63,731 research outputs found
Visualization, Exploration and Data Analysis of Complex Astrophysical Data
In this paper we show how advanced visualization tools can help the
researcher in investigating and extracting information from data. The focus is
on VisIVO, a novel open source graphics application, which blends high
performance multidimensional visualization techniques and up-to-date
technologies to cooperate with other applications and to access remote,
distributed data archives. VisIVO supports the standards defined by the
International Virtual Observatory Alliance in order to make it interoperable
with VO data repositories. The paper describes the basic technical details and
features of the software and it dedicates a large section to show how VisIVO
can be used in several scientific cases.Comment: 32 pages, 15 figures, accepted by PAS
ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization
ROOT is an object-oriented C++ framework conceived in the high-energy physics
(HEP) community, designed for storing and analyzing petabytes of data in an
efficient way. Any instance of a C++ class can be stored into a ROOT file in a
machine-independent compressed binary format. In ROOT the TTree object
container is optimized for statistical data analysis over very large data sets
by using vertical data storage techniques. These containers can span a large
number of files on local disks, the web, or a number of different shared file
systems. In order to analyze this data, the user can chose out of a wide set of
mathematical and statistical functions, including linear algebra classes,
numerical algorithms such as integration and minimization, and various methods
for performing regression analysis (fitting). In particular, ROOT offers
packages for complex data modeling and fitting, as well as multivariate
classification based on machine learning techniques. A central piece in these
analysis tools are the histogram classes which provide binning of one- and
multi-dimensional data. Results can be saved in high-quality graphical formats
like Postscript and PDF or in bitmap formats like JPG or GIF. The result can
also be stored into ROOT macros that allow a full recreation and rework of the
graphics. Users typically create their analysis macros step by step, making use
of the interactive C++ interpreter CINT, while running over small data samples.
Once the development is finished, they can run these macros at full compiled
speed over large data sets, using on-the-fly compilation, or by creating a
stand-alone batch program. Finally, if processing farms are available, the user
can reduce the execution time of intrinsically parallel tasks - e.g. data
mining in HEP - by using PROOF, which will take care of optimally distributing
the work over the available resources in a transparent way
SPOT: Open Source framework for scientific data repository and interactive visualization
SPOT is an open source and free visual data analytics tool for
multi-dimensional data-sets. Its web-based interface allows a quick analysis of
complex data interactively. The operations on data such as aggregation and
filtering are implemented. The generated charts are responsive and OpenGL
supported. It follows FAIR principles to allow reuse and comparison of the
published data-sets. The software also support PostgreSQL database for
scalability
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