Academic literature on the topic 'Collaborative Immersive Analytics'
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Journal articles on the topic "Collaborative Immersive Analytics"
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Chhikara, Vanshika. "IMMERSIVE ANALYTICS." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 10, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem33585.
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Immersive Analytics focuses on the benefits and challenges of using immersive environments for data analysis, and developing designs to improve efficiency. Although immersive technologies are widely available, practical solutions have not gained widespread acceptance in real- world applications. Research in this field focuses on abstract 3D visualization, immersive environments, paper sampling and use case evaluation. 03 Related Works • Brooks early review of VR applications found it effective in specific domains like flight simulators, automotive engineering, and astronaut training. • Van Dam et al. highlighted VR applications for SciVis, benefiting archaeology and medical fields. • Laha and Bowman reviewed VR techniques for visualizing volume data, highlighting the need for controlled experiments to explore individual components of immersion. • Reda et al. summarized research for hybrid reality environments like the CAVE2, emphasizing the possibility of collaborative data analysis. • Brath collected evidence that 3D visualizations offer advantages beyond 2D, focusing on immersive displays. 05 Result • Overall, immersive analytics can lead to better data comprehension, better decision-making, more engagement and teamwork, effective big data exploration, creative data visualization methods, non-technical users' empowerment, and applications in a variety of fields. • These results add to the increasing importance of immersive analytics as an efficient tool for decision support and data analysis. Introduction • To facilitate data-driven analytical reasoning, immersive analytics leverages interactive technology like as virtual reality glasses, big flat screen displays, and even the internet of things. • Immersion refers to an experience that creates a genuine sense of presence in a virtual environment. • A person experiences a shift in awareness from their immediate real environment to another reality. • Immersion analytics is still a relatively new field that has mostly been studied in use cases and workshops. • The notion remains extremely difficult, even within the small community of immersive analytics practitioners. Methodology 4.1 Immersive environments • The study focuses on immersive environments leading to a mixed reality experience. • Abstract 3D visualizations must be presented in a mixed or VR environment where hardware and user interact closely. 4.2 Abstract 3D visualizations • Data that lacks a physical representation or intrinsic spatial organization is referred to as abstract data. • In visualization, abstraction is obtained by using colors and shapes that are not directly associated with the object. 4.3 Paper sampling • Paper sampling in immersive analytics refers to the process of selecting and gathering relevant research papers and publications related to immersive analytics. Conclusion and future scope • In conclusion, immersive analytics has the potential to completely transform how we work with data by facilitating deeper understanding, better decision-making, and improved teamwork. • Immersion analytics will develop further and contribute significantly to data analysis and decision support in the future by tackling issues and seizing opportunities in technological innovation, domain-specific applications, ethical issues, and user experience design.
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Benk, Michaela, Raphael P. Weibel, Stefan Feuerriegel, and Andrea Ferrario. ""Is It My Turn?"." Proceedings of the ACM on Human-Computer Interaction 6, CSCW2 (November 7, 2022): 1–23. http://dx.doi.org/10.1145/3555580.
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Immersive analytics has the potential to promote collaboration in machine learning (ML). This is desired due to the specific characteristics of ML modeling in practice, namely the complexity of ML, the interdisciplinary approach in industry, and the need for ML interpretability. In this work, we introduce an augmented reality-based system for collaborative immersive analytics that is designed to support ML modeling in interdisciplinary teams. We conduct a user study to examine how collaboration unfolds when users with different professional backgrounds and levels of ML knowledge interact in solving different ML tasks. Specifically, we use the pair analytics methodology and performance assessments to assess collaboration and explore their interactions with each other and the system. Based on this, we provide qualitative and quantitative results on both teamwork and taskwork during collaboration. Our results show how our system elicits sustained collaboration as measured along six distinct dimensions. We finally make recommendations how immersive systems should be designed to elicit sustained collaboration in ML modeling.
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Chen, Lei, Hai-Ning Liang, Feiyu Lu, Jialin Wang, Wenjun Chen, and Yong Yue. "Effect of Collaboration Mode and Position Arrangement on Immersive Analytics Tasks in Virtual Reality: A Pilot Study." Applied Sciences 11, no. 21 (November 8, 2021): 10473. http://dx.doi.org/10.3390/app112110473.
