458 research outputs found
Contextualization of topics - browsing through terms, authors, journals and cluster allocations
This paper builds on an innovative Information Retrieval tool, Ariadne. The
tool has been developed as an interactive network visualization and browsing
tool for large-scale bibliographic databases. It basically allows to gain
insights into a topic by contextualizing a search query (Koopman et al., 2015).
In this paper, we apply the Ariadne tool to a far smaller dataset of 111,616
documents in astronomy and astrophysics. Labeled as the Berlin dataset, this
data have been used by several research teams to apply and later compare
different clustering algorithms. The quest for this team effort is how to
delineate topics. This paper contributes to this challenge in two different
ways. First, we produce one of the different cluster solution and second, we
use Ariadne (the method behind it, and the interface - called LittleAriadne) to
display cluster solutions of the different group members. By providing a tool
that allows the visual inspection of the similarity of article clusters
produced by different algorithms, we present a complementary approach to other
possible means of comparison. More particular, we discuss how we can - with
LittleAriadne - browse through the network of topical terms, authors, journals
and cluster solutions in the Berlin dataset and compare cluster solutions as
well as see their context.Comment: proceedings of the ISSI 2015 conference (accepted
Web-Based Visualization of Very Large Scientific Astronomy Imagery
Visualizing and navigating through large astronomy images from a remote
location with current astronomy display tools can be a frustrating experience
in terms of speed and ergonomics, especially on mobile devices. In this paper,
we present a high performance, versatile and robust client-server system for
remote visualization and analysis of extremely large scientific images.
Applications of this work include survey image quality control, interactive
data query and exploration, citizen science, as well as public outreach. The
proposed software is entirely open source and is designed to be generic and
applicable to a variety of datasets. It provides access to floating point data
at terabyte scales, with the ability to precisely adjust image settings in
real-time. The proposed clients are light-weight, platform-independent web
applications built on standard HTML5 web technologies and compatible with both
touch and mouse-based devices. We put the system to the test and assess the
performance of the system and show that a single server can comfortably handle
more than a hundred simultaneous users accessing full precision 32 bit
astronomy data.Comment: Published in Astronomy & Computing. IIPImage server available from
http://iipimage.sourceforge.net . Visiomatic code and demos available from
http://www.visiomatic.org
A Development Environment for Visual Physics Analysis
The Visual Physics Analysis (VISPA) project integrates different aspects of
physics analyses into a graphical development environment. It addresses the
typical development cycle of (re-)designing, executing and verifying an
analysis. The project provides an extendable plug-in mechanism and includes
plug-ins for designing the analysis flow, for running the analysis on batch
systems, and for browsing the data content. The corresponding plug-ins are
based on an object-oriented toolkit for modular data analysis. We introduce the
main concepts of the project, describe the technical realization and
demonstrate the functionality in example applications
Recommended from our members
Collaborative yet independent: Information practices in the physical sciences
In many ways, the physical sciences are at the forefront of using digital tools and methods to work with information and data. However, the fields and disciplines that make up the physical sciences are by no means uniform, and physical scientists find, use, and disseminate information in a variety of ways. This report examines information practices in the physical sciences across seven cases, and demonstrates the richly varied ways in which physical scientists work, collaborate, and share information and data.
This report details seven case studies in the physical sciences. For each case, qualitative interviews and focus groups were used to understand the domain. Quantitative data gathered from a survey of participants highlights different information strategies employed across the cases, and identifies important software used for research.
Finally, conclusions from across the cases are drawn, and recommendations are made. This report is the third in a series commissioned by the Research Information Network (RIN), each looking at information practices in a specific domain (life sciences, humanities, and physical sciences). The aim is to understand how researchers within a range of disciplines find and use information, and in particular how that has changed with the introduction of new technologies
Search and Discovery Tools for Astronomical On-line Resources and Services
A growing number of astronomical resources and data or information services
are made available through the Internet. However valuable information is
frequently hidden in a deluge of non-pertinent or non up-to-date documents. At
a first level, compilations of astronomical resources provide help for
selecting relevant sites. Combining yellow-page services and meta-databases of
active pointers may be an efficient solution to the data retrieval problem.
