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Visual Highlighting Methods for Geovisualization
VISUAL HIGHLIGHTING METHODS FOR GEOVISUALIZATION Anthony C. Robinson GeoVISTA Center, Department of Geography 302 Walker Building The Pennsylvania State University University Park, PA 16802, USA [email protected] ABSTRACT A key advantage of interactive geovisualization tools is that users are able to quickly view data observations across multiple views. This is usually supported with a transient visual effect applied around the edges of an object during a mouse selection or rollover. This effect, commonly called highlighting, has not received much attention in geovisualization research. Today, most geovisualization tools rely on simple color-based highlighting. This paper proposes additional visual highlighting methods that could be used in geovisualizations. It also presents a typology of interactive highlighting behaviors that specify multiple ways in which highlighting techniques can be blended together or modified based on data values to enhance visual recognition in multiple coordinated view applications. INTRODUCTION The key analytical affordances of geovisualization tools include dynamic interactive behaviors and coordinated multiple views of geospatial data. Much attention in geovisualization research is devoted to developing new types of views, integrating new types of data, and designing customized systems for specific analytical tasks and domains (MacEachren and Kraak, 2001). This paper focuses on refining and extending the interactively-driven visual indication, known as highlighting, that allows users to make connections between data objects in multiple views in a geovisualization. As data and the number of views we use to explore those data become increasingly complicated (Andrienko et al., 2007), it is timely to consider new highlighting methods to ensure that visual discovery is efficient and effective. -
The Fourth Paradigm
ABOUT THE FOURTH PARADIGM This book presents the first broad look at the rapidly emerging field of data- THE FOUR intensive science, with the goal of influencing the worldwide scientific and com- puting research communities and inspiring the next generation of scientists. Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud- computing technologies. This collection of essays expands on the vision of pio- T neering computer scientist Jim Gray for a new, fourth paradigm of discovery based H PARADIGM on data-intensive science and offers insights into how it can be fully realized. “The impact of Jim Gray’s thinking is continuing to get people to think in a new way about how data and software are redefining what it means to do science.” —Bill GaTES “I often tell people working in eScience that they aren’t in this field because they are visionaries or super-intelligent—it’s because they care about science The and they are alive now. It is about technology changing the world, and science taking advantage of it, to do more and do better.” —RhyS FRANCIS, AUSTRALIAN eRESEARCH INFRASTRUCTURE COUNCIL F OURTH “One of the greatest challenges for 21st-century science is how we respond to this new era of data-intensive -
Connected 2D and 3D Visualizations for the Interactive Exploration of Spatial Information
CONNECTED 2D AND 3D VISUALIZATIONS FOR THE INTERACTIVE EXPLORATION OF SPATIAL INFORMATION S. Bleisch *, S. Nebiker FHNW, University of Applied Sciences Northwestern Switzerland, Institute of Geomatics Engineering, CH-4132 Muttenz, Switzerland - (susanne.bleisch, stephan.nebiker)@fhnw.ch KEY WORDS: Geovisualization, Three-dimensional representation, Interactive, Spatial Data Exploration, Virtual globe, Development ABSTRACT: This paper describes the concepts and the successful prototypal implementation of interactively connected 2D information visualizations and data displays in 3D virtual environments for the interactive exploration of spatial data and information. Virtual globes or earth viewers such as Google Earth have become very popular over the last few years. They are used for looking at holiday destinations but more importantly also for scientific visualizations. From a geovisualization point of view we might regard 3D data or information displays as yet another representation type that adds to the multitude of information visualization methods. Combining 3D views of data sets with traditional 2D displays offers the advantage of being able to use 3D if and when this type of representation is considered useful or effective for finding new insights into a data set. The traditional and newer displays of mainly 2D information visualization may be enhanced and new insights into the data may be generated by displays of the data in a 3D virtual environment. On the other hand, data in 3D displays might be better understood by simultaneously reading and querying connected 2D representations.The paper presents a prototypal implementation of the interactively connected visualizations of spatial information in 2D views and 3D virtual environments using the brushing technique. -
(Geo-)Visualization
