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Beyond the horizon:immersive developments for animal ecology research

Visual Computing for Industry,Biomedicine,and Art 2023年第1期6卷 139-152页

作者： Ying Zhang Karsten Klein Falk Schreiber Kamran Safi Department of Computer and Information Science University of KonstanzKonstanz 78464Germany Department of Migration Max Planck Institute of Animal BehaviorRadolfzell 78315Germany Faculty of Information Technologies Monash UniversityMelbourneVIC 3145Australia

More diverse data on animal ecology are now ***“data deluge”presents challenges for both biologists and computer scientists;however,it also creates opportunities to improve analysis and answer more holistic research *** aim to increase awareness of the current opportunity for interdisciplinary research between animal ecology researchers and computer *** analytics(IA)is an emerging research field in which investigations are performed into how immersive technologies,such as large display walls and virtual reality and augmented reality devices,can be used to improve data analysis,outcomes,and *** investigations have the potential to reduce the analysis effort and widen the range of questions that can be *** propose that biologists and computer scientists combine their efforts to lay the foundation for IA in animal ecology *** discuss the potential and the challenges and outline a path toward a structured *** imagine that a joint effort would combine the strengths and expertise of both communities,leading to a well-defined research agenda and design space,practical guidelines,robust and reusable software frameworks,reduced analysis effort,and better comparability of results.

关键词： Immersive analytics Animal ecology Collaboration interactive data visualization

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User Experience for Non-Expert Audiences in data Exploration 23

User Experience for Non-Expert Audiences in Data Exploration

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11th International Conference on Communities and Technologies - Humanization of Digital Technologies (C and T)

作者： Tylosky, Natasha Knutas, Antti Qureshi, Majad Wolff, Annika Finland LUT Univ Lappeenranta Finland

ISBN: (纸本)9798400707582

data Exploration remains an untapped area of research, and as of yet few guidelines exist for how to design a data exploration tool. In this paper we conduct a qualitative study of a data exploration tool that has been created using a series of principles for designing data exploration systems for non-expert audiences. In the course of this study, we both evaluate the tool, dubbed the data Explorer, and refine the design principles that it was based on.

关键词： data Exploration Design Principles interactive data visualization Sensemaking User Experience

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Surmounting Obstacles for Academic Resilience: A Dynamic Portal for Supporting an Alliance of Students with Disabilities 17th

Surmounting Obstacles for Academic Resilience: A Dynamic Por...

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17th International Conference on Universal Access in Human-Computer Interaction (UAHCI) part of the 25th International Conference on Human-Computer Interaction (HCI)

作者： Petri, Alexis N. Ho, Duy H. Wang, Ye Lee, Yugyung Univ Missouri Kansas City Kansas City MO 64110 USA Auburn Univ NSF Eddie Bernice Johnson INCLUDES Initiat TAPDINTO S Auburn AL 36849 USA UMKC Sch Sci & Engn Kansas City MO USA UMKC Sch Humanities & Social Sci Kansas City MO USA

ISBN: (纸本)9783031358968;9783031358975

Description of the development and use of a dynamic portal for supporting an alliance of colleges and universities focused on supporting students with disabilities and transitioning to careers in science and technology. Called SOAR, the portal is designed to support separate institutes achieve collective impact through shared measures. Significant aspects of SOAR are the user-driven design with three different communication roles, dynamic generation of survey forms, the ability to schedule surveys, collecting data through the surveys, and data presentation through dynamic chart generation. SOAR utilizes and advances the best practices of Universal Access and is central to the alliance's ability to empower individuals with disabilities to live their best lives. One of the most interesting features is the ability for different institutes to customize their forms and collect campus-relevant data that can be changed and the application of machine learning to produce the dynamic chart generation. SOAR allows the alliance to meet individual campus needs and the reporting and evaluation needs of the National Science Foundation.

关键词： User-friendly Survey App Inclusive User Experience Tailored User Interface interactive data visualization

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Accessibility of a COVID-19 interactive display: An evaluation of the Johns Hopkins COVID-19 dashboard An evaluation of the Johns Hopkins COVID-19 dashboard 23

Accessibility of a COVID-19 interactive display: An evaluati...

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41st ACM International Conference on Design of Communication (SIGDOC)

作者： Deets, Stuart M. Univ Minnesota Twin Cities Dept Writing Studies Minneapolis MN 55455 USA

This paper highlights the importance of heuristic accessibility analysis by investigating the Johns Hopkins COVID-19 U.S. dashboard. It suggests possible future research directions for technical communicators to conti... 详细信息

ISBN: (纸本)9798400703362

关键词： COVID-19 interactive data visualization

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interactive Visual Self-service data Classification Approach to Democratize Machine Learning 24

Interactive Visual Self-service Data Classification Approach...

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24th International Conference Information Visualisation (IV)

作者： Wagle, Sridevi Narayana Kovalerchuk, Boris Cent Washington Univ Dept Comp Sci Ellensburg WA 98926 USA

ISBN: (纸本)9781728191348

Although machine learning algorithms are progressively used in an expansive range of domains, the effective machine learning classifiers are often black-boxed, non-comprehensive to the end users and beyond their abilities to develop models themselves. To overcome this challenge, data visualization combined with self-service or democratized machine learning is proposed in the form of the Iterative Logical Classifier (ILC) algorithm with an added advantage of outperforming the accuracies of black-box machine learning classifiers on benchmark datasets. The algorithm is based on the concept of Shifted Paired Coordinates that allow 2-D visualization of n-D data without loss of n-D information.

