Information Visualization Techniques Research Articles

Data by Proxy - Material Traces as Autographic Visualizations.

Information visualization limits itself, per definition, to the domain of symbolic information. This paper discusses arguments why the field should also consider forms of data that are not symbolically encoded, including physical traces and material indicators. Continuing a provocation presented by Pat Hanrahan in his 2004 IEEE Vis capstone address, this paper compares physical traces to visualizations and describes the techniques and visual practices for producing, revealing, and interpreting them. By contrasting information visualization with a speculative counter model of autographic visualization, this paper examines the design principles for material data. Autographic visualization addresses limitations of information visualization, such as the inability to directly reflect the material circumstances of data generation. The comparison between the two models allows probing the epistemic assumptions behind information visualization and uncovers linkages with the rich history of scientific visualization and trace reading. The paper begins by discussing the gap between data visualizations and their corresponding phenomena and proceeds by investigating how material visualizations can bridge this gap. It contextualizes autographic visualization with paradigms such as data physicalization and indexical visualization and grounds it in the broader theoretical literature of semiotics, science and technology studies (STS), and the history of scientific representation. The main section of the paper proposes a foundational design vocabulary for autographic visualization and offers examples of how citizen scientists already use autographic principles in their displays, which seem to violate the canonical principles of information visualization but succeed at fulfilling other rhetorical purposes in evidence construction. The paper concludes with a discussion of the limitations of autographic visualization, a roadmap for the empirical investigation of trace perception, and thoughts about how information visualization and autographic visualization techniques can contribute to each other.

Information visualisation methods and techniques: State-of-the-art and future directions

Abstract Visualisation research explores techniques for conveying information in a meaningful way to allow users to make sense of data. This paper aims to review state-of-the-art information visualisation methods and techniques particularly for farmed data in defence simulations. It also discusses some of the key visualisation design challenges and outlines a conceptual framework for future research directions in information visualisation. It further presents a concept demonstrator that has been designed and developed to visualise joint force simulations for the purpose of showcasing some of the key concepts in the proposed information visualisation conceptual framework.

Reflecting on Global South planning and planning literature

ABSTRACT There is limited literature pertaining to planning in the Global South, in comparison to the literature base of planning in the global North, and some believe that much of the planning literature on the Global South comes from outside the continent, and does not reflect indigenous African-knowledge. The aim of this paper is to evaluate literature relating to South African planning approaches as point of departure to validate the claims pertaining to authorship of literature, and to further investigate the thematic content that is published. The empirical investigation considered 125 papers that were identified through a qualitative inquiry as part of theory-based sampling, where the respective titles of the papers were captured and 345 key words identified and information visualisation techniques employed to illustrate such. Conclusions were drawn with regard to (1) planning literature of South Africa (and references to Africa), (2) current research themes being investigated within the local South African context, and (3) future research opportunities which could advance the science of planning, teaching-learning approaches and contribute to broadening the local planning literature base within the Global South, whilst decolonising urban theory.

Tracing Paths and Connecting Multiple Design Domains: An Information Visualisation Approach to Product Architecture Modelling

AbstractVisual representation of product architecture models is crucial in complex engineering systems design. However, when the number of entities in a model is large and when multiple levels of hierarchies are included, visual representations currently in use need to be more intuitive. As such, improved visual representations that enable better system overview and better communication of essential product- related information among design participants are needed. This paper uses interactive information visualisation techniques – collapsible hierarchical tree, edge bundling and alluvial diagram – and provides the foundations of a computerised tool that improves the traceability of connections between design domains, including stakeholders, requirements, functions, behaviours and structure. The case of a cleaning robot is used as an illustrative example. The approach supports designers by providing an enhanced overview during the development of complex product architecture models, in particular in the communication with external stakeholders, in the identification of change propagation paths across several design domains, and in capturing the design rationale of previous design decisions.

A computational perspective of the periodic table of elements

This paper adopts dimensionality reduction, clustering and information visualization techniques to organize and map a set of 86 chemical elements (CE). Each CE is characterized through 17 properties and the dissimilarities between the CE are measured by different metrics, namely the arccosine, Canberra and Lorentzian distances. The dissimilarity information is then used as input to hierarchical clustering and multidimensional scaling algorithms. The two computational techniques yield 2- and 3-dim maps of the CE organized accordingly to their characteristics. The results can be visualized and interpreted not only under the light of the CE location, but also of the emerging clusters. The new representations constitute an alternative to the classic Cartesian-like 2-dimensional table and point towards advanced scientific visualization using present day computational resources.