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[Background] Virtual reality (VR) technology can provide unique immersive experiences for group users, and especially for analytics tasks with visual information in learning. Providing a shared control/view may improve the task performance and enhance the user experience during VR collaboration. [Objectives] Therefore, this research explores the effect of collaborative modes and user position arrangements on task performance, user engagement, and collaboration behaviors and patterns in a VR learning environment that supports immersive collaborative tasks. [Method] The study involved two collaborative modes (shared and non-shared view and control) and three position arrangements (side-by-side, corner-to-corner, and back-to-back). A user study was conducted with 30 participants divided into three groups (Single, Shared, and Non-Shared) using a VR application that allowed users to explore the structural and transformational properties of 3D geometric shapes. [Results] The results showed that the shared mode would lead to higher task performance than single users for learning analytics tasks in VR. Besides, the side-by-side position got a higher score and more favor for enhancing the collaborative experience. [Conclusion] The shared view would be more suitable for improving task performance in collaborative VR. In addition, the side-by-side position may provide a higher user experience when collaborating in learning VR. From these results, a set of guidelines for the design of collaborative visualizations for VR environments are distilled and presented at the end of the paper. All in all, although our experiment is based on a colocated setting with two users, the results are applicable to both colocated and distributed collaborative scenarios with two or more users.
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Fanini, Bruno, and Giorgio Gosti. "A New Generation of Collaborative Immersive Analytics on the Web: Open-Source Services to Capture, Process and Inspect Users’ Sessions in 3D Environments." Future Internet 16, no. 5 (April 25, 2024): 147. http://dx.doi.org/10.3390/fi16050147.
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Recording large amounts of users’ sessions performed through 3D applications may provide crucial insights into interaction patterns. Such data can be captured from interactive experiences in public exhibits, remote motion tracking equipment, immersive XR devices, lab installations or online web applications. Immersive analytics (IA) deals with the benefits and challenges of using immersive environments for data analysis and related design solutions to improve the quality and efficiency of the analysis process. Today, web technologies allow us to craft complex applications accessible through common browsers, and APIs like WebXR allow us to interact with and explore virtual 3D environments using immersive devices. These technologies can be used to access rich, immersive spaces but present new challenges related to performance, network bottlenecks and interface design. WebXR IA tools are still quite new in the literature: they present several challenges and leave quite unexplored the possibility of synchronous collaborative inspection. The opportunity to share the virtual space with remote analysts in fact improves sense-making tasks and offers new ways to discuss interaction patterns together, while inspecting captured records or data aggregates. Furthermore, with proper collaborative approaches, analysts are able to share machine learning (ML) pipelines and constructively discuss the outcomes and insights through tailored data visualization, directly inside immersive 3D spaces, using a web browser. Under the H2IOSC project, we present the first results of an open-source pipeline involving tools and services aimed at capturing, processing and inspecting interactive sessions collaboratively in WebXR with other analysts. The modular pipeline can be easily deployed in research infrastructures (RIs), remote dedicated hubs or local scenarios. The developed WebXR immersive analytics tool specifically offers advanced features for volumetric data inspection, query, annotation and discovery, alongside spatial interfaces. We assess the pipeline through users’ sessions captured during two remote public exhibits, by a WebXR application presenting generative AI content to visitors. We deployed the pipeline to assess the different services and to better understand how people interact with generative AI environments. The obtained results can be easily adopted for a multitude of case studies, interactive applications, remote equipment or online applications, to support or accelerate the detection of interaction patterns among remote analysts collaborating in the same 3D space.
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Wong, Jing-Ying, Chun-Chieh Yip, Su-Ting Yong, Andy Chan, Sien-Ti Kok, Teck-Leong Lau, Mohammed T. Ali, and Essameldin Gouda. "BIM-VR Framework for Building Information Modelling in Engineering Education." International Journal of Interactive Mobile Technologies (iJIM) 14, no. 06 (April 17, 2020): 15. http://dx.doi.org/10.3991/ijim.v14i06.13397.
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With the advancement of information technology, Building Information Modeling (BIM) is evolving fast and play an essential role in Architecture, Engineering, Construction, Owner and Operators (AECOO) industry. Universities play an important role in the current BIM transition in construction projects as well as to embrace Industry 4.0. In this research, immersive Virtual Reality (VR) in BIM offer a unique, supportive environment for the user experience in visualizing and collecting data from the model. With Virtual Reality (VR), engineering education has a major breakthrough. Immersive interactions, stereoscopic 3D, real time multisensory simulations, virtual explorations, synchronous communications, data analytics and visual analysis – all these are impossible without VR. VR offers a student-centred learning environment that promotes active and collaborative learning, situated within simulated real-world contexts.
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Rubart, Jessica, Valentin Grimm, and Jonas Potthast. "Augmenting Industrial Control Rooms with Multimodal Collaborative Interaction Techniques." Future Internet 14, no. 8 (July 26, 2022): 224. http://dx.doi.org/10.3390/fi14080224.
