Abstract
With the advent of the era of big data, extract and display effective information from massive amount of data has become a hot research field. Visualization is the most direct way for users ...to perceive and understand data. That’s why data dashboard with its cool dynamic visual effect has become so popular. In this paper, we propose a framework for rapid construction and development of web-based large screen visual dashboard—Anov. Anov dedicates to three goals: high efficiency, innovative AI user interaction and 3D scene. First, this framework provides a “30% configuration, 70% customization” development scheme which shortens the development cycle by at least one third. Second, Anov adopts a hierarchical architecture model to achieve high reusability, easy extensibility, high reliability, and easy maintenance. Finally, this paper introduces Anov’s wide range of application field and rich user experience through multiple cases to demonstrate the practicality of the framework.
On Jan 22, 2020, a day after the USA reported its first COVID-19 case, the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) launched the first global real-time ...coronavirus surveillance system: the JHU CSSE COVID-19 Dashboard. As of June 1, 2022, the dashboard has served the global audience for more than 30 consecutive months, totalling over 226 billion feature layer requests and 3·6 billion page views. The highest daily record was set on March 29, 2020, with more than 4·6 billion requests and over 69 million views. This Personal View reveals the fundamental technical details of the entire data system underlying the dashboard, including data collection, data fusion logic, data curation and sharing, anomaly detection, data corrections, and the human resources required to support such an effort. The Personal View also covers the challenges, ranging from data visualisation to reporting standardisation. The details presented here help develop a framework for future, large-scale public health-related data collection and reporting.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Increasingly, higher education institutions are exploring the potential of learning analytics to predict student retention, understand learning behaviors, and improve student learning through ...providing personalized feedback and support. The technical development of learning analytics has outpaced consideration of ethical issues surrounding their use. Of particular concern is the absence of the student voice in decision-making about learning analytics. We explored higher education students' knowledge, attitudes, and concerns about big data and learning analytics through four focus groups (
= 41). Thematic analysis of the focus group transcripts identified six key themes. The first theme, "Uninformed and Uncertain," represents students' lack of knowledge about learning analytics prior to the focus groups. Following the provision of information, viewing of videos and discussion of learning analytics scenarios three further themes; "Help or Hindrance to Learning," "More than a Number," and "Impeding Independence"; represented students' perceptions of the likely impact of learning analytics on their learning. "Driving Inequality" and "Where Will it Stop?" represent ethical concerns raised by the students about the potential for inequity, bias and invasion of privacy and the need for informed consent. A key tension to emerge was how "personal" vs. "collective" purposes or principles can intersect with "uniform" vs. "autonomous" activity. The findings highlight the need the need to engage students in the decision making process about learning analytics.
Learning analytics dashboards (LADs) are intended to give relevant information to students and other stakeholders to inform potential next steps in the learning process. The current study examines ...the relationship between information indirectly presented through academic advisors' use of LADs, and college students' academic motivation, self-regulated learning, and academic achievement. We modeled how changes in student motivation and self-regulated learning (SRL) were related to what occurred during 1-on-1 meetings with academic advisors during which students had the potential to view representations of their achievement embedded within an Early Warning System (EWS) that visually represented aspects of their academic performance referenced with course averages. Constructs associated with SRL were moderated by advisor-advisee meetings. Results indicated that advisors' use of EWS while they met with students was negatively associated with the rate of decrease of students' reporting of using memorizing strategies but positively related when students' performance was compared to that of their peers. We discuss the moderating effects of students’ exposure to visualizations of academic performance on their SRL strategies and academic motivation. This study points to the importance of monitoring the effects of information presented via EWS on motivation and SRL.
•We investigated the relationship between exposure to a dashboard through advisors, and students' motivation and SRL.•Dashboards used by academic advisors is related to decreases in the rate of students' motivation and SRL strategies.•We discuss the importance of visualizations on students' motivation and self-regulated learning.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
35.
What Do We Talk About When We Talk About Dashboards? Sarikaya, Alper; Correll, Michael; Bartram, Lyn ...