Visual Networks As a Means of Representing Collocational Information in Electronic Dictionaries

AbstractThe digital turn in lexicography has paved the way to new techniques for presenting information in dictionaries. This paper explores the potential of collocational networks (Phillips 1983, Williams 1998) as key lexicographical tools to represent information about lexical combinatorics. Collocational networks, which had initially been used as a means of identifying collocations in large corpora, must now be rethought in order to assist non-expert dictionary users in text production by allowing them to find the exact collocates they are looking for, as well as by offering the grammatical information needed to use collocations accurately. We advocate improving networks by incorporating information visualization techniques (Ware 2008, Pham 2012). Specifically, we suggest a number of measures which may be taken to both simplify access to the information provided by raw output from corpora —much of which may be noise for the dictionary user— and to enrich such collocational data by means of visually-explained relevant grammatical information.

Information visualization skills for academic librarians

PurposeThe purpose of this paper is to investigate how scholars in the digital humanities employ information visualization techniques in their research, and how academic librarians should prepare themselves to support this emerging trend.Design/methodology/approachThis study adopts a content analysis methodology, which further draws techniques from data mining, natural language processing and information visualization to analyze three peer-reviewed journals published within the last five years and ten online university library research guides in this field.FindingsTo successfully support and effectively contribute to the digital humanities, academic librarians should be knowledgeable in more than just visualization concepts and tools. The content analysis results for the digital humanities journals reflect the importance of recognizing the wide variety of applications and purposes of information visualization in digital humanities research.Practical implicationsThis study provides useful and actionable insights into how academic librarians can prepare for this emerging technology to support future endeavors in the digital humanities.Originality/valueAlthough information visualization has been widely adopted in digital humanities research, it remains unclear how librarians, especially academic librarians who support digital humanities research, should prepare for this emerging technology. This research is the first study to address this research gap through the lens of actual applications of information visualization techniques in digital humanities research, which is compared against university LibGuides for digital humanities research.

Visual Analysis Scenarios for Understanding Evolutionary Computational Techniques’ Behavior

Machine learning algorithms are used in many applications nowadays. Sometimes, we need to describe how the decision models created output, and this may not be an easy task. Information visualization (InfoVis) techniques (e.g., TreeMap, parallel coordinates, etc.) can be used for creating scenarios that visually describe the behavior of those models. Thus, InfoVis scenarios were used to analyze the evolutionary process of a tool named AutoClustering, which generates density-based clustering algorithms automatically for a given dataset using the EDA (estimation-of-distribution algorithm) evolutionary technique. Some scenarios were about fitness and population evolution (clustering algorithms) over time, algorithm parameters, the occurrence of the individual, and others. The analysis of those scenarios could lead to the development of better parameters for the AutoClustering tool and algorithms and thus have a direct impact on the processing time and quality of the generated algorithms.

VisminerTD: a tool for automatic identification and interactive monitoring of the evolution of technical debt items

Technical debt (TD) contextualizes problems faced during software evolution considering the tasks that are not carried out adequately during software development. Software TD is a type of debt that brings a short-term benefit, but which may have to be paid with interest later on in the software development life cycle. Its presence brings risks to the project and can reduce its quality. It is worthwhile to have automatic mechanisms to monitor it, as TD monitoring requires the analysis of large amounts of complex data. Therefore, the combination of software metrics and code comment analysis, in the identification, and information visualization techniques, in monitoring, present themselves as a promising strategy to manage TD. This work presents VisminerTD, a tool that allows the automatic identification and interactive monitoring of the evolution of TD items by combining software metrics, code comment analysis, and information visualization. To evaluate its applicability, a feasibility study was carried out considering JUnit 4 and Apache Ant software projects. The results indicated that VisminerTD can support software development teams in monitoring TD items. In addition, a second case study was performed to assess the feasibility of the proposed tool regarding its usefulness, ease of use, and self-predicted future use. The results provided positive evidence on the use of the proposed tool, indicating (i) that it can be useful in supporting TD Identification and TD monitoring activities and (ii) that it can bring gains in terms of comprehensiveness and efficacy when evaluating the desirable time to identify and monitor different types of debt. Given the current scenario characterized by limited options of tools that combine different information to support automatic identification and monitoring of the evolution of TD items in software projects, VisminerTD can approximate the state-of-the-art and the state-of-the-practice in the TD area, contributing to a wider dissemination of the concept.

