A progressive development of a visual analysis interface of climate-related VGI

AbstractThis paper describes the progressive development of three approaches of successively increasing analytic functionality for visually exploring and analysing climate-related volunteered geographic information. The information is collected in the CitizenSensing project within which urban citizens voluntarily submit reports of site-specific extreme weather conditions, their impacts, and recommendations for best-practice adaptation measures. The work has pursued an iterative development process where the limitations of one approach have become the trigger for the subsequent ones. The proposed visual exploration approaches are: an initial map application providing a low-level data overview, a visual analysis prototype comprising three visual dashboards for more in-depth exploration, and a final custom-made visual analysis interface, the CitizenSensing Visual Analysis Interface (CS-VAI), which enables the flexible multifaceted exploration of the climate-related geographic information in focus. The approaches developed in this work are assessed with volunteered data collected in two of the CitizenSensing project’s campaigns held in the city of Norrköping, Sweden.

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Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

BMC Genomics ◽

10.1186/s12864-021-07791-z ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Ratanond Koonchanok ◽

Swapna Vidhur Daulatabad ◽

Quoseena Mir ◽

Khairi Reda ◽

Sarath Chandra Janga

Keyword(s):

Single Molecule ◽

Visual Analytics ◽

Visual Analysis ◽

Direct Sequencing ◽

Visual Exploration ◽

Nanopore Sequencing ◽

Sequencing Data ◽

Rna Sequences ◽

Sequencing Technologies ◽

Signal Features

Abstract Background Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data. Result Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization. Conclusions Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

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TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data

Information Visualization ◽

10.1177/1473871619858937 ◽

2019 ◽

Vol 19 (1) ◽

pp. 3-23

Author(s):

Aurea Soriano-Vargas ◽

Bernd Hamann ◽

Maria Cristina F de Oliveira

Keyword(s):

Visual Analytics ◽

Visual Analysis ◽

Multivariate Data ◽

Visual Exploration ◽

Data Sets ◽

Time Varying ◽

Domain Experts ◽

Data Mining Algorithms ◽

Temporal Relationships ◽

Visualization Techniques

We present an integrated interactive framework for the visual analysis of time-varying multivariate data sets. As part of our research, we performed in-depth studies concerning the applicability of visualization techniques to obtain valuable insights. We consolidated the considered analysis and visualization methods in one framework, called TV-MV Analytics. TV-MV Analytics effectively combines visualization and data mining algorithms providing the following capabilities: (1) visual exploration of multivariate data at different temporal scales, and (2) a hierarchical small multiples visualization combined with interactive clustering and multidimensional projection to detect temporal relationships in the data. We demonstrate the value of our framework for specific scenarios, by studying three use cases that were validated and discussed with domain experts.

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Critical Land Detection using Remote Sensing Device and Geographic Information (Case Study of Critical Land Basic of Catchments Area, Alang, Wonogiri)

Forum Geografi ◽

10.23917/forgeo.v19i1.4567 ◽

2017 ◽

Vol 19 (1) ◽

pp. 1

Author(s):

Beny Harjadi

Keyword(s):

Remote Sensing ◽

Field Survey ◽

Critical Level ◽

Satellite Image ◽

Geographic Information ◽

Level Data ◽

The Difference

Work criteria and indicator of Catchments Area need to be determined because the success and the failure of cultivating Catchments Area can be monitored and evaluated through the determined criteria. Criteria Indicators in utilizing land, one of them is determined based on the erosion index and the ability of utilizing land, for analyzing the land critical level. However, the determination of identification and classification of land critical level has not been determined; as a result the measurement of how wide the real critical land is always changed all the year. In this study, it will be tried a formula to determine the land critical/eve/ with various criteria such as: Class KPL (Ability of Utilizing Land) and the difference of the erosion tolerance value with the great of the erosion compared with land critical level analysis using remote sensing devices. The aim of studying land critical level detection using remote sensing tool and Geographic Information System (SIG) are:1. The backwards and the advantages of critical and analysis method2. Remote Sensing Method for critical and classification3. Critical/and surveyed method in the field (SIG) Collecting and analyzing data can be found from the field survey and interpretation of satellite image visually and using computer. The collected data are analyzed as:a. Comparing the efficiency level and affectivity of collecting biophysical data through field survey, sky photo interpretation, and satellite image analysis.b. Comparing the efficiency level and affectivity of land critical level data that are found from the result of KPL with the result of the measurement of the erosion difference and erosion tolerance.

