedade e velocidade), fazem emergir o conceito de Big Data. Nesta área, e para suportar o armazenamento dos dados, Big Data Warehouses e Data Lakes são conceitos cimentados e implementados por várias organizações, de forma a servirem a sua necessidade de tomada de decisão. No entanto, apesar de serem conceitos estabelecidos e aceites pela maioria da comunidade científica e por diversas organizações a nível mundial, tal não elimina a necessidade de melhoria e inovação. É, este contexto, que origina o surgimento do conceito de Data Mesh, propondo arquiteturas de dados decentralizadas. Após a análise das limitações demonstrados pelas arquiteturas monolíticas (e.g., dificuldade em mudar as tecnologias de armazenamento usadas para implementar o sistema de dados), é possível concluir sobre a necessidade de uma mudança de paradigma que tornará as organizações verdadeiramente orientadas aos dados. A Data Mesh consiste, na implementação de uma arquitetura onde os dados se encontram intencionalmente distribuídos por vários nós da Data Mesh e onde não existe caos, uma vez que existem estratégias centralizadas de governança de dados e a garantia de que os princípios fundamentais dos domínios são partilhados por toda a arquitetura. A presente dissertação propõe uma abordagem para a implementação de uma Data Mesh, procurando definir o modelo de domínios do conceito. Após esta definição é proposta de uma arquitetura concetual e tecnológica, que visam a auxiliar a materialização dos conceitos apresentados no modelo de domínios e assim auxiliar na conceção e implementação de uma Data Mesh. Posteriormente é realizada uma prova de conceito, de forma a validar os supracitados modelos, contribuindo com conhecimento técnico e científico relacionado com este conceito emergente.Currently there is an increasingly accentuated trend towards the use of software by most of the population (social applications, management software, e-commerce platforms, among others), identifying the creation and storage of data that, due to its characteristics (volume, variety, and speed), make the concept of Big Data emerge. In this area, and to support data storage, Big Data Warehouses and Data Lakes are solid concept and implemented by various organizations to serve their decision-making needs. However, despite being established and accepted concepts by most of the scientific community and by several organizations worldwide, this does not eliminate the need for improvement and innovation in the field. It is this context that gives rise to the emergence of the Data Mesh concept, proposing decentralized data architectures. After analyzing the limitations demonstrated by monolithic architectures (e.g., difficulty in changing the storage technologies used to implement the data system), it is possible to conclude on the need for a paradigm shift that will make organizations truly data driven. Data Mesh consists, in the implementation of an architecture where data is intentionally distributed over several nodes of the Data Mesh, and where there is no chaos, since there are centralized data governance strategies and the assurance that the fundamental principles of the domains are shared throughout the architecture. This master thesis proposes an approach for the implementation of a Data Mesh, seeking to define the domain model of the concept. After this definition, a conceptual and technological architecture is proposed, which aim to help materialize the concepts presented in the domain model and thus assist in the design and implementation of a Data Mesh. Afterwards a proof-of-concept is carried out, to validate the aforementioned models, contributing with technical and scientific knowledge related to this emerging concept

An evaluation of the challenges of Multilingualism in Data Warehouse development

In this paper we discuss Business Intelligence and define what is meant by support for Multilingualism in a Business Intelligence reporting context. We identify support for Multilingualism as a challenging issue which has implications for data warehouse design and reporting performance. Data warehouses are a core component of most Business Intelligence systems and the star schema is the approach most widely used to develop data warehouses and dimensional Data Marts. We discuss the way in which Multilingualism can be supported in the Star Schema and identify that current approaches have serious limitations which include data redundancy and data manipulation, performance and maintenance issues. We propose a new approach to enable the optimal application of multilingualism in Business Intelligence. The proposed approach was found to produce satisfactory results when used in a proof-of-concept environment. Future work will include testing the approach in an enterprise environmen