16,111 research outputs found
Inviwo -- A Visualization System with Usage Abstraction Levels
The complexity of today's visualization applications demands specific
visualization systems tailored for the development of these applications.
Frequently, such systems utilize levels of abstraction to improve the
application development process, for instance by providing a data flow network
editor. Unfortunately, these abstractions result in several issues, which need
to be circumvented through an abstraction-centered system design. Often, a high
level of abstraction hides low level details, which makes it difficult to
directly access the underlying computing platform, which would be important to
achieve an optimal performance. Therefore, we propose a layer structure
developed for modern and sustainable visualization systems allowing developers
to interact with all contained abstraction levels. We refer to this interaction
capabilities as usage abstraction levels, since we target application
developers with various levels of experience. We formulate the requirements for
such a system, derive the desired architecture, and present how the concepts
have been exemplary realized within the Inviwo visualization system.
Furthermore, we address several specific challenges that arise during the
realization of such a layered architecture, such as communication between
different computing platforms, performance centered encapsulation, as well as
layer-independent development by supporting cross layer documentation and
debugging capabilities
Progressive Analytics: A Computation Paradigm for Exploratory Data Analysis
Exploring data requires a fast feedback loop from the analyst to the system,
with a latency below about 10 seconds because of human cognitive limitations.
When data becomes large or analysis becomes complex, sequential computations
can no longer be completed in a few seconds and data exploration is severely
hampered. This article describes a novel computation paradigm called
Progressive Computation for Data Analysis or more concisely Progressive
Analytics, that brings at the programming language level a low-latency
guarantee by performing computations in a progressive fashion. Moving this
progressive computation at the language level relieves the programmer of
exploratory data analysis systems from implementing the whole analytics
pipeline in a progressive way from scratch, streamlining the implementation of
scalable exploratory data analysis systems. This article describes the new
paradigm through a prototype implementation called ProgressiVis, and explains
the requirements it implies through examples.Comment: 10 page
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