Geographic Data Science - Lecture III (Geo-)Visualization Dani Arribas-Bel Today Visualization What and why History Examples Geovisualization What "A map for everyone" Dangers of geovisualization Visualization "Data graphics visually display measured quantities by means of the combined use of points, lines, a coordinate system, numbers, symbols, words, shading, and color." The Visual Display of Quantitative Information. Edward R. Tufte. [Source] [Source] A bit of history Maps A bit of history Maps --> Data Maps (XVIIth.C.) A bit of history Maps --> Data Maps (XVIIth.C.) --> Time series (1786) A bit of history Maps --> Data Maps (XVIIth.C.) --> Time series (1786) --> Scatter plots A bit of history Maps --> Data Maps (XVIIth.C.) --> Time series (1786) --> Scatter plots Surprisingly recent: 1750-1800 approx. (much later than many other advances in math and stats!) William Playfair's "linear arithmetic": encode/replace numbers in tables into visual representations. Other relevant names throughout history: Lambert, Minard, Marey. Visualization The Visual Display of Quantitative Information. Edward R. Tufte. By encoding information visually, they allow to present large amounts of numbers in a meaninful way. If well made, visualizations provide leads into the processes underlying the graphic. Learning by seeing time... Time series [Source] XVIIIth. Cent. - Pytometrie by J. H Lambert Bar chart [Source] Playfair's bar chart in The Commercial and Political Atlas (1786) Abstract line plot [Source] Lambert - Evaporation rate against temperature, 1769 Minard - Napoleon army map (XIXth. Cent.) [Source] "It may well be the best statistical graphic ever drawn" (E. R. Tufte) Geovisualization Tufte (1983) "The most extensive data maps [...] place millions of bits of information on a single page before our eyes. -
Geovisualization: Integration and Visualization of Multiple Datasets Using Mapbox Cecilia Cadenas California Polytechnic State University, San Luis Obispo
Geovisualization: Integration and Visualization of Multiple Datasets Using Mapbox Cecilia Cadenas California Polytechnic State University, San Luis Obispo Abstract—The use of geovisualizations to different from information visualization dealing analyze multiple datasets can ease the with abstract data spaces. [3] research and investigation to find B. Mapbox & TileMill correlations between these datasets. However, making these visualizations with The creation of these visualizations can be multiple datasets can be challenging due to challenging due to the complexity and the lack of standardization within file formats differences between the geographical data types, and the software needed to render the and how easily they can be accessed and used. visualizations. In order to help with the creation of these visualizations, many cartographers and software This project investigates the making of engineers have created many different tools that these visualizations, maps in this case, using can make the creation of these visualizations an open source platforms like Mapbox. Using easier and accessible to anyone with a computer. Python scripts for the data parsing, For the creation of the maps in this project, CartoCSS for the designing of the maps, one of these tools was used. After some research JavaScript to make the maps interactive, and and testing different tools and platforms, HTML to combine all the layers together a Mapbox was selected as the best option for the set of maps were created. These maps customization level needed for the maps wanted. contained data regarding tons of wine grape Mapbox is an online platform that makes the data crushed and yearly heat accumulation viewing of these maps simple across multiple during the growing season that demonstrate platforms since it requires no extra software to how combining multiple data sets can lead to be downloaded. -
What Is Geovisualization? to the Growing Field of Geovisualization
This issue of GeoMatters is devoted What is Geovisualization? to the growing field of geovisualization. Brian McGregor uses geovisualiztion to by Joni Storie produce animated maps showing settle- ment patterns of Hutterite colonies. Dr. Marc Vachon’s students use it to produce From a cartography perspective, dynamic presentation options to com- videos about urban visualization (City geovisualization represents a change in municate knowledge. For example, at- Hall and Assiniboine Park), while Dr. how knowledge is formed and repre- lases require extra planning compared Chris Storie shows geovisualiztion for sented. Traditional cartography is usu- to individual maps, structurally they retail mapping in Winnipeg. Also in this issue Honours students describe their ally seen a visualization (a.k.a. map) could include hundreds of maps, and thesis projects for the upcoming collo- that is presented after the conclusion all the maps relate to each other. Dr. quium next March, Adrienne Ducharme is reached to emphasize or compliment Danny Blair and Dr. Ian Mauro, in the tells us about her graduate research at the research conclusions. Geovisual- Department of Geography, provide an ELA, we have a report about Cultivate ization changes this format by incor- excellent example of this integration UWinnipeg and our alumni profile fea- porating spatial data into the analysis with the Prairie Climate Atlas (http:// tures Michelle Méthot (Smith). (O’Sullivan and Unwin, 2010). Spatial www.climateatlas.ca/). The combina- Please feel free to pass this newsletter data, statistics and analysis are used to tion of maps with multimedia provides to anyone with an interest in geography. answer questions which contribute to for better understanding as well as en- Individuals can also see GeoMatters at the Geography website, or keep up with the conclusion that is reached within riched and informative experiences of us on Facebook (Department of Geog- the research. -