Gestão da informação aplicada aos processos de trabalho do Ibama

Apresenta o estudo de caso em andamento, cujo objetivo é analisar a informação produzida nas atividades finalísticas e registrada nos sistemas informacionais do Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (Ibama) como recurso para a gestão da organização. Discorre acerca da relação entre a relação da Ciência da Informação (CI) e a Arquivologia, sobre o documento e a gestão documental, especialmente no âmbito da administração pública brasileira. Debate sobre o que define a gestão da informação na constituição das informações produzidas pelas organizações e reflete acerca das teorias sobre o comportamento humano em informação e as variáveis contextuais que influenciam em tal comportamento. Tal perspectiva fortalece o mérito do paradigma sociocognitivo da Ciência da Informação, pois traz ao debate os desafios impostos pela sociedade atual. Pesquisa aplicada e descritiva, faz uso da observação-participante. Na sua característica de pesquisa documental, a coleta de dados compreende fontes documentais, dados registrados nos sistemas de informação, além de entrevistas semiestruturadas. Como ferramentas de análise, faz uso de técnicas de visualização da informação e análise qualitativa do conteúdo.

A task-and-technique centered survey on visual analytics for deep learning model engineering

Although deep neural networks have achieved state-of-the-art performance in several artificial intelligence applications in the past decade, they are still hard to understand. In particular, the features learned by deep networks when determining whether a given input belongs to a specific class are only implicitly described concerning a considerable number of internal model parameters. This makes it harder to construct interpretable hypotheses of what the network is learning and how it is learning—both of which are essential when designing and improving a deep model to tackle a particular learning task. This challenge can be addressed by the use of visualization tools that allow machine learning experts to explore which components of a network are learning useful features for a pattern recognition task, and also to identify characteristics of the network that can be changed to improve its performance. We present a review of modern approaches aiming to use visual analytics and information visualization techniques to understand, interpret, and fine-tune deep learning models. For this, we propose a taxonomy of such approaches based on whether they provide tools for visualizing a network’s architecture, to facilitate the interpretation and analysis of the training process, or to allow for feature understanding. Next, we detail how these approaches tackle the tasks above for three common deep architectures: deep feedforward networks, convolutional neural networks, and recurrent neural networks. Additionally, we discuss the challenges faced by each network architecture and outline promising topics for future research in visualization techniques for deep learning models.

Data exploration in evolutionary reconstruction of PET images

This work is based on a cooperative co-evolution algorithm called ‘Fly Algorithm’, which is an evolutionary algorithm (EA) where individuals are called ‘flies’. It is a specific case of the ‘Parisian Approach’ where the solution of an optimisation problem is a set of individuals (e.g. the whole population) instead of a single individual (the best one) as in typical EAs. The optimisation problem considered here is tomography reconstruction in positron emission tomography (PET). It estimates the concentration of a radioactive substance (called a radiotracer) within the body. Tomography, in this context, is considered as a difficult ill-posed inverse problem. The Fly Algorithm aims at optimising the position of 3-D points that mimic the radiotracer. At the end of the optimisation process, the fly population is extracted as it corresponds to an estimate of the radioactive concentration. During the optimisation loop a lot of data is generated by the algorithm, such as image metrics, duration, and internal states. This data is recorded in a log file that can be post-processed and visualised. We propose using information visualisation and user interaction techniques to explore the algorithm’s internal data. Our aim is to better understand what happens during the evolutionary loop. Using an example, we demonstrate that it is possible to interactively discover when an early termination could be triggered. It is implemented in a new stopping criterion. It is tested on two other examples on which it leads to a 60% reduction of the number of iterations without any loss of accuracy.

