Ph.D
Group : Databases

Optimisation de requêtes olap et visualisation de résultats

Starts on 15/09/2007
Advisor : SPYRATOS, Nicolas

Funding : AM
Affiliation : Université Paris-Saclay
Laboratory : LRI

Defended on 16/09/2011, committee :

Research activities :
   - Databases
   - Multidimensional databases

Abstract :
In this thesis, we explore different aspects of Data Warehousing and OLAP,
the common point of our proposals being the functional model for data
analysis. Our main objective is to use that model in studying three
different, but related aspects:

- query optimization through rewriting and cache management,
- query result visualization,
- mapping of a relational BCNF schema to a functional schema.

Query optimization and cache management is a crucial issue in query
processing in general, and in data warehousing in particular; and query
rewriting is one of the basic techniques for query optimization. We
establish derivability conditions for analytic functional queries, using a
partial pre-order over the set of queries. Then we provide a sound and
complete rewriting algorithm, as well as an optimized cache management
strategy, both based on the underlying functional model.
A second important aspect that we explore in the thesis is that of query
result visualization. We show the importance for the visualization to
reflect such essential features of the dataset as functional dependencies.
We show that the connection existing between data and visualization is
precisely the connection between their functional representations. We then
define a framework, whose objective is to establish such a connection for a
given dataset and a set of visualizations.
In addition to the analysis of the visualization process, we use the
functional data model as a guide for interactive visualization, and define
what we call a parametric visualization.
A third important aspect of our work is experimentation with the results
obtained in the thesis. In order to be able to analyze the data contained
in a Boyce-Codd Normal Form (BCNF) table, one can use the results obtained
in this thesis, provided that the schema of the table can be mapped to a
functional schema. We present such a mapping in this thesis. Once the
relational schema has been transformed into a functional schema, we can
take advantage of the query optimization and result visualization results
presented in the thesis. We have used this transformation in the
implementation of two prototypes in the context of two different projects.

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.