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Regional assessment of climate risks using GIS technologies (on the example of the Belgorod Region)

Proceedings of the International conference “InterCarto/InterGIS” ◽

10.35595/2414-9179-2020-1-26-271-278 ◽

2020 ◽

Vol 26 (1) ◽

pp. 271-278

Author(s):

Yuri Chendev ◽

Maria Lebedeva ◽

Olga Krymskaya ◽

Maria Petina

Keyword(s):

Climate Change ◽

Quantitative Assessment ◽

Weather Conditions ◽

Climatic Conditions ◽

Winter Period ◽

Adaptation Measures ◽

Climate Services ◽

Climate Risks ◽

Weather And Climate ◽

The Impact

The ongoing climate change requires a quantitative assessment of the impact of weather conditions on the nature and livelihoods of the population. However, to date, the concept of “climate risk” has not been finally defined, and the corresponding terminology is not universally recognized. One manifestation of climate change is an increase in climate variability and extremeness in many regions. At the same time, modern statistics indicate growing worldwide damage from dangerous weather and climate events. The most widely used in climate services is the concept of “Vulnerability index”, which reflects a combination (with or without weighing) of several indicators that indicate the potential damage that climate change can cause to a particular sector of the economy. development of adaptation measures to ensure sustainable development of territories. The main criterion for the vulnerability of the territory from the point of view of meteorological parameters is the extremeness of the basic values: daily air temperature, daily precipitation, maximum wind speed. To fully take into account the possible impacts of extreme climatic conditions on the region’s economy, it is necessary to detail the weather and climate risks taking into account the entire observation network, since significant differences in quantitative assessment are possible. The obtained average regional values of the climate vulnerability indices for the Belgorod Region of the Russian Federation provide 150 points for the winter period, 330 points for the summer season, which indicates the prevalence of extreme weather conditions in the warm season. Most of the territory has a relative influence on climatic phenomena, with the exception of the East and the Southeast Region. Moreover, the eastern part of the region is the most vulnerable in climatic terms.

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Volunteered Geographic Information: Interpretation, Visualisation and Social Computing (VGIscience)

Proceedings of the ICA ◽

10.5194/ica-proc-1-15-2018 ◽

2018 ◽

Vol 1 ◽

pp. 1-5 ◽

Cited By ~ 1

Author(s):

Dirk Burghardt ◽

Wolfgang Nejdl ◽

Jochen Schiewe ◽

Monika Sester

Keyword(s):

Visual Analysis ◽

Spatial Information ◽

Volunteered Geographic Information ◽

Scientific Basis ◽

Geographic Information ◽

Sensor Data ◽

Short Paper ◽

German Research Foundation ◽

Knowledge Presentation ◽

Large Heterogeneity

In the past years Volunteered Geographic Information (VGI) has emerged as a novel form of user-generated content, which involves active generation of geo-data for example in citizen science projects or during crisis mapping as well as the passive collection of data via the user’s location-enabled mobile devices. In addition there are more and more sensors available that detect our environment with ever greater detail and dynamics. These data can be used for a variety of applications, not only for the solution of societal tasks such as in environment, health or transport fields, but also for the development of commercial products and services. The interpretation, visualisation and usage of such multi-source data is challenging because of the large heterogeneity, the differences in quality, the high update frequencies, the varying spatial-temporal resolution, subjective characteristics and low semantic structuring.<br> Therefore the German Research Foundation has launched a priority programme for the next 3&ndash;6 years which will support interdisciplinary research projects. This priority programme aims to provide a scientific basis for raising the potential of VGI- and sensor data. Research questions described more in detail in this short paper span from the extraction of spatial information, to the visual analysis and knowledge presentation, taking into account the social context while collecting and using VGI.