THE ANALYSIS OF INTERNET MARKETING RESEARCH DIRECTION

The sustainable development of internet marketing (later identified as IM) faces the dynamic environment and its alterations, which occurs in both - business terms and conditions, and in the use of electronic tools and applicable concepts. The growing importance of the IM is being indicated by the development of electronic markets, increasing number of new generation consumers, deepening interest of scientists from different scientific fields, as well as widening the related knowledge base. Despite the continuously increasing amount of scientific literature about marketing on the internet, this area of research is still in its initial stage. The aim of this article is to analyse fields of ongoing IM researches and to identify areas for deeper examination. The following methods were used: the comparative analysis and summary of the scientific literature, information comparing, grouping and graphic information visualization techniques. Keywords: internet marketing, internet marketing environment, communication, internet marketing research areas. DOI: 10.15276/mdt.2.1.2018.1 Powers T, Advincula D, Austin MS, Graiko S. 2013. Digital and Social Media in the Purchase-Decision Process: A Special Report from the Advertising Research Foundation. J. Advert. Res. 52:479. Sharma A, Sheth JN. 2004. Web-based marketing. J. Bus. Res. 57:696–702. Taylor DG, Strutton D. 2010. Has e-marketing come of age? Modeling historical influences on post-adoption era Internet consumer behaviors. J. Bus. Res. 63:950–956. Tiago MT, Tiago F. 2012. Revisiting the Impact of Integrated Internet Marketing on Firms’ Online Performance: European Evidences. Procedia Technol. 5:418–426. Crocker D. 2006. Email history. The living Internet. [cited 14 October 2015]. Available from http://debian.fmi.uni-sofia.bg/~group1_2008/english/email_history.doc. Kiang MY, Raghu T., Shang KH-M. 2000. Marketing on the Internet — who can benefit from an online marketing approach? Decis. Support Syst. 27:383–393. Kiang MY, Raghu TS, Shang KH-M. 2000. Marketing on the Internet — who can benefit from an online marketing approach? Decis. Support Syst. 27:383–393. Ngai EWT. 2003. Internet marketing research (1987-2000): a literature review and classification. Eur. J. Mark. 37:24–49. Schibrowsky JA, Peltier JW, Nill A. 2007. The state of internet marketing research: A review of the literature and future research directions. Eur. J. Mark. 41:722–733. Davidavicienė V, Sabaitytė J. 2014. Tyrimų internetinės rinkodaros srityje analizė. Verslas Teor. ir Prakt. [cited 8 December 2015]. Available from http://www.ceeol.com/aspx/getdocument. aspx?logid=5&id=e7cf2f13e070430ca0810cab1a6e97a5. Kwan ISY, Fong J, Wong HK. 2005. An e-customer behavior model with online analytical mining for internet marketing planning. Decis. Support Syst. 41:189–204.

A narrative approach to interactive information visualization in the digital humanities classroom

Humanities researchers have expressed concern about the uncritical adoption of information visualization techniques originating in the sciences by digital humanities classrooms. This paper describe...

Visualization of Online Datasets

As computing technology advances, computers are being used to orchestrate and advance wide spectrums of commercial and personal life, information visualization becomes even more significant as we immerse ourselves into the era of big data, leading to an economy heavily reliant on data mining and precise, meaningful visualizations. However, accuracy of information visualization techniques is heavily dependent on the knowledge and capabilities of users, leaving novices in many fields at a disadvantage. This is a challenging problem that has been inadequately addressed regardless of the influx in visualization tools. Therefore, this paper proposes a novel approach with a focus on online datasets, allowing users to automatically and accurately visualize datasets. Experiment results show that using a browser extension and specially created HTML tables containing custom attributes - stating the data attribute type - the approach is able to detect and present the most suitable visualizations at the click of a mouse. This proposed approach provides a means for novices to quickly and accurately visualize online datasets.

Application of Hierarchical Visualization Techniques in Meta-Analysis Data

The meta-analysis is a probabilistic technique that groups the results of several studies, approaches the same subject and produces a result that summarizes the whole. The results that are displayed in graphical form neither offer interactivity with the user, nor a user-friendly interface and easy comprehension. In order to obtain a visual exploratory analysis with more satisfactory results, there are information visualization techniques applied to map the data in graphical form to broaden the user cognition. This article performs the execution of the meta-analysis, through R software, in order to determine the efficiency of fungicide fluquinconazole when combating Asian soy rust and applies the Technique for the Visualization of Hierarchical Information Structure; the Bifocal Tree, to improve the results displayed by the R through the forest plot graphic.