The Diversity of Data and Tasks in Event Analytics
The Diversity of Data and Tasks in Event Analytics Catherine Plaisant, Ben Shneiderman Abstract— The growing interest in event analytics has resulted in an array of tools and applications using visual analytics techniques. As we start to compare and contrast approaches, tools and applications it will be essential to develop a common language to describe the data characteristics and diverse tasks. We propose a characterisation of event data along 3 dimensions (temporal characteristics, attributes and scale) and propose 8 high-level user tasks. We look forward to refining the lists based on the feedback of workshop attendees. KEYWORDS having the same time stamp, medical data are often Temporal analysis, pattern analysis, task analysis, taxonomy, big recorded in batches after the fact. data, temporal visualization o The relevant time scale may vary (from milliseconds to years), and may be homogeneous or not. INTRODUCTION o Data may represent changes over time of a status The growing interest in event analytics (e.g. Aigner et al, 2011; indicator, e.g. changes of cancer stages, student status or Shneiderman and Plaisant, 2016) has resulted in an array of novel physical presence in various hospital services, or may tools and applications using visual analytics techniques. As represent a set of events or actions that are not exclusive researchers compare and contrast approaches it will be helpful to from one another, e.g. actions in a computer log or series develop a common language to describe the diverse tasks and data of symptoms and medical tests. characteristics analysts encounter. o Patterns may be very cyclical or not, and this may vary The methodology of design studies - which primarily focus on over time. -
Visual Bandwidth Selection for Kernel Density Maps
Photogrammetrie • Fernerkundung • Geoinformation 5/2009, S. 445–454 Visual Bandwidth Selection for Kernel Density Maps Jukka M. krisp, stefan peters,Christian e. Murphy & hongChao fan, München Keywords: Kernel Density, Visualization, Visual Analytics, Geostatistics, Kernel Bandwidth, Cartography Summary: Within this paper we investigate the Zusammenfassung: Visuelle Radius Festlegung challenge to find an appropriate bandwidth in ker- für Kernel Dichte Abschätzungen. In dieser Arbeit nel density estimation. Kernel density estimation untersuchen wir die Möglichkeiten, um einen ange- methods can be used in visualizing and analyzing messenen Radius in der Kernel-Dichte Schätzung spatial data, with the objective of understanding zu erhalten. Kernel-Dichte Schätzung Methoden and potentially predicting event patterns. Our aim können in der Visualisierung und Analyse räumli- is to provide a computational tool to visually select cher Daten zum Verständnis und zur Vorhersage the bandwidth parameter and to visually investi- von räumlichen Mustern dienen. Unser Ziel ist es, gate the effect of different parameters within the ein Computer-Werkzeug zur visuellen Parameter kernel density calculations. With this tool the user Bestimmung zu entwickeln. Die Radien verschie- is able to visually find the most appropriate band- deneR Kernel werden visuell geprüft und können width foR the particular dataset and scale. The slid- experimentell untersucht werden. Mit diesem er-tool includes a graphical user interface and can Werkzeug kann der Anwender den am besten ge- read point datasets. A specific number of kernel eigneten Radius für den jeweiligen Datensatz be- density maps are generated by using a range of stimmen. Das Schieberegler-Werkzeug beinhaltet bandwidths. In the graphical interface these kernel eine grafische Benutzeroberfläche und kann Punkt- density maps can be drawn near real-time while the datensätze einladen. -
Recent Publications 1984 — 2017 Issues 1 — 100
RECENT PUBLICATIONS 1984 — 2017 ISSUES 1 — 100 Recent Publications is a compendium of books and articles on cartography and cartographic subjects that is included in almost every issue of The Portolan. It was compiled by the dedi- cated work of Eric Wolf from 1984-2007 and Joel Kovarsky from 2007-2017. The worldwide cartographic community thanks them greatly. Recent Publications is a resource for anyone interested in the subject matter. Given the dates of original publication, some of the materi- als cited may or may not be currently available. The information provided in this document starts with Portolan issue number 100 and pro- gresses to issue number 1 (in backwards order of publication, i.e. most recent first). To search for a name or a topic or a specific issue, type Ctrl-F for a Windows based device (Command-F for an Apple based device) which will open a small window. Then type in your search query. For a specific issue, type in the symbol # before the number, and for issues 1— 9, insert a zero before the digit. For a specific year, instead of typing in that year, type in a Portolan issue in that year (a more efficient approach). The next page provides a listing of the Portolan issues and their dates of publication. PORTOLAN ISSUE NUMBERS AND PUBLICATIONS DATES Issue # Publication Date Issue # Publication Date 100 Winter 2017 050 Spring 2001 099 Fall 2017 049 Winter 2000-2001 098 Spring 2017 048 Fall 2000 097 Winter 2016 047 Srping 2000 096 Fall 2016 046 Winter 1999-2000 095 Spring 2016 045 Fall 1999 094 Winter 2015 044 Spring -
