242 research outputs found
Tasks for multivariate network analysis
In Chap. 1, a multivariate network was defined as having two important characteristics. First, nodes are connected to each other via links; there is topological structure. Second, being multivariate, nodes and links have attributes associated with them, with these attributes having a value. In this chapter, we describe tasks associated with multivariate networks. We consider a task to be an activity that a user wishes to accomplish by interacting with a visual representation of a multivariate network. This implies that there is user intent [13], and that the network has been presented visually. At the highest level, this intent is usually described as the goal of obtaining insight about the data being studied [6]
Dagstuhl News January - December 2011
"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic
Mapping Tasks to Interactions for Graph Exploration and Graph Editing on Interactive Surfaces
Graph exploration and editing are still mostly considered independently and
systems to work with are not designed for todays interactive surfaces like
smartphones, tablets or tabletops. When developing a system for those modern
devices that supports both graph exploration and graph editing, it is necessary
to 1) identify what basic tasks need to be supported, 2) what interactions can
be used, and 3) how to map these tasks and interactions. This technical report
provides a list of basic interaction tasks for graph exploration and editing as
a result of an extensive system review. Moreover, different interaction
modalities of interactive surfaces are reviewed according to their interaction
vocabulary and further degrees of freedom that can be used to make interactions
distinguishable are discussed. Beyond the scope of graph exploration and
editing, we provide an approach for finding and evaluating a mapping from tasks
to interactions, that is generally applicable. Thus, this work acts as a
guideline for developing a system for graph exploration and editing that is
specifically designed for interactive surfaces.Comment: 21 pages, minor corrections (typos etc.
Towards the Formalization of Fractional Calculus in Higher-Order Logic
Fractional calculus is a generalization of classical theories of integration
and differentiation to arbitrary order (i.e., real or complex numbers). In the
last two decades, this new mathematical modeling approach has been widely used
to analyze a wide class of physical systems in various fields of science and
engineering. In this paper, we describe an ongoing project which aims at
formalizing the basic theories of fractional calculus in the HOL Light theorem
prover. Mainly, we present the motivation and application of such formalization
efforts, a roadmap to achieve our goals, current status of the project and
future milestones.Comment: 9 page
2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualisations in Virtual Reality
Relational information between different types of entities is often modelled
by a multilayer network (MLN) -- a network with subnetworks represented by
layers. The layers of an MLN can be arranged in different ways in a visual
representation, however, the impact of the arrangement on the readability of
the network is an open question. Therefore, we studied this impact for several
commonly occurring tasks related to MLN analysis. Additionally, layer
arrangements with a dimensionality beyond 2D, which are common in this
scenario, motivate the use of stereoscopic displays. We ran a human subject
study utilising a Virtual Reality headset to evaluate 2D, 2.5D, and 3D layer
arrangements. The study employs six analysis tasks that cover the spectrum of
an MLN task taxonomy, from path finding and pattern identification to
comparisons between and across layers. We found no clear overall winner.
However, we explore the task-to-arrangement space and derive empirical-based
recommendations on the effective use of 2D, 2.5D, and 3D layer arrangements for
MLNs.Comment: IEEE Transactions on Visualization and Computer Graphics, In press,
To appear. Accepted to IEEE VIS 202
The State of the Art in Multilayer Network Visualization
Modelling relationships between entities in real-world systems with a simple
graph is a standard approach. However, reality is better embraced as several
interdependent subsystems (or layers). Recently the concept of a multilayer
network model has emerged from the field of complex systems. This model can be
applied to a wide range of real-world datasets. Examples of multilayer networks
can be found in the domains of life sciences, sociology, digital humanities and
more. Within the domain of graph visualization there are many systems which
visualize datasets having many characteristics of multilayer graphs. This
report provides a state of the art and a structured analysis of contemporary
multilayer network visualization, not only for researchers in visualization,
but also for those who aim to visualize multilayer networks in the domain of
complex systems, as well as those developing systems across application
domains. We have explored the visualization literature to survey visualization
techniques suitable for multilayer graph visualization, as well as tools,
tasks, and analytic techniques from within application domains. This report
also identifies the outstanding challenges for multilayer graph visualization
and suggests future research directions for addressing them
Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs
The overview-driven visual analysis of large-scale dynamic graphs poses a
major challenge. We propose Multiscale Snapshots, a visual analytics approach
to analyze temporal summaries of dynamic graphs at multiple temporal scales.
First, we recursively generate temporal summaries to abstract overlapping
sequences of graphs into compact snapshots. Second, we apply graph embeddings
to the snapshots to learn low-dimensional representations of each sequence of
graphs to speed up specific analytical tasks (e.g., similarity search). Third,
we visualize the evolving data from a coarse to fine-granular snapshots to
semi-automatically analyze temporal states, trends, and outliers. The approach
enables to discover similar temporal summaries (e.g., recurring states),
reduces the temporal data to speed up automatic analysis, and to explore both
structural and temporal properties of a dynamic graph. We demonstrate the
usefulness of our approach by a quantitative evaluation and the application to
a real-world dataset.Comment: IEEE Transactions on Visualization and Computer Graphics (TVCG), to
appea
The State of the Art in Multilayer Network Visualization
Modelling relationship between entities in real-world systems with a simple graph is a standard approach. However, realityis better embraced as several interdependent subsystems (or layers). Recently, the concept of a multilayer network model hasemerged from the field of complex systems. This model can be applied to a wide range of real-world data sets. Examples ofmultilayer networks can be found in the domains of life sciences, sociology, digital humanities and more. Within the domainof graph visualization, there are many systems which visualize data sets having many characteristics of multilayer graphs.This report provides a state of the art and a structured analysis of contemporary multilayer network visualization, not only forresearchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as wellas those developing systems across application domains. We have explored the visualization literature to survey visualizationtechniques suitable for multilayer graph visualization, as well as tools, tasks and analytic techniques from within applicationdomains. This report also identifies the outstanding challenges for multilayer graph visualization and suggests future researchdirections for addressing them
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