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The German manufacturing industry has been carrying out new developments towards the next industrial revolution, focusing on smart manufacturing environments. Our work emphasizes human-centered control rooms in the context of production plants. Increased automation does not have to come with less human control. Therefore, we report on multimodal collaborative interaction techniques to augment industrial control rooms. In particular, we include mobile workers who use the control room while being in the production hall using tablets or specifically mixed reality glasses. Collaborative annotation dashboards support discussions and a shared understanding among analysts. Manufacturing-related data can be integrated into business analytics environments so that holistic analyses can be performed. Multimodal interaction techniques can support effective interaction with the control room based on the users’ preferences. Immersive experience through mixed reality-based three-dimensional visualizations and interaction possibilities support users in obtaining a clear understanding of the underlying data.
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Vatanen, Anna, Heidi Spets, Maarit Siromaa, Mirka Rauniomaa, and Tiina Keisanen. "Experiences in Collecting 360° Video Data and Collaborating Remotely in Virtual Reality." QuiViRR: Qualitative Video Research Reports 3 (September 1, 2022): a0005. http://dx.doi.org/10.54337/ojs.quivirr.v3.2022.a0005.
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This paper reports on a pilot project called Remote Research and Collaboration Using VR and 360° Video (RReCo) that was carried out in late Spring 2021 at the University of Oulu, Finland. The project explored new ways of collecting, viewing and analysing video data for the purposes of engaging in remote, collaborative research on social interaction and activity. Here we share our experiences in collecting different types of video data, especially 360°, and relate those to our user experiences in analysing the data together in virtual reality. Our remote multisite data sessions were organised using software for immersive qualitative analytics, virtual reality and live streaming. In this paper, we also reflect on the similarities and differences between our data sets, especially with view to how awareness of different technical setups may help in making informed choices, and thereby increase the reliability of research on social interaction.
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Aparicio-Gómez, Oscar-Yecid, Olga-Lucia Ostos-Ortiz, and Constanza Abadía-García. "Convergence between emerging technologies and active methodologies in the university." Journal of Technology and Science Education 14, no. 1 (January 30, 2024): 31. http://dx.doi.org/10.3926/jotse.2508.
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In today's educational environment, the convergence of emerging technologies and active methodologies has become a fundamental driver of change in university education. Emerging technologies, such as artificial intelligence, virtual reality, machine learning, and data analytics, are redefining the dynamics of higher education. Active methodologies, such as problem-based learning, collaborative learning, and flipped learning, center the pedagogical focus on the student, encouraging active participation and problem-solving. The combination of emerging technologies and active methodologies creates a powerful synergy, enabling the effective implementation of personalized and immersive learning experiences. This convergence not only enhances learning, but also prepares students to be autonomous learners, critical thinkers, and 21st century problem solvers.
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Gowher Hassan. "TECHNOLOGY AND THE TRANSFORMATION OF EDUCATIONAL PRACTICES: A FUTURE PERSPECTIVE." International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) 3, no. 1 (February 27, 2023): 1596–603. http://dx.doi.org/10.54443/ijebas.v3i1.1136.
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Educational technology is undergoing a transformative evolution, bringing forth a convergence of digital tools, platforms, and methodologies to augment the learning journey. The proliferation of Learning Management Systems (LMS) and collaborative tools has ushered in an era of online learning, amplified by global shifts like the COVID-19 pandemic. These virtual platforms are redefining the boundaries of teaching, enabling a connection beyond physical spaces. Simultaneously, advancements in artificial intelligence and data analytics are reshaping personalized learning by discerning individual learner needs and facilitating real-time feedback. This evolving landscape is further enriched by emergent technologies like Artificial Intelligence (AI), Virtual Reality (VR), and Augmented Reality (AR). These innovations offer immersive, tailored experiences, reimagining traditional pedagogies. AI tailors education to individual needs, VR offers experiential realms previously unattainable, and AR provides an enriched overlay of information on the real world, revolutionising engagement. However, with these strides comes a responsibility to address underlying challenges: ensuring privacy, bridging the digital divide, and addressing potential biases in educational algorithms. The focus on accessibility and inclusivity is paramount, and technology plays a pivotal role in democratizing access to quality education. This synthesis underscores the imperative of interweaving technological advancements with core educational values, ensuring that the integration is both meaningful and equitable.
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Patricia, Kulemeka, and Chatola Fanny. "Climate change visualization awareness system." i-manager's Journal on Computer Science 11, no. 4 (2024): 21. http://dx.doi.org/10.26634/jcom.11.4.20653.