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Simple Geography-Related Multimedia

E-Learning for Geographers ◽

10.4018/978-1-59904-980-9.ch012 ◽

2010 ◽

pp. 204-221

Author(s):

Richard Treves

Keyword(s):

Information Systems ◽

Geographic Information Systems ◽

Best Practice ◽

Geographic Information ◽

University Level

Teaching geography at university level involves students in study of complex diagrams and maps. These can be made easier to understand if split into parts. This chapter reports the work of a team writing a series of courses in geographic information systems (GIS) and their solution to the problem, which involved authoring simple multimedia animations using Microsoft PowerPoint™ software. The animations were authored by those writing the courses with little input from the multimedia Web specialist supporting the team. The techniques that the team used to produce the animations are explained, as are the nine points of best practice that were developed and how the animations were used with other non-animated content. Three sub-categories of these animations are described and explained and the issues of maintenance and reuse of the animated content is considered.

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The impact of extreme weather on mass-participation sporting events

International Journal of Event and Festival Management ◽

10.1108/ijefm-04-2018-0027 ◽

2019 ◽

Vol 10 (2) ◽

pp. 95-109

Author(s):

Julia Kathryn Giddy

Keyword(s):

Best Practice ◽

Weather Conditions ◽

Extreme Weather ◽

Survey Method ◽

Sporting Events ◽

Content Type ◽

Sport Events ◽

Mass Participation ◽

The Impact ◽

Insight Into

Purpose The purpose of this paper is to investigate the impact of extreme weather on tourism events through the perceptions of participants, using the case of the 2017 Cape Town Cycle Tour (CTCT). Design/methodology/approach This study utilized a survey method to collect data. Questionnaires were distributed online to would-be participants in the cancelled 2017 CTCT. The questionnaire included both fixed-response and open-ended questions. Findings The results show that participants experienced mixed emotions to event cancellation. Most felt that the weather conditions warranted cancellation, but some concerns emerged as to how the cancellation was managed. In addition, many felt that the organization of the race needs to be rethought due to numerous negative weather experiences in recent years. Research limitations/implications The findings in this study are exploratory. They focus on a single event in one city. However, they provide important initial insight into how sporting event participants react to the negative impacts of extreme weather. Practical implications These results have important management implications in addressing the impact of weather on the events sector. They are significant in understanding best practice with regard to managing participants in the case of weather impacts on an event. They also demonstrate interesting results with regard to participant loyalty among active sport events tourists. Originality/value The originality of this study is in its extension of the broad discussion of the impact of extreme weather and climate change on tourism to the events sector. The implications of changing weather and climatic patterns on events, particularly mass-participation sporting events, are clear and need to be considered in order to effectively manage future impacts on this important economic sector. This is done by providing insight into how participants respond to these types of circumstances.

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Visual Data Mining of Multimedia Data for Social and Behavioral Studies

Information Visualization ◽

10.1057/ivs.2008.32 ◽

2009 ◽

Vol 8 (1) ◽

pp. 56-70 ◽

Cited By ~ 13

Author(s):

Chen Yu ◽

Yiwen Zhong ◽

Thomas Smith ◽

Ikhyun Park ◽

Weixia Huang

Keyword(s):