Responses generated by submission of queries to a set of heterogeneous
resources are difficult to merge or cross-match, because different data
providers generally use different data formats: new endeavors are under way to
tackle this problem. We review the technical challenges involved in trying to
provide general search and discovery tools, and to integrate them through upper
level interfaces.Comment: 7 pages, 2 Postscript figures; to be published in A&A
Recommended from our members
Visualization-driven Structural and Statistical Analysis of Turbulent Flows
Knowledge extraction from data volumes of ever increasing size requires ever more flexible tools to facilitate interactive query. In- teractivity enables real-time hypothesis testing and scientific discovery, but can generally not be achieved without some level of data reduction. The approach described in this paper combines multi-resolution access, region-of-interest extraction, and structure identification in order to pro- vide interactive spatial and statistical analysis of a terascale data volume. Unique aspects of our approach include the incorporation of both local and global statistics of the flow structures, and iterative refinement fa- cilities, which combine geometry, topology, and statistics to allow the user to effectively tailor the analysis and visualization to the science. Working together, these facilities allow a user to focus the spatial scale and domain of the analysis and perform an appropriately tailored mul- tivariate visualization of the corresponding data. All of these ideas and algorithms are instantiated in a deployed visualization and analysis tool called VAPOR, which is in routine use by scientists internationally. In data from a 10243 simulation of a forced turbulent flow, VAPOR allowed us to perform a visual data exploration of the flow properties at interac- tive speeds, leading to the discovery of novel scientific properties of the flow, in the form of two distinct vortical structure populations. These structures would have been very difficult (if not impossible) to find with statistical overviews or other existing visualization-driven analysis ap- proaches. This kind of intelligent, focused analysis/refinement approach will become even more important as computational science moves to- wards petascale applications
You can't always sketch what you want: Understanding Sensemaking in Visual Query Systems
Visual query systems (VQSs) empower users to interactively search for line
charts with desired visual patterns, typically specified using intuitive
sketch-based interfaces. Despite decades of past work on VQSs, these efforts
have not translated to adoption in practice, possibly because VQSs are largely
evaluated in unrealistic lab-based settings. To remedy this gap in adoption, we
collaborated with experts from three diverse domains---astronomy, genetics, and
material science---via a year-long user-centered design process to develop a
VQS that supports their workflow and analytical needs, and evaluate how VQSs
can be used in practice. Our study results reveal that ad-hoc sketch-only
querying is not as commonly used as prior work suggests, since analysts are
often unable to precisely express their patterns of interest. In addition, we
characterize three essential sensemaking processes supported by our enhanced
VQS. We discover that participants employ all three processes, but in different
proportions, depending on the analytical needs in each domain. Our findings
suggest that all three sensemaking processes must be integrated in order to
make future VQSs useful for a wide range of analytical inquiries.Comment: Accepted for presentation at IEEE VAST 2019, to be held October 20-25
in Vancouver, Canada. Paper will also be published in a special issue of IEEE
Transactions on Visualization and Computer Graphics (TVCG) IEEE VIS
(InfoVis/VAST/SciVis) 2019 ACM 2012 CCS - Human-centered computing,
Visualization, Visualization design and evaluation method
Spectroscopic Analysis in the Virtual Observatory Environment with SPLAT-VO
SPLAT-VO is a powerful graphical tool for displaying, comparing, modifying
and analyzing astronomical spectra, as well as searching and retrieving spectra
from services around the world using Virtual Observatory (VO) protocols and
services. The development of SPLAT-VO started in 1999, as part of the Starlink
StarJava initiative, sometime before that of the VO, so initial support for the
VO was necessarily added once VO standards and services became available.
Further developments were supported by the Joint Astronomy Centre, Hawaii until
2009. Since end of 2011 development of SPLAT-VO has been continued by the
German Astrophysical Virtual Observatory, and the Astronomical Institute of the
Academy of Sciences of the Czech Republic. From this time several new features
have been added, including support for the latest VO protocols, along with new
visualization and spectra storing capabilities. This paper presents the history
of SPLAT-VO, it's capabilities, recent additions and future plans, as well as a
discussion on the motivations and lessons learned up to now.Comment: 15 pages, 6 figures, accepted for publication in Astronomy &
Computin
Hierarchical progressive surveys. Multi-resolution HEALPix data structures for astronomical images, catalogues, and 3-dimensional data cubes
Scientific exploitation of the ever increasing volumes of astronomical data
requires efficient and practical methods for data access, visualisation, and
analysis. Hierarchical sky tessellation techniques enable a multi-resolution
approach to organising data on angular scales from the full sky down to the
individual image pixels. Aims. We aim to show that the Hierarchical progressive
survey (HiPS) scheme for describing astronomical images, source catalogues, and
three-dimensional data cubes is a practical solution to managing large volumes
of heterogeneous data and that it enables a new level of scientific
interoperability across large collections of data of these different data
types. Methods. HiPS uses the HEALPix tessellation of the sphere to define a
hierarchical tile and pixel structure to describe and organise astronomical
data. HiPS is designed to conserve the scientific properties of the data
alongside both visualisation considerations and emphasis on the ease of
implementation. We describe the development of HiPS to manage a large number of
diverse image surveys, as well as the extension of hierarchical image systems
to cube and catalogue data. We demonstrate the interoperability of HiPS and
Multi-Order Coverage (MOC) maps and highlight the HiPS mechanism to provide
links to the original data. Results. Hierarchical progressive surveys have been
generated by various data centres and groups for ~200 data collections
including many wide area sky surveys, and archives of pointed observations.
These can be accessed and visualised in Aladin, Aladin Lite, and other
applications. HiPS provides a basis for further innovations in the use of
hierarchical data structures to facilitate the description and statistical
analysis of large astronomical data sets.Comment: 21 pages, 6 figures. Accepted for publication in Astronomy &
Astrophysic
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