Middlesex University Research Repository
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Middlesex University Research Repository Middlesex University Research Repository An open access repository of Middlesex University research http://eprints.mdx.ac.uk Shepherd, Ifan D. H. (2008) Travails in the third dimension: a critical evaluation of three-dimensional geographical visualization. In: Geographic visualization: concepts, tools and applications. Dodge, Martin and McDerby, Mary and Turner, Martin, eds. John Wiley & Sons, Chichester, pp. 199-222. ISBN 9780470515112 http://dx.doi.org/10.1002/9780470987643 Submitted Version Available from Middlesex University’s Research Repository at http://eprints.mdx.ac.uk/6588/ Copyright: Middlesex University Research Repository makes the University’s research available electronically. Copyright and moral rights to this thesis/research project are retained by the author and/or other copyright owners. The work is supplied on the understanding that any use for commercial gain is strictly forbidden. A copy may be downloaded for personal, non- commercial, research or study without prior permission and without charge. Any use of the thesis/research project for private study or research must be properly acknowledged with reference to the work’s full bibliographic details. This thesis/research project may not be reproduced in any format or medium, or extensive quotations taken from it, or its content changed in any way, without first obtaining permission in writing from the copyright holder(s). If you believe that any material held in the repository infringes copyright law, please contact the Repository Team at Middlesex University via the following email address: [email protected] The item will be removed from the repository while any claim is being investigated. -
Quantitative Literacy to New Quantitative Literacies
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/319160466 Quantitative Literacy to New Quantitative Literacies Chapter · May 2017 CITATIONS READS 0 39 3 authors, including: Rohit Mehta James P. Howard California State University, Fresno Johns Hopkins University 32 PUBLICATIONS 42 CITATIONS 13 PUBLICATIONS 0 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: MSU-Wipro STEM & Leadership View project I Wonder: Research To Practice View project All content following this page was uploaded by Rohit Mehta on 18 October 2017. The user has requested enhancement of the downloaded file. 5 Quantitative Literacy to New Quantitative Literacies Jeffrey Craig, Rohit Mehta; James P. Howard II Michigan State University; University of Maryland University College 5.1 Introduction Steen and colleagues [42] made their Case for Quantitative Literacy based on the premise that the 21st-century, pri- marily due to technology changes, is a significantly more quantitative environment than any previous time in history. The design team who wrote the case made rhetorical observations about the increasing prevalence of numbers in society in the United States; phrases like [a] world awash in numbers [42] precede nearly every piece of literature regarding quantitative literacy (or numeracy). The authors used this rhetoric to position people relative to the demands of social systems in the world. Specifically, numeracy has emerged as a partner to literacy because the social world is being integrated with numbers due to recent technological advances. Steen argued that as the printing press gave the power of letters to the masses, so the computer gives the power of number to ordinary citizens [40, p. -
Surfacing Visualization Mirages
Surfacing Visualization Mirages Andrew McNutt Gordon Kindlmann Michael Correll University of Chicago University of Chicago Tableau Research Chicago, IL Chicago, IL Seattle, WA [email protected] [email protected] [email protected] ABSTRACT In this paper, we present a conceptual model of these visual- Dirty data and deceptive design practices can undermine, in- ization mirages and show how users’ choices can cause errors vert, or invalidate the purported messages of charts and graphs. in all stages of the visual analytics (VA) process that can lead These failures can arise silently: a conclusion derived from to untrue or unwarranted conclusions from data. Using our a particular visualization may look plausible unless the an- model we observe a gap in automatic techniques for validating alyst looks closer and discovers an issue with the backing visualizations, specifically in the relationship between data data, visual specification, or their own assumptions. We term and chart specification. We address this gap by developing a such silent but significant failures visualization mirages. We theory of metamorphic testing for visualization which synthe- describe a conceptual model of mirages and show how they sizes prior work on metamorphic testing [92] and algebraic can be generated at every stage of the visual analytics process. visualization errors [54]. Through this combination we seek to We adapt a methodology from software testing, metamorphic alert viewers to situations where minor changes to the visual- testing, as a way of automatically surfacing potential mirages ization design or backing data have large (but illusory) effects at the visual encoding stage of analysis through modifications on the resulting visualization, or where potentially important to the underlying data and chart specification.