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As the global community faces the escalating challenges posed by climate change, there is an increasing need for innovative tools that enhance public awareness and understanding of the complex and dynamic nature of environmental shifts. This paper introduces a Climate Change Visualization Awareness System (CCVAS), designed to bridge the gap between scientific data and public comprehension through immersive and accessible visualizations. Leveraging cutting-edge technologies, including augmented reality, interactive mapping, and data analytics, CCVAS provides users with real-time and historical insights into key climate indicators such as temperature variations, sea level rise, and extreme weather events. The CCVAS employs a user-centric approach, tailoring information to diverse audiences and promoting engagement through intuitive interfaces. Community engagement features facilitate collaborative efforts among users, enabling the sharing of experiences, knowledge, and initiatives aimed at addressing climate change challenges at the local and global levels. Users will be able to participate in discussions, organize events, and access community-driven resources within the CCVAS platform. Personalized user profiles enable individuals to customize their climate change experience within CCVAS, tailoring content and visualizations to their specific interests, expertise, and geographical locations. By providing personalized recommendations, alerts, and action plans based on user preferences and behavior, CCVAS will empower individuals to take meaningful steps towards climate resilience and sustainability in their daily lives. This paper outlines the architecture, functionality, and potential applications of the Climate Change Visualization Awareness System.
Dissertations / Theses on the topic "Collaborative Immersive Analytics"
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Chen, Xin. "Be the Data: Embodied Visual Analytics." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/72287.
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With the rise of big data, it is becoming increasingly important to educate students about data
analytics. In particular, students without a strong mathematical background usually have an unenthusiastic attitude towards high-dimensional data and find it challenging to understand relevant complex analytical methods, such as dimension reduction. In this thesis, we present an embodied approach for visual analytics designed to teach students exploring alternative 2D projections of high dimensional data points using weighted multidimensional scaling. We proposed a novel application, Be the Data, to explore the possibilities of using human's embodied resources to learn from high dimensional data. In our system, each student embodies a data point and the position of students in a physical space represents a 2D projection of the high-dimensional data. Students physically moves in a room with respect to others to interact with alternative projections
and receive visual feedback. We conducted educational workshops with students inexperienced in
relevant data analytical methods. Our findings indicate that the students were able to learn about
high-dimensional data and data analysis process despite their low level of knowledge about the
complex analytical methods. We also applied the same techniques into social meetings to explain social gatherings and facilitate interactions.Master of Science
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Sereno, Mickaël. "Collaborative Data Exploration and Discussion Supported by Augmented Reality." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG106.
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J'étudie les avantages et limitations des casques de réalité augmentée (RA) pour l'exploration collaborative de données 3D. Avant d’entamer mes travaux, je voyais dans ces casques des avantages liés à leurs capacités immersives : ils fusionnent les espaces interactifs, de visualisation, de collaboration et physique des utilisateurs. Plusieurs collaborateurs peuvent voir et interagir directement avec des visuels 3D ancrés dans le monde réel. Ces casques reposent sur une vision stéréoscopique 3D qui fournit une perception de profondeur accrue par rapport aux écrans 2D, aidant les utilisateurs à mieux comprendre leurs données 3D. Laissant les utilisateurs se voir les uns les autres, il est possible de transitionner sans effort d’une phase de discussion à une phase d'exploration. Ces casques permettant aux utilisateurs d’interagir au sein de l’espace de travail de manière directe, rapide et intuitive en 3D, donnent des indices sur les intentions d'une personne aux autres. Par exemple, le fait de déplacer un objet en le saisissant est un indice fort sur les intentions de cette personne. Enfin, en n'occultant pas le monde réel, les outils habituels mais importants tels que les postes de travail restent facilement accessibles dans cet environnement. Cela étant, et bien qu’ils soient étudiés depuis des décennies, la puissance de calcul de ces casques avant la récente sortie de l'HoloLens en 2016 n'était pas suffisante pour une exploration efficace de données 3D telles que des données océaniques. De plus, les chercheurs précédemment étaient plus intéressés par comment rendre la RA possible que par comment utiliser la RA. Malgré toutes leurs qualités, il y a donc peu de travaux qui traitent de l'exploration de jeux de données 3D. Finalement, les casques de RA ne fournissent pas d'entrées 2D qui sont couramment utilisées avec les outils d'exploration actuels tels que ParaView et les logiciels de CAO, avec lesquels entre autre scientifiques et ingénieurs sont déjà efficaces. Je théorise donc dans cette thèse les situations où ces casques sont préférables. Ils semblent préférables lorsque l'objectif est de partager des idées, d'explorer des modèles ensemble et lorsque les outils d'exploration peuvent être minimaux par rapport à ce que les postes de travail fournissent, et ou la plupart des travaux et simulations préalables peuvent être effectués à l'avance. J'associe alors les casques de RA à des tablettes tactiles. J'utilise ces casques pour fusionner la visualisation, certaines interactions 3D et les espaces de collaboration dans l'espace physique des utilisateurs, et les tablettes pour la saisie 2D et l'interface utilisateur graphique habituelle que la plupart des logiciels proposent.J’étudie ensuite l'interaction de bas niveau nécessaire à l'exploration de données. Cela concerne la sélection de points et de régions dans des données 3D à l'aide de ce système hybride. Comme cette thèse vise à étudier les casques de RA dans des environnements collaboratifs, j’étudie également leurs capacités à adapter le visuel à chaque collaborateur pour un objet 3D ancré donné, similairement au "What-You-See-Is-What-I-See" relaxé qui permet par exemple à plusieurs utilisateurs de voir et modifier simultanément différentes parties d'un document partagé. Enfin, j’étudie en ce moment l'utilisation de mon système pour l'exploration collaborative en 3D des jeux de données océaniques sur lesquels travaillent mes collaborateurs du Helmholtz-Zentrum Geesthacht en Allemagne. Pour résumer, cette thèse fournit un état de l'art de la RA à des fins collaboratifs, fournit un aperçu de l'impact de la directivité de l'interaction 3D sur l'exploration de donnée 3D, et donne aux concepteurs un aperçu de l'utilisation de la RA pour l'exploration collaborative de données scientifique 2D et 3D, en mettant l'accent sur le domaine océanographiqueI studied the benefits and limitations of Augmented Reality (AR) Head-Mounted Displays (AR-HMDs) for collaborative 3D data exploration. Prior of conducting any projects, I saw in AR-HMDs benefits concerning their immersive features: AR-HMDs merge the interactive, visualization, collaborative, and users' physical spaces together. Multiple collaborators can then see and interact directly with 3D visuals anchored within the users' physical space. AR-HMDs usually rely on stereoscopic 3D displays which provide additional depth cues compared to 2D screens, supporting users at understanding 3D datasets better. As AR-HMDs allow users to see each other within the workspace, seamless switches between discussion and exploration phases are possible. Interacting within those visualizations allow for fast and intuitive 3D direct interactions, which yields cues about one's intentions to others, e.g., moving an object by grabbing it is a strong cue about what a person intends to do with that object. Those cues are important for everyone to understand what is currently going on. Finally, by not occluding the users' physical space, usual but important tools such as billboards and workstations performing simulations are still easily accessible within this environment without wearing off the headsets. That being said, and while AR-HMDs are being studied for decades, their computing power before the recent release of the HoloLens in 2016 was not enough for an efficient exploration of 3D data such as ocean datasets. Moreover, previous researchers were more interested in how to make AR possible as opposed to how to use AR. Then, despite all those qualities one may think prior of working with AR-HMDs, there were almost no work that discusses the exploration of such 3D datasets. Moreover AR-HMDs are not suitable for 2D input which are however commonly used with usual explorative tools such as ParaView or CAD software, where users such as scientists and engineers are already efficient with. I then theorize in what situations are AR-HMDs preferable. They seem preferable when the purpose is to share insights with multiple collaborators and to explore patterns together, and where explorative tools can be minimal compared to what workstations provide as most of the prior work and simulations can be done before hand. I am thus combining AR-HMDs with multi-touch tablets, where I use AR-HMDs to merge the visualizations, some 3D interactions, and the collaborative spaces within the users' physical space, and I use the tablets for 2D input and usual Graphical User Interfaces that most software provides (e.g., buttons and menus). I then studied low-level interactions necessary for data exploration which concern the selection of points and regions inside datasets using this new hybrid system. The techniques my co-authors and I have chosen possess different level of directness that we investigated. As this PhD aims at studying AR-HMDs within collaborative environments, I also studied their capacities to adapt the visual to each collaborator for a given anchored 3D object. This is similar to the relaxed "What-You-See-Is-What-I-See" that allows, e.g., multiple users to see different parts of a shared document that remote users can edit simultaneously. Finally, I am currently (i.e., is not finished by the time I am writing this PhD) studying the use of this new system for the collaborative 3D data exploration of ocean datasets that my collaborators at Helmholtz-Zentrum Geesthacht, Germany, are working on. This PhD provides a state of the art of AR used within collaborative environments. It also gives insights about the impacts of 3D interaction directness for 3D data exploration. This PhD finally gives designers insights about the use of AR for collaborative scientific data exploration, with a focus on oceanography
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(6861467), Hui Tang. "ShapeUD: A Real-time, Modifiable, Tangible Interactive Tabletop System for Collaborative Urban Design." Thesis, 2019.