A Framework for Visual Representation of Crime Information

Objectives: This paper proposes a framework that transforms the structural crime related data into effective visual reports to strengthen the pro-active activities of law enforcement agencies. Methods/Statistical Analysis: The information visualization depends on the input data. The visualization engine, as proposed in this research work, processes all the data to produce crime information instrumental for the law-enforcing agencies and present it in three different formats: 1) Statistically summarized reports in graphical formats, 2) Heat-maps of crimes and 3) Clusters of crime patterns based on geo-locations. Findings: The visual crime analysis information may also help the policy-makers to gain depth knowledge about crime types, their timings at certain regions. This insight knowledge may improve the performance of law enforcement agencies in reducing crime rate and utilizing resources efficiently. Especially, it performs comprehensive processing of crime information to detecting heat-maps of crimes, clustering crime patterns and presenting it by means of information visualization techniques. Application/Improvements: Law enforcement agencies can use the system to have comprehensive, consolidated and chronologically view of all types of reported criminal activities. Keywords: Crime Information, Data Visualization, Heat Maps, Information Visualization

A Simulation and Visualization Environment for Spatiotemporal Disaster Risk Assessments of Network Infrastructures

Emerging methodologies for risk assessments of civil infrastructure networks require the coupling of several spatiotemporal models that need to be executed multiple times with varying parametrizations to account for model uncertainty and to investigate “what-if” scenarios. These requirements led to the development of a software environment to support the simulation process and the visual analysis of its results. The simulation engine component of the environment makes it possible to define, couple, and execute models. An embedded infrastructure model facilitates the development of functionality to estimate and aggregate capacity measures of single objects affected by multiple hazards. The simulation manager component can be used to execute multiple instances of the simulation engine conveniently with varying parametrizations. The included visualization tool provides two complementary views. The ensemble view can be used to analyze the data at a highly aggregated level with information visualization techniques and the simulation view can be used to investigate simulations in greater detail via an interactive map window and a state dependency graph. The software environment is used in a risk assessment for the region of Chur, Switzerland, which comprises the simulation of multiple natural hazard scenarios that lead to impaired transport infrastructure capacities and thus to disrupted traffic flows.

Developing 3D Spatial Information Analysis and Visualization Technique for Disaster Areas

이 연구는 시설물 붕괴사고와 같은 재난현장을 신속하게 모델링하여 3차원 공간정보 분석과 함께 붕괴지 하부에 매몰된 요구조자의 위치정보를 가시화하는데 목적이 있다. 붕괴사고가 발생하게 되면, 구조자가 현장 상황을 신속히 파악하여 골든타임 내에 인명을 구조하는 것이 매우 중요하다. 또한, 붕괴사고 현장은 추가 붕괴 우려로 인하여 구조자가 쉽게 접근할 수 없다는 점이 장애요인으로 작용한다. 따라서 이 연구에서는 붕괴사고 발생 시, 구조자가 신속하고 안전하게 구조활동을 수행할 수 있도록 다음과 같은 방법론을 제시하였다. 첫째, 붕괴지형 정보를 보다 손쉽게 취득하기 위하여 드론탑재형 스테레오 카메라 기반의 영상 취득 및 송신용 모듈을 개발하였다. 둘째, 취득된 영상을 바탕으로 공간정보 분석이 가능하도록 붕괴형상정보를 3차원으로 모델링하였다. 셋째, 매몰자의 위치정보를 3차원 모델상에 가시화하였다. 넷째, 현장테스트를 통하여 개발된 장비 및 시스템에 대하여 검증하였다. 본 연구 결과를 실제 재난현장에 적용할 경우, 구조자로 하여금 보다 신속하고 안전한 구조업무 지원을 할 수 있을 것으로 판단된다.

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer's disease neuroimaging initiative.

BackgroundAlzheimer’s disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years.MethodsCitation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time.ResultsDuring the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period.ConclusionsBoth statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD.