Abstract: Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.
Abstract: New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.
Abstract: The increasing availability of information about earth
surface elevation (Digital Elevation Models DEM) generated from
different sources (remote sensing, Aerial Images, Lidar) poses the
question about how to integrate and make available to the most than
possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the
quality of data management plays a fundamental role. Due to the high
acquisition costs and the huge amount of generated data, highresolution
terrain surveys tend to be small or medium sized and
available on limited portion of earth. Here comes the need to merge
large-scale height maps that typically are made available for free at
worldwide level, with very specific high resolute datasets. One the
other hand, the third dimension increases the user experience and the
data representation quality, unlocking new possibilities in data
analysis for civil protection, real estate, urban planning, environment
monitoring, etc. The open-source 3D virtual globes, which are
trending topics in Geovisual Analytics, aim at improving the
visualization of geographical data provided by standard web services
or with proprietary formats. Typically, 3D Virtual globes like do not
offer an open-source tool that allows the generation of a terrain
elevation data structure starting from heterogeneous-resolution terrain
datasets. This paper describes a technological solution aimed to set
up a so-called “Terrain Builder”. This tool is able to merge
heterogeneous-resolution datasets, and to provide a multi-resolution
worldwide terrain services fully compatible with CesiumJS and
therefore accessible via web using traditional browser without any
additional plug-in.
Abstract: The aim of this paper is to understand emerging
learning conditions, when a visual analytics is implemented and used
in K 12 (education). To date, little attention has been paid to the role
visual analytics (digital media and technology that highlight visual
data communication in order to support analytical tasks) can play in
education, and to the extent to which these tools can process
actionable data for young students. This study was conducted in three
public K 12 schools, in four social science classes with students aged
10 to 13 years, over a period of two to four weeks at each school.
Empirical data were generated using video observations and analyzed
with help of metaphors within Actor-network theory (ANT). The
learning conditions are found to be distinguished by broad
complexity, characterized by four dimensions. These emerge from
the actors’ deeply intertwined relations in the activities. The paper
argues in relation to the found dimensions that novel approaches to
teaching and learning could benefit students’ knowledge building as
they work with visual analytics, analyzing visualized data.
Abstract: Due to the widespread of mobile sensing, there is a strong need to handle trails of moving objects, and trajectories. This paper proposes three visual analytics approaches for higher order information of trajectory datasets based on the higher order Voronoi diagram data structure. Proposed approaches reveal geometrical, topological, and directional information. Experimental resultsdemonstrate the applicability and usefulness of proposed three approaches.
Abstract: The advances in location-based data collection
technologies such as GPS, RFID etc. and the rapid reduction of their
costs provide us with a huge and continuously increasing amount of
data about movement of vehicles, people and goods in an urban area.
This explosive growth of geospatially-referenced data has far
outpaced the planner-s ability to utilize and transform the data into
insightful information thus creating an adverse impact on the return
on the investment made to collect and manage this data. Addressing
this pressing need, we designed and developed DIVAD, a dynamic
and interactive visual analytics dashboard to allow city planners to
explore and analyze city-s transportation data to gain valuable
insights about city-s traffic flow and transportation requirements. We
demonstrate the potential of DIVAD through the use of interactive
choropleth and hexagon binning maps to explore and analyze large
taxi-transportation data of Singapore for different geographic and
time zones.