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This research was to develop a real-time, modifiable, tangible interactive tabletop system for participatory urban design. The targeting user group was those stakeholders in urban design charrettes. Previous system solutions overlooked the importance of the modifiable tangible medium in the situation of reaching spatial-temporal consensus. These design issues impeded communication between the stakeholders and the professionals. Users of these systems had difficulties expressing ideas to professionals during the collaborative design process. Literature in evolving technology in the smart city context, collaborative urban design, embodied interaction, and depth-sensing was referred to guide the system design. Based on the review, this research identified the pivotal role of a shapeable and tangible medium in the system. The prototype system unified the modifiable, realistic model with its digital equivalent in urban analytics in real-time. By integrating tangible interaction, depth-sensing, and large touch screen tabletop, an intuitive, immersive decision-making interface for non-professional stakeholders could be created. During the system implementation, system elements centering ‘tangible interoperability’ were documented along the system pipeline. A heuristic evaluation, a method of usability inspection, was conducted to assess and to guide the future system design. The result was promising and inspiring. In the end, challenges and directions of system design were discussed. The contribution of this research included: discovering direction, centering tangibility, implementing a prototype, and documenting elements in each stage along the system pipeline of designing a modifiable tangible interactive tabletop system for the urban design charrette.
Book chapters on the topic "Collaborative Immersive Analytics"
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Billinghurst, Mark, Maxime Cordeil, Anastasia Bezerianos, and Todd Margolis. "Collaborative Immersive Analytics." In Immersive Analytics, 221–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01388-2_8.
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Garrido, Daniel, João Jacob, and Daniel Castro Silva. "Building a Prototype for Easy to Use Collaborative Immersive Analytics." In Computational Science – ICCS 2021, 628–41. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77961-0_50.
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Nakamura, Shohei, and Yoshihiro Okada. "Co-browsing Cubic Gantt Charts with VR Goggles for Collaborative Immersive Visual Data Analytics." In Complex, Intelligent and Software Intensive Systems, 384–94. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35734-3_39.
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Klamma, Ralf, Rizwan Ali, and István Koren. "Immersive Community Analytics for Wearable Enhanced Learning." In Learning and Collaboration Technologies. Ubiquitous and Virtual Environments for Learning and Collaboration, 162–74. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21817-1_13.
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Khalid, Md Saifullah. "Sustainable Tourism's Tomorrow." In Achieving Sustainable Transformation in Tourism and Hospitality Sectors, 139–55. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3390-7.ch008.
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This chapter explores the symbiotic relationship between technology innovation and sustainable tourism. It elucidates the indispensable roles of data analytics, artificial intelligence, and information technology, showcasing their applications in IoT and smart destination technologies. Furthermore, it examines the transparency benefits of blockchain, and the immersive experiences offered by AR, VR, and big data predictive analytics. Ethical considerations are thoroughly examined, emphasizing the importance of responsible innovation. Forecasts predict that big data analytics, digital solutions, and smart technology will profoundly influence the future of tourism. Recommendations are provided for stakeholders to prioritize sustainability, address privacy concerns, bridge the digital divide, and invest in green technologies. Collaboration among stakeholders is underscored as essential for the industry's responsible evolution, advocating for an integrated approach that combines technology with traditional sustainable practices.
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Del Moral Pérez, M. Esther, Nerea López-Bouzas, and Jonathan Castañeda Fernández. "Activating Teacher Competencies Through Designing Gamified Stories With Augmentative Reality." In Handbook of Research on Establishing Digital Competencies in the Pursuit of Online Learning, 230–52. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-7010-7.ch012.
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The GANA-AR project activates the competencies of future infant and primary school teachers through the design of gamified stories with augmented reality. It is an interactive digital environment with an educational aim which encourages learning through immersion and emotional engagement in a plot and the incorporation of game mechanics, dynamics, and aesthetics. The study was empirical, non-probabilistic (N=62), descriptive, and inferential. It was exploratory and analytical, with the objective of assessing university students' didactic, digital, creative, and socio-collaborative skills, and their abilities in gamification. The study found moderate-to-high levels of competence, with the highest levels in didactic competence, followed by digital. In addition, the students' gamified resources indicated high creative skills. This project allowed students to develop their teaching competencies through collaboratively creating gamified, digitally augmented resources to a high level of artistic and aesthetic quality.
