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Università degli studi di Trento

Diversity Aware Visualization

Abstract

dc:description

This thesis aims to address a significant issue related with the consumption of diversified data in the field of semantics and knowledge representation by using a framework which allows the data consumption in a generic, scalable and pleasing manner. The work proposes a mixed solution by splitting the issue into four subproblems: how to preserve the richness associated with the data; how to present information about an object in a single or multiple visualization contexts; and to provide a seamless exploration of interconnected entities; and how to design a tool that offers a better user experience. A real-world object can have various representations which lead to data diversity. However, each representation captures a view (mostly partial) of an object. To preserve the richness associated with the data, we follow an entity-centric design approach. In this approach, we represent multiple datasets related to an object as an entity with various properties. An entity is then further categorized in a group according to its similarities or differences. Our contextual model not only considers the transformation of objects as entities but also adapts to various visualization contexts. These contexts are space, list, timeline, and network. We design a multiview visualization framework that allows simultaneous presentation of entities according to these four defined visualization contexts. To allow seamless interaction of data with the users, we emphasized on using a multilayered architecture where: 1)datasets are aggregated and stored using an entity-centric approach, 2) visualized in various contexts and viewpoints simultaneously according to the entity types and users' need. This adaptation is capable enough to facilitate presentation and exploration of diversified data according to users need. To prove the feasibility of our framework, we applied it to visualize diversified data in various settings. Continuous interaction with the end users produced valuable feedback and essential design suggestions. Finally, multiple prototypes were evaluated with the end users to verify their usability. The results obtained were highly favorable.

Degree

thesis:*
Grantor dc:publisher
Università degli studi di Trento
Year dc:date
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ojha, Sajan Raj
Contributors dc:contributor
  • Giunchiglia, Fausto

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • info:eu-repo/semantics/openAccess
  • license:Tutti i diritti riservati (All rights reserved)
  • license uri:iris.PRI01
Language dc:language
eng

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:iris.unitn.it:11572/368979

Chain of custody

source
Harvested from
Università degli Studi di Trento
Base URL
iris.unitn.it/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Ojha, Sajan Raj. Diversity Aware Visualization. Università degli studi di Trento, 2018. https://hdl.handle.net/11572/368979