IEEE transactions on visualization and computer graphics,
01/2019, Volume:
25, Issue:
1
Journal Article
Peer reviewed
Dashboards are one of the most common use cases for data visualization, and their design and contexts of use are considerably different from exploratory visualization tools. In this paper, we look at ...the broad scope of how dashboards are used in practice through an analysis of dashboard examples and documentation about their use. We systematically review the literature surrounding dashboard use, construct a design space for dashboards, and identify major dashboard types. We characterize dashboards by their design goals, levels of interaction, and the practices around them. Our framework and literature review suggest a number of fruitful research directions to better support dashboard design, implementation and use.
Life Cycle Assessment (LCA) is increasingly used for decision-making in the design process of buildings and neighbourhoods. Therefore, visualisation of LCA results to support interpretation and ...decision-making becomes more important. The number of building LCA tools and the published literature has increased substantially in recent years. Most of them include some type of visualisation. However, there are currently no clear guidelines and no harmonised way of presenting LCA results. In this paper, we review the current state of the art in visualising LCA results to provide a structured overview. Furthermore, we discuss recent and potential future developments. The review results show a great variety in visualisation options. By matching them with common LCA goals we provide a structured basis for future developments. Case studies combining different kinds of visualisations within the design environment, interactive dashboards, and immersive technologies, such as virtual reality, show a big potential for facilitating the interpretation of LCA results and collaborative design processes. The overview and recommendations presented in this paper provide a basis for future development of intuitive and design-integrated visualisation of LCA results to support decision-making.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper develops a methodology for the early detection of reactivation of tourist markets to help mitigate the effects of the COVID-19 crisis, using Skyscanner data on air passenger searches ...(>5,000 million) and picks (>600 million), for flights between November 2018 and December 2020, through ForwardKeys. For future travel during the May to September 2020 period, the desire to travel (based on the number of flight searches) has dropped by about 30% in Europe and the Americas, and by about 50% in Asia, while intention to travel (the number of flight picks, the final selections amongst flight searches) has dropped a further 10-20%. Most source markets remain optimistic about air travel during the last quarter of 2020, suggesting a U shape recovery. However, optimism has dwindled as time passes, suggesting a flatline L shape. A traffic light dashboard for domestic and inbound air travel demand to Spain shows how destination managers might use Big Data relating to the early recovery of key source markets to develop targeted marketing strategies. We show how Big Data provides timely granular data essential in highly volatile situations, and we argue that destination management organisations must improve their Big Data analytical and evidence-based, decision-making skills.
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BFBNIB, NUK, PILJ, SAZU, UL, UM, UPUK
The analysis of user interfaces using quantitative metrics is a straightforward way to quickly measure interface usability and other various design aspects (such as the suitability of page layout or ...selected colors). Development and evaluation of objective metrics corresponding with user perception, however, usually requires a sufficiently large training set of user interface samples. Finding real user interface samples might not be easy. Therefore, we rather use generated samples. In such case, we need to provide a realistic‐looking appearance of samples. This paper describes a workflow of the preparation of such samples. It presents a configurable generator based on the composition of simple widgets according to a predefined model. It also describes a reusable library for simple creation of widgets using capabilities of the JavaScript framework Vue.js. Finally, we demonstrate the applicability of the generator on a generation of dashboard samples which are used to evaluate existing metrics of interface aesthetics and show the possibility of their improvement.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
City dashboard websites are a common modality for bringing open-government philosophies into the public domain. Yet, there has been little research concerning the optimum design for city dashboards ...that takes account of users' expectations and skills. Indeed, there has been minimal exploration of user-centered design (UCD) to improve the usability and utility of smart city technologies in general. This study sought to conduct a user evaluation analysis to inform a UCD approach to city dashboards. Interviews with different types of users were conducted that applied a protocol analysis to gain insight into user perspectives and experiences of city dashboards. Along with critical incident technique procedures, interaction data of critical significance to the user was collected and a content analysis was conducted. These qualitative data were used to determine representations of users, as identified through observed behaviors, attitudes, needs, and goals. Targeted-scope user experience personas for the design process were then constructed to represent and build empathy towards three potential users of city dashboard systems: novices, end-users, and advanced users. The collected user requirements and the personas formulated are underpinning the re-design of an existing city dashboard.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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