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Thompson, Kate, and Lina Markauskaite. "Identifying Group Processes and Affect in Learners." In Cases on the Assessment of Scenario and Game-Based Virtual Worlds in Higher Education, 175–210. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4470-0.ch006.
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In the last five years, the analytical techniques for identifying the processes of online learning have developed to the point where applications for the assessment of learning can be discussed. This would be most appropriate for twenty-first century skills—such as collaboration, decision-making, and teamwork skills—which are the core learning outcomes in immersive learning environments. The state of the art in this field is still at the stage of discovering patterns of the processes of learning, identifying stages, and suggesting their meaning. However, already it is important to consider what technologies can offer and what information teachers need in order to evaluate students' situated performance and to provide useful feedback. This chapter describes an imagined virtual world, one that affords the range of twenty-first century skills, in order to illustrate types of analyes that could be conducted on learning process data. Such analytical methods could provide both descriptive information about the performance of learners and depict structures and patterns of their learning processes. The future assessment of learning in immersive virtual worlds may draw on data about deep embodied processes and multiple senses that usually underpin professional skills, such as affect, visual perception, and movement. This type of assessment could also provide deeper insights into many psychological processes in collaborative learning, decision-making, and problem-solving in virtual worlds, such as motivation, self-efficacy, and engagement. Overall, the view of the assessment presented in this chapter extends beyond the formal learning outcomes that are usually required by tertiary education quality and standards agencies and assessed in traditional courses in higher education to include a range of new capacities that may not be required but are essential for successful performance in contemporary workplaces.
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Thompson, Kate, and Lina Markauskaite. "Identifying Group Processes and Affect in Learners." In Gamification, 1479–505. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8200-9.ch075.
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In the last five years, the analytical techniques for identifying the processes of online learning have developed to the point where applications for the assessment of learning can be discussed. This would be most appropriate for twenty-first century skills—such as collaboration, decision-making, and teamwork skills—which are the core learning outcomes in immersive learning environments. The state of the art in this field is still at the stage of discovering patterns of the processes of learning, identifying stages, and suggesting their meaning. However, already it is important to consider what technologies can offer and what information teachers need in order to evaluate students' situated performance and to provide useful feedback. This chapter describes an imagined virtual world, one that affords the range of twenty-first century skills, in order to illustrate types of analyes that could be conducted on learning process data. Such analytical methods could provide both descriptive information about the performance of learners and depict structures and patterns of their learning processes. The future assessment of learning in immersive virtual worlds may draw on data about deep embodied processes and multiple senses that usually underpin professional skills, such as affect, visual perception, and movement. This type of assessment could also provide deeper insights into many psychological processes in collaborative learning, decision-making, and problem-solving in virtual worlds, such as motivation, self-efficacy, and engagement. Overall, the view of the assessment presented in this chapter extends beyond the formal learning outcomes that are usually required by tertiary education quality and standards agencies and assessed in traditional courses in higher education to include a range of new capacities that may not be required but are essential for successful performance in contemporary workplaces.
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Ellis, Maureen, and Patricia Anderson. "Teaching and Learning Through Interdisciplinary Pedagogies in a Second Life Environment." In Handbook of Research on Program Development and Assessment Methodologies in K-20 Education, 275–303. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3132-6.ch013.
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While virtual worlds have been available since the 1970s, opportunities for teaching and learning leading to improved pedagogical practice have increased over the past three decades (Livingstone, Kemp, & Edgar, 2008). Second Life, a highly immersive and scalable three-dimensional (3-D) multi-user social virtual environment, emphasizes the use of rich and authentic worlds for supporting an array of human activities and interactions within Web 2.0. Through synchronous communication, collaboration, and simulated experiences (Skiba, 2009), students accept the role of active creators of knowledge when faculty members adopt the Second Life platform as a learning environment. Bandura's social learning theory, Vygotsky's social development theory, and Piaget's constructivist learning theory form the conceptual framework for this chapter. This chapter describes how faculty from different disciplines in higher education adopted the interdisciplinary approach to course design, development, and delivery of a Second Life course with emphasis on authentic evaluation and assessment to improve student learning outcomes. The Second Life platform offered unique opportunities for students to become fully engaged in learning outcomes within two different courses. With learning outcomes and pedagogical needs at the forefront of instructional design decisions, instructors identified strategies for teaching, assessing, and evaluating the collaborative, immersive opportunities within Second Life as they taught two separate courses to the same group of students. This interdisciplinary approach to teaching entailed the use and integration of methods and analytical frameworks from more than one academic discipline to examine a theme, issue, question, or topic (Newell, 1994, 2001). Following both a constructivist approach and an integrated teaching model, instructors from two disciplines collaborated in the learning process with the goal of fostering inter-professional interactions. Interdisciplinary education was based on mutual understanding and respect for the concrete and unique opportunities for new contributions of each discipline.
