36,833 research outputs found
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BallotMaps: Detecting name bias in alphabetically ordered ballot papers
The relationship between candidates’ position on a ballot paper and vote rank is explored in the case of 5000 candidates for the UK 2010 local government elections in the Greater London area. This design study uses hierarchical spatially arranged graphics to represent two locations that affect candidates at very different scales: the geographical areas for which they seek election and the spatial location of their names on the ballot paper. This approach allows the effect of position bias to be assessed; that is, the degree to which the position of a candidate’s name on the ballot paper influences the number of votes received by the candidate, and whether this varies geographically. Results show that position bias was significant enough to influence rank order of candidates, and in the case of many marginal electoral wards, to influence who was elected to government. Position bias was observed most strongly for Liberal Democrat candidates but present for all major political parties. Visual analysis of classification of candidate names by ethnicity suggests that this too had an effect on votes received by candidates, in some cases overcoming alphabetic name bias. The results found contradict some earlier research suggesting that alphabetic name bias was not sufficiently significant to affect electoral outcome and add new evidence for the geographic and ethnicity influences on voting behaviour. The visual approach proposed here can be applied to a wider range of electoral data and the patterns identified and hypotheses derived from them could have significant implications for the design of ballot papers and the conduct of fair elections
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Digitizing mass spectrometry data to explore the chemical diversity and distribution of marine cyanobacteria and algae.
Natural product screening programs have uncovered molecules from diverse natural sources with various biological activities and unique structures. However, much is yet underexplored and additional information is hidden in these exceptional collections. We applied untargeted mass spectrometry approaches to capture the chemical space and dispersal patterns of metabolites from an in-house library of marine cyanobacterial and algal collections. Remarkably, 86% of the metabolomics signals detected were not found in other available datasets of similar nature, supporting the hypothesis that marine cyanobacteria and algae possess distinctive metabolomes. The data were plotted onto a world map representing eight major sampling sites, and revealed potential geographic locations with high chemical diversity. We demonstrate the use of these inventories as a tool to explore the diversity and distribution of natural products. Finally, we utilized this tool to guide the isolation of a new cyclic lipopeptide, yuvalamide A, from a marine cyanobacterium
Configuring Hierarchical Layouts to Address Research Questions
We explore the effects of selecting alternative layouts in hierarchical displays that show multiple aspects of large multivariate datasets, including spatial and temporal characteristics. Hierarchical displays of this type condition a dataset by multiple discrete variable values, creating nested graphical summaries of the resulting subsets in which size, shape and colour can be used to show subset properties. These 'small multiples' are ordered by the conditioning variable values and are laid out hierarchically using dimensional stacking. Crucially, we consider the use of different layouts at different hierarchical levels, so that the coordinates of the plane can be used more effectively to draw attention to trends and anomalies in the data. We argue that these layouts should be informed by the type of conditioning variable and by the research question being explored. We focus on space-filling rectangular layouts that provide data-dense and rich overviews of data to address research questions posed in our exploratory analysis of spatial and temporal aspects of property sales in London. We develop a notation ('HiVE') that describes visualisation and layout states and provides reconfiguration operators, demonstrate its use for reconfiguring layouts to pursue research questions and provide guidelines for this process. We demonstrate how layouts can be related through animated transitions to reduce the cognitive load associated with their reconfiguration whilst supporting the exploratory process
The SSDC contribution to the improvement of knowledge by means of 3D data projections of minor bodies
The latest developments of planetary exploration missions devoted to minor
bodies required new solutions to correctly visualize and analyse data acquired
over irregularly shaped bodies. ASI Space Science Data Center (SSDC-ASI,
formerly ASDC-ASI Science Data Center) worked on this task since early 2013,
when started developing the web tool MATISSE (Multi-purpose Advanced Tool for
the Instruments of the Solar System Exploration) mainly focused on the
Rosetta/ESA space mission data. In order to visualize very high-resolution
shape models, MATISSE uses a Python module (vtpMaker), which can also be
launched as a stand-alone command-line software. MATISSE and vtpMaker are part
of the SSDC contribution to the new challenges imposed by the "orbital
exploration" of minor bodies: 1) MATISSE allows to search for specific
observations inside datasets and then analyse them in parallel, providing
high-level outputs; 2) the 3D capabilities of both tools are critical in
inferring information otherwise difficult to retrieve for non-spherical targets
and, as in the case for the GIADA instrument onboard Rosetta, to visualize data
related to the coma. New tasks and features adding valuable capabilities to the
minor bodies SSDC tools are planned for the near future thanks to new
collaborations
Computational Statistics and Data Visualization
This book is the third volume of the Handbook of Computational Statistics and covers the field of Data Visualization. In line with the companion volumes, it contains a collection of chapters by experts in the field to present readers with an up-to-date and comprehensive overview of the state of the art. Data Visualization is an active area of application and research and this is a good time to gather together a summary of current knowledge. Graphic displays are often very effective at communicating information. They are also very often not effective at communicating information. Two important reasons for this state of affairs are that graphics can be produced with a few clicks of the mouse without any thought, and that the design of graphics is not taken seriously in many scientific textbooks. Some people seem to think that preparing good graphics is just a matter of common sense (in which case their common sense cannot be in good shape) and others believe that preparing graphics is a low-level task, not appropriate for scientific attention. This volume of the Handbook of Computational Statistics takes graphics for Data Visualization seriously.Data Visualization, Exploratory Graphics.
Phenotype and animal domestication : A study of dental variation between domestic, wild, captive, hybrid and insular Sus scrofa
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Acknowledgements We thank the institutions and individuals that provided access to collections, especially the curators of the Museum für Naturkunde, Berlin; Zoologische Staatssammlung, München; Muséum National d’Histoire Naturelle, Paris; Muséum d’Histoire Naturelle, Genève; National Museum of Natural History, Washington; The Field Museum, Chicago and The American Museum of Natural History, New-York. We also thank Jean-Denis Vigne, Nelly Gidaszewski, Vincent Debat and Mathieu Joron for fruitful discussions. This work was supported by a research grant from the Natural Environment Research Council, UK (grant number NE/F003382/1).Peer reviewedPublisher PD
Towards Better Understanding Researcher Strategies in Cross-Lingual Event Analytics
With an increasing amount of information on globally important events, there
is a growing demand for efficient analytics of multilingual event-centric
information. Such analytics is particularly challenging due to the large amount
of content, the event dynamics and the language barrier. Although memory
institutions increasingly collect event-centric Web content in different
languages, very little is known about the strategies of researchers who conduct
analytics of such content. In this paper we present researchers' strategies for
the content, method and feature selection in the context of cross-lingual
event-centric analytics observed in two case studies on multilingual Wikipedia.
We discuss the influence factors for these strategies, the findings enabled by
the adopted methods along with the current limitations and provide
recommendations for services supporting researchers in cross-lingual
event-centric analytics.Comment: In Proceedings of the International Conference on Theory and Practice
of Digital Libraries 201
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