Data Mining ◽

Visual Analysis ◽

Hybrid Approach ◽

Heterogeneous Data ◽

Multimedia Data ◽

Visual Exploration ◽

Visual Data Mining ◽

Flexible Tool ◽

Visualization System ◽

Behavioral Studies

With advances in computing techniques, a large amount of high-resolution high-quality multimedia data (video and audio, and so on) has been collected in research laboratories in various scientific disciplines, particularly in cognitive and behavioral studies. How to automatically and effectively discover new knowledge from rich multimedia data poses a compelling challenge because most state-of-the-art data mining techniques can only search and extract pre-defined patterns or knowledge from complex heterogeneous data. In light of this challenge, we propose a hybrid approach that allows scientists to use data mining as a first pass, and then forms a closed loop of visual analysis of current results followed by more data mining work inspired by visualization, the results of which can be in turn visualized and lead to the next round of visual exploration and analysis. In this way, new insights and hypotheses gleaned from the raw data and the current level of analysis can contribute to further analysis. As a first step toward this goal, we implement a visualization system with three critical components: (1) a smooth interface between visualization and data mining; (2) a flexible tool to explore and query temporal data derived from raw multimedia data; and (3) a seamless interface between raw multimedia data and derived data. We have developed various ways to visualize both temporal correlations and statistics of multiple derived variables as well as conditional and high-order statistics. Our visualization tool allows users to explore, compare and analyze multi-stream derived variables and simultaneously switch to access raw multimedia data.

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Ploceus: Modeling, visualizing, and analyzing tabular data as networks

Information Visualization ◽

10.1177/1473871613488591 ◽

2013 ◽

Vol 13 (1) ◽

pp. 59-89 ◽

Cited By ~ 13

Author(s):

Zhicheng Liu ◽

Shamkant B Navathe ◽

John T Stasko

Keyword(s):

Visual Analysis ◽

Dynamic Network ◽

Visual Exploration ◽

Tabular Data ◽

Immediate Feedback ◽

Levels Of Abstraction ◽

Multiple Networks ◽

Algebraic Framework ◽

Network Manipulation ◽

User Actions

Tabular data are pervasive. Although tables often describe multivariate data without explicit definitions of a network, it may be advantageous to explore the data by modeling it as a graph or network for analysis. Even when a given table design specifies a network structure, analysts may want to look at multiple networks from different perspectives, at different levels of abstraction, and with different edge semantics. We present a system called Ploceus that offers a general approach for performing multidimensional and multilevel network–based visual analysis on multivariate tabular data. Powered by an underlying relational algebraic framework, Ploceus supports flexible construction and transformation of networks through a direct manipulation interface and integrates dynamic network manipulation with visual exploration through immediate feedback mechanisms. We report our findings on the learnability and usability of Ploceus and propose a model of user actions in visualization construction using Ploceus.

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Modeling and evaluating user behavior in exploratory visual analysis

Information Visualization ◽

10.1177/1473871616638546 ◽

2016 ◽

Vol 15 (4) ◽

pp. 325-339 ◽

Cited By ~ 7

Author(s):

Khairi Reda ◽

Andrew E. Johnson ◽

Michael E. Papka ◽

Jason Leigh

Keyword(s):

Visual Analysis ◽

User Behavior ◽

Empirical Evaluation ◽

Visual Exploration ◽

Chain Process ◽

Visualization System ◽

Log Files ◽

Analytic Process ◽

Visualization Systems ◽

Analytical Tools

Empirical evaluation methods for visualizations have traditionally focused on assessing the outcome of the visual analytic process as opposed to characterizing how that process unfolds. There are only a handful of methods that can be used to systematically study how people use visualizations, making it difficult for researchers to capture and characterize the subtlety of cognitive and interaction behaviors users exhibit during visual analysis. To validate and improve visualization design, it is important for researchers to be able to assess and understand how users interact with visualization systems under realistic scenarios. This article presents a methodology for modeling and evaluating the behavior of users in exploratory visual analysis. We model visual exploration using a Markov chain process comprising transitions between mental, interaction, and computational states. These states and the transitions between them can be deduced from a variety of sources, including verbal transcripts, videos and audio recordings, and log files. This model enables the evaluator to characterize the cognitive and computational processes that are essential to insight acquisition in exploratory visual analysis and reconstruct the dynamics of interaction between the user and the visualization system. We illustrate this model with two exemplar user studies, and demonstrate the qualitative and quantitative analytical tools it affords.

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