Ph.D
Group : Large-scale Heterogeneous DAta and Knowledge

Accessing and using complex multimedia documents in a digital library

Starts on 01/12/2009
Advisor : SPYRATOS, Nicolas

Funding : Bourse pour étudiant étranger
Affiliation : Université Paris-Saclay
Laboratory : LRI BD

Defended on 09/07/2013, committee :

Research activities :

Abstract :
In the context of three European projects, our research team has developed a data model and query language for digital libraries supporting identification, structuring, metadata, and discovery and reuse of digital resources. The model is inspired by the Web and it is formalized as a first-order theory, certain models of which correspond to the notion of digital library. In addition, a full translation of the model to RDF and of the query language to SPARQL has been proposed to demonstrate the feasibility of the model and its suitability for practical applications. The choice of RDF is due to the fact that it is a generally accepted representation language in the context of digital libraries and the Semantic Web.
One of the major aims of the thesis was to design and actually implement a simplified form of a digital library management system based on the theoretical model. To obtain this, we have developed a prototype based on RDF and SPARQL, which uses a RDF store to facilitate internal management of metadata. The prototype allows users to manage and query metadata of digital or non-digital resources in the system, using URIs as resource identifiers, a set of predicates to model descriptions of resources, and simple conjunctive queries to discover knowledge in the system. The prototype is implemented by using Java technologies and the Google Web Toolkit framework whose system architecture consists of a storage layer, a business logic layer, a service layer and a user interface. During the thesis work, the prototype was built, tested, and debugged locally and then deployed on Google App Engine. In the future, it will be expanded to become a full fledged digital library management system.
Moreover, the thesis also presents our contribution to content generation by reuse. This is mostly theoretical work whose purpose is to enrich the model and query language by providing an important community service. The incorporation of this service in the implemented system is left to future work.

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.