关键词： Self-service Machine Learning interactive data visualization Logical Classifier AutoML

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data Abstraction for Visual and Haptic Representations in Flow visualization 22

Data Abstraction for Visual and Haptic Representations in Fl...

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28th ACM Symposium on Virtual Reality Software and Technology (VRST)

作者： Bhardwaj, Ayush Kang, Sungjoo Kim, Jin Ryong Univ Texas Dallas Richardson TX 75083 USA ETRI AI Res Lab Daejeon South Korea

ISBN: (纸本)9781450398893

This paper presents a new way of data abstraction for visual and haptic representations in immersive analytics using a mid-air haptic display. Visual and haptic abstraction is proposed to transform raw data (wind tunnel data) into another form of data for effective visual and haptic data mapping. Three main features are extracted: (i) Magnitude of Velocity, (ii) Recirculation Region, and (iii) Vorticity. For each feature, visual and haptic abstractions are defined based on data characterization and data reduction. A preliminary study shows a promising direction toward multimodal data interaction in immersive analytics.

关键词： Immersive analytics haptic data abstraction data transformation interactive data visualization

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Quality of Supply data Mining

Quality of Supply Data Mining

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16th International Conference on Harmonics and Quality of Power (ICHQP)

作者： Stander, Tiaan Rens, Johan North West Univ Sch Elect & Elect Engn Potchefstroom Campus Potchefstroom South Africa

ISBN: (纸本)9781467364874

Extracting useful network management information from a large volume of QoS data obtained all over a network can be simplified by innovative data mining techniques. The need for QoS expertise is reduced as interactive visualization by brushing and linking of datasets reveals interrelation of parameters. data contextualization by annotated data can aid the assessment on the global level of compatibility between supply and use conditions. data dashboards can further simplify the analysis of QoS data by recognizing the network connectivity of different sites, seasonal effects and direction of voltage waveform events.

关键词： QoS PQ data mining SQL QoS reporting compliance to compatibility network risk management interactive data visualization contextualization data dashboards

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visualization as a mean of Big data Management: Using Qatar's Electricity Consumption data 9

Visualization as a mean of Big Data Management: Using Qatar'...

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9th IEEE-GCC Conference and Exhibition (GCCCE)

作者： Soliman, Engy Fetais, Noora Qatar Univ KINDI Ctr Comp Res 2713 Al Hala St Doha Qatar

ISBN: (纸本)9781538627563

visualization as a mean of big data management is the new century revolution. Managing data has become a great challenge today, as the amount of raw data size is increasing *** data like electricity consumption, a new data value is received every minute from different areas. This creates the well-known five challenges for any data analyst trying to deliver a visual representation of such huge raw data. Adding to that, a data analyst should understand the four dimensions of the given data;Volume, variety, velocity and veracity. The integration of big data and visualization is the key to addressing real market significant shift in enterprise technology. The aim of the paper is to give an insight of 'how to manage' Qatars electricity consumption from raw data provided by electricity companies. This can lead to a much better visualization solution as analysts and top-level managers can understand how to act towards their resources and plan.

关键词： Big data visualization Electricity Consumption interactive data visualization

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A Heterogeneous and interactive Big Earth data Framework 2019

A Heterogeneous and Interactive Big Earth Data Framework

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International Conference on Big data Engineering (BDE)

作者： Bi, Haixia Xue, Yong Merritt, Patrick Windmill, Chris Davis, Bradley Univ Derby Derby DE22 1GB England

ISBN: (纸本)9781450360913

The dramatic development of Earth observation techniques leads to an explosion of Earth data. However, the increase of the Earth data size and their heterogeneity bring significant challenges to the storage, processing and visualization of the big Earth data. To address the problems caused by the huge Earth data-sets, a heterogeneous and interactive big Earth data framework is proposed in this paper, integrating raster-vector data cloud storage, data processing based on workflow and machine learning techniques and real-time rendering and interactive visualization. The framework provides a theoretical reference for future implementations of the system.

关键词： Big Earth data heterogeneous data storage interactive data visualization workflow machine learning

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Clustering and visualization of a high-dimensional diabetes dataset 23rd

Clustering and visualization of a high-dimensional diabetes ...

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23rd KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES)

作者： Lasek, Piotr Mei, Zhen Univ Rzeszow Rzeszow Poland Manifold Data Min Inc Toronto ON Canada

data clustering algorithms have proved to be important and widely used methods of artificial intelligence and data mining for discovering unknown yet important patterns in datasets. Nevertheless, one of the additional aspects of data clustering is proper interpretation of the clustering results. In this paper we aim to investigate possibilities of using both data clustering and visualization methods to analyze a sample diabetes dataset. In the first part, we focus on how to cluster a highly-dimensional sample dataset and then, we concentrate on how to properly visually present the clustering results in the most meaningful way to uncover potentially interesting behavioral patterns or features of diabetes patients. In this work we examine two clustering algorithms (DBSCAN, k-Means) along with several different distance measures. We also present sample visualizations of clustering results generated by an application which we have developed and discuss if the proposed way of clustering results visualization can be helpful in understanding the analyzed dataset and lead a viewer to drawing valuable conclusions about it. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses)/by-nc-nd/4.0/) Peer-review under responsibility of KES International.

关键词： data mining data visualization interactive data visualization diabetes visualization clustering high-dimensional clustering

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