A visual analytics agenda

Thomas, Jim; Cook, Kristin A.

doi:10.1109/mcg.2006.5

Cited by 523 publications

(359 citation statements)

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“…Geographical information scientists are commissioned to develop methods that detect the expected and discover the unexpected from massive streams of disparate data, potentially originating from various sources [58]. Such methods need to be scalable, flexible and reliable.…”

Section: Discussionmentioning

confidence: 99%

Reporting Leaders and Followers among Trajectories of Moving Point Objects

et al. 2007

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Abstract. Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern 'one object is leading others', which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.

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Section: Discussionmentioning

confidence: 99%

Reporting Leaders and Followers among Trajectories of Moving Point Objects

et al. 2007

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“…Especially human factors (e.g., interaction, cognition, perception, collaboration, presentation, and dissemination) play a key role in the communication between human and computer, as well as in the decision-making process. In this context, production is defined as the creation of materials that summarize the results of an analytical effort, presentation as the packaging of those materials in a way that helps the audience understand the analytical results in context using terms that are meaningful to them, and dissemination as the process of sharing that information with the intended audience [4]. In matters of data analysis, visual analytics further- more profits from methodologies developed in the fields of data management & knowledge representation, knowledge discovery and statistical analytics.…”

Section: Scope Of Visual Analyticsmentioning

confidence: 99%

Visual Analytics: Scope and Challenges

Keim

Mansmann

Schneidewind

et al.

Lecture Notes in Computer Science

351

222

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Abstract. In today's applications data is produced at unprecedented rates. While the capacity to collect and store new data rapidly grows, the ability to analyze these data volumes increases at much lower rates. This gap leads to new challenges in the analysis process, since analysts, decision makers, engineers, or emergency response teams depend on information hidden in the data. The emerging field of visual analytics focuses on handling these massive, heterogenous, and dynamic volumes of information by integrating human judgement by means of visual representations and interaction techniques in the analysis process. Furthermore, it is the combination of related research areas including visualization, data mining, and statistics that turns visual analytics into a promising field of research. This paper aims at providing an overview of visual analytics, its scope and concepts, addresses the most important research challenges and presents use cases from a wide variety of application scenarios.

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“…In such models, visualization allows interactive analytic process, where humans and computers effectively cooperate using their respective distinct capabilities for data processing and visual recognition. The "visual analytics" filed itself has formally begun in 2005 by the publication of Illuminating the Path: The R&D Agenda for visual analytics [24]. R&D agenda defines visual analytics as "the science of analytical reasoning facilitated by interactive visual interfaces".…”

Section: Big Data Visual Analyticsmentioning

confidence: 99%

Analytics and Telehealth Emerging Technologies: The Path Forward for Smart Primary Care Environment

AbuKhousa¹

2017

J Healthc Commun

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The increasing global health expenditure positions primary care to use digital health technologies to manage chronic disease and deliver cost-effective personalized and preventive care. In this paper, we review the recent advancements in telehealth and big data technologies that have the potentials to move primary care services to smart environments. We adopt the smart environment concept to propose our conceptual model for a Smart Primary Care Environment (SPCE). We also identify challenges and key factors for a successful realization of the model in the future.

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A visual analytics agenda

Cited by 523 publications

References 0 publications

Reporting Leaders and Followers among Trajectories of Moving Point Objects

Reporting Leaders and Followers among Trajectories of Moving Point Objects

Visual Analytics: Scope and Challenges

Analytics and Telehealth Emerging Technologies: The Path Forward for Smart Primary Care Environment

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