93,928 research outputs found
Visual Event Cueing in Linked Spatiotemporal Data
abstract: The media disperses a large amount of information daily pertaining to political events social movements, and societal conflicts. Media pertaining to these topics, no matter the format of publication used, are framed a particular way. Framing is used not for just guiding audiences to desired beliefs, but also to fuel societal change or legitimize/delegitimize social movements. For this reason, tools that can help to clarify when changes in social discourse occur and identify their causes are of great use. This thesis presents a visual analytics framework that allows for the exploration and visualization of changes that occur in social climate with respect to space and time. Focusing on the links between data from the Armed Conflict Location and Event Data Project (ACLED) and a streaming RSS news data set, users can be cued into interesting events enabling them to form and explore hypothesis. This visual analytics framework also focuses on improving intervention detection, allowing users to hypothesize about correlations between events and happiness levels, and supports collaborative analysis.Dissertation/ThesisMasters Thesis Computer Science 201
Big Data guided Digital Petroleum Ecosystems for Visual Analytics and Knowledge Management
The North West Shelf (NWS) interpreted as a Total
Petroleum System (TPS), is Super Westralian Basin with
active onshore and offshore basins through which shelf, -
slope and deep-oceanic geological events are construed. In
addition to their data associativity, TPS emerges with
geographic connectivity through phenomena of digital
petroleum ecosystem. The super basin has a multitude of
sub-basins, each basin is associated with several petroleum
systems and each system comprised of multiple oil and gas
fields with either known or unknown areal extents. Such
hierarchical ontologies make connections between
attribute relationships of diverse petroleum systems.
Besides, NWS has a scope of storing volumes of instances
in a data-warehousing environment to analyse and
motivate to create new business opportunities.
Furthermore, the big exploration data, characterized as
heterogeneous and multidimensional, can complicate the
data integration process, precluding interpretation of data
views, drawn from TPS metadata in new knowledge
domains. The research objective is to develop an
integrated framework that can unify the exploration and
other interrelated multidisciplinary data into a holistic TPS
metadata for visualization and valued interpretation.
Petroleum digital ecosystem is prototyped as a digital oil
field solution, with multitude of big data tools. Big data
associated with elements and processes of petroleum
systems are examined using prototype solutions. With
conceptual framework of Digital Petroleum Ecosystems
and Technologies (DPEST), we manage the
interconnectivity between diverse petroleum systems and
their linked basins. The ontology-based data warehousing
and mining articulations ascertain the collaboration
through data artefacts, the coexistence between different
petroleum systems and their linked oil and gas fields that
benefit the explorers. The connectivity between systems
further facilitates us with presentable exploration data
views, improvising visualization and interpretation. The
metadata with meta-knowledge in diverse knowledge
domains of digital petroleum ecosystems ensures the
quality of untapped reservoirs and their associativity
between Westralian basins
Interactive Visual Analysis of Networked Systems: Workflows for Two Industrial Domains
We report on a first study of interactive visual analysis of networked systems. Working with ABB Corporate Research and Ericsson Research, we have created workflows which demonstrate the potential of visualization in the domains of industrial automation and telecommunications. By a workflow in this context, we mean a sequence of visualizations and the actions for generating them. Visualizations can be any images that represent properties of the data sets analyzed, and actions typically either change the selection of data visualized or change the visualization by choice of technique or change of parameters
What May Visualization Processes Optimize?
In this paper, we present an abstract model of visualization and inference
processes and describe an information-theoretic measure for optimizing such
processes. In order to obtain such an abstraction, we first examined six
classes of workflows in data analysis and visualization, and identified four
levels of typical visualization components, namely disseminative,
observational, analytical and model-developmental visualization. We noticed a
common phenomenon at different levels of visualization, that is, the
transformation of data spaces (referred to as alphabets) usually corresponds to
the reduction of maximal entropy along a workflow. Based on this observation,
we establish an information-theoretic measure of cost-benefit ratio that may be
used as a cost function for optimizing a data visualization process. To
demonstrate the validity of this measure, we examined a number of successful
visualization processes in the literature, and showed that the
information-theoretic measure can mathematically explain the advantages of such
processes over possible alternatives.Comment: 10 page
Video Data Visualization System: Semantic Classification And Personalization
We present in this paper an intelligent video data visualization tool, based
on semantic classification, for retrieving and exploring a large scale corpus
of videos. Our work is based on semantic classification resulting from semantic
analysis of video. The obtained classes will be projected in the visualization
space. The graph is represented by nodes and edges, the nodes are the keyframes
of video documents and the edges are the relation between documents and the
classes of documents. Finally, we construct the user's profile, based on the
interaction with the system, to render the system more adequate to its
references.Comment: graphic
Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data
Semantic formalisms represent content in a uniform way according to ontologies. This enables manipulation and reasoning via automated means (e.g. Semantic Web services), but limits the user’s ability to explore the semantic data from a point of view that originates from knowledge representation motivations. We show how, for user consumption, a visualization of semantic data according to some easily graspable dimensions (e.g. space and time) provides effective sense-making of data. In this paper, we look holistically at the interaction between users and semantic data, and propose multiple visualization strategies and dynamic filters to support the exploration of semantic-rich data.
We discuss a user evaluation and how interaction challenges could be overcome to create an effective user-centred framework for the visualization and manipulation of semantic data. The approach has been implemented and evaluated on a real company archive
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Guide Me in Analysis: A Framework for Guidance Designers
Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed and what specific factors should be considered for effective support. In this paper, we approach this problem from the perspective of guidance designers. We present a framework comprising requirements and a set of specific phases designers should go through when designing guidance for visual analytics. We relate this process with a set of quality criteria we aim to support with our framework, that are necessary for obtaining a suitable and effective guidance solution. To demonstrate the practical usability of our methodology, we apply our framework to the design of guidance in three analysis scenarios and a design walk-through session. Moreover, we list the emerging challenges and report how the framework can be used to design guidance solutions that mitigate these issues
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