Conference papers on the topic "Collaborative Immersive Analytics"
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Geymayer, Thomas, and Dieter Schmalstieg. "Collaborative distributed cognition using a seamless desktop infrastructure." In 2016 Workshop on Immersive Analytics (IA). IEEE, 2016. http://dx.doi.org/10.1109/immersive.2016.7932375.
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Hackathorn, Richard, and Todd Margolis. "Immersive analytics: Building virtual data worlds for collaborative decision support." In 2016 Workshop on Immersive Analytics (IA). IEEE, 2016. http://dx.doi.org/10.1109/immersive.2016.7932382.
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Nguyen, Huyen, Peter Marendy, and Ulrich Engelke. "Collaborative Framework Design for Immersive Analytics." In 2016 Big Data Visual Analytics (BDVA). IEEE, 2016. http://dx.doi.org/10.1109/bdva.2016.7787044.
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Lee, Benjamin, Maxime Cordeil, Arnaud Prouzeau, and Tim Dwyer. "FIESTA: A Free Roaming Collaborative Immersive Analytics System." In ISS '19: Interactive Surfaces and Spaces. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3343055.3360746.
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Zagermann, Johannes, Sebastian Hubenschmid, Daniel Immanuel Fink, Jonathan Wieland, Harald Reiterer, and Tiare Feuchtner. "Challenges and Opportunities for Collaborative Immersive Analytics with Hybrid User Interfaces." In 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). IEEE, 2023. http://dx.doi.org/10.1109/ismar-adjunct60411.2023.00044.
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Lock, John G., Daniel Filonik, Robert Lawther, Nalini Pather, Katharina Gaus, Sarah Kenderdine, and Tomasz Bednarz. "Visual analytics of single cell microscopy data using a collaborative immersive environment." In VRCAI '18: International Conference on Virtual Reality Continuum and its Applications in Industry. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3284398.3284412.
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Reski, Nico, Aris Alissandrakis, Jukka Tyrkkö, and Andreas Kerren. "“Oh, that’s where you are!” – Towards a Hybrid Asymmetric Collaborative Immersive Analytics System." In NordiCHI '20: Shaping Experiences, Shaping Society. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3419249.3420102.
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Kim, Duck Bong, Mahdi Sadeqi Bajestani, Guodong Shao, Albert Jones, and Sang Do Noh. "Conceptual Architecture of Digital Twin With Human-in-the-Loop-Based Smart Manufacturing." In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-112791.
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Abstract This paper proposes a conceptual architecture of digital twin with human-in-the-loop-based smart manufacturing (DH-SM). Our proposed architecture integrates cyber-physical systems with human spaces, where artificial intelligence and human cognition are employed jointly to make informed decisions. This will enable real-time, collaborative decision-making between humans, software, and machines. For example, when evaluating a new product design, information about the product’s physical features, manufacturing requirements, and customer demands must be processed concurrently. Moreover, the DH-SM architecture enables the creation of an immersive environment that allows customers to be effectively involved in the manufacturing process. The DH-SM architecture is well fitted to those relatively new manufacturing processes, such as metal additive manufacturing, since they can benefit from using digital twins, data analytics, and artificial intelligence for monitoring and controlling those processes to support non-contact manufacturing. The proposed DH-SM will enable manufacturers to leverage the existing cyber-physical system and extended reality technologies to generate immersive experiences for end users, operators, managers, and stakeholders. A use case of wire + arc additive manufacturing is discussed to demonstrate the applicability of the proposed architecture. Relevant development and implementation challenges are also discussed.
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Borhani, Zahra. "[DC] Annotation in Asynchronous Collaborative Immersive Analytic Environments using Augmented Reality." In 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, 2022. http://dx.doi.org/10.1109/vrw55335.2022.00326.
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Seraji, Mohammad Rajabi, and Wolfgang Stuerzlinger. "XVCollab: An Immersive Analytics Tool for Asymmetric Collaboration across the Virtuality Spectrum." In 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). IEEE, 2022. http://dx.doi.org/10.1109/ismar-adjunct57072.2022.00035.
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