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Information Visualization
Published in Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane, Big Data and Social Science, 2020
M. Adil Yalcın, Catherine Plaisant
Given the wide variety of goals, tasks, and use cases of visualization, many different data visualization tools have been developed that address different needs and appeal to different skill levels. In this chapter, we can only point to a few examples to get started. To generate a wide range of visualizations and dashboards, and to quickly share them online, Tableau and Tableau Public provide a flexible visualization design platform. If a custom design is required and programmers are available, d3 is the de facto low-level library of choice for many web-based visualizations, with its native integration to web standards and flexible methods to convert and manipulate data into visual objects as a JavaScript library. There exist other JavaScript web libraries that offer chart templates (such as Highcharts), or web services that can be used to create a range of charts from given (small) data sets, such as Raw or DataWrapper. To clean, transform, merge, and restructure data sources so that they can be visualized appropriately, tools, such as Trifacta and Alteryx, can be used to create pipelines for data wrangling. For statistical analysis and batch-processing data, programming environments, such as R, or libraries for languages, such as Python (e.g., the Python Plotly library), can be used.
A flexible and scalable approach to building monitoring and diagnostics
Published in Symeon E. Christodoulou, Raimar Scherer, eWork and eBusiness in Architecture, Engineering and Construction, 2017
M. Schuss, S. Glawischnig, A. Mahdavi
First modules for data illustration and visualization are implemented in PHP and java scripts. These modules can be used in the related PHP-files of the content management system. Figure 9 shows a typical dashboard block that is generated by a function based on a list of sensor-IDs. These blocks also include direct links to trend chart plots (see Figure 10). The Highchart (Highcharts 2016) java script library was used for the interactive integration of different plot types.
Advanced sensor-based maintenance in real-world exemplary cases
Published in Automatika, 2020
Michele Albano, Luis Lino Ferreira, Giovanni Di Orio, Pedro Maló, Godfried Webers, Erkki Jantunen, Iosu Gabilondo, Mikel Viguera, Gregor Papa
The MANTIS-PC is a Raspberry Pi 3 Model B that acts as a Bluetooth Low Energy (BLE) server, a data-converter, a middleware client, and provides a simple User Interface to inspect the data as they are collected. The MANTIS-PC uses a server-side JavaScript program built over Node.js and the noble library to collect values from both sensors with a period of 30 milliseconds, and sends them to cloud through the Middleware component, which is based on the AMQP [54] protocol. The cloud hosts the components to store the data (Database, or DB), to analyse them (Analysis) and to interact with the user (Human Machine Interface or HMI). The simple HMI presented by the MANTIS-PC (Figure 7) uses a server-side/client-side JavaScript based on Node.js to send warnings to management personnel. The interface is based on the Highcharts library, and it enjoys its “full-responsiveness” capabilities.
The global climate monitor system: from climate data-handling to knowledge dissemination
Published in International Journal of Digital Earth, 2019
Juan Mariano Camarillo-Naranjo, José Ignacio Álvarez-Francoso, Natalia Limones-Rodríguez, María Fernanda Pita-López, Mónica Aguilar-Alba
The system is structured using three levels (Figure 3) of architecture, as follows: Data warehouse: The data server system has a core component comprising a PostgreSQL relational database server (version 9.2) and its spatial extension PostGIS (version 2.0) for point geometry management. At the second level, the system has a file server with a Linux operating system that handles the plain-text files deriving from the netCDF/Grib climate data extraction.Business layer: This layer moves and processes data between the data warehouse and the client and is supported by two main components: a map server and a web server. GeoServer (version 2.5) is selected to handle the transactions between the database server and the clients through WMS and WFS interoperable services. In addition, NGINX (version 1.1.19) is the web server that integrates the standards for web content definition. The latter was chosen because it is the best in terms of the number of requests per second that it can serve and because of its memory usage (DreamHost n.d.).Client (geoviewer): This level is the viewer itself, which is accessible at the following URL: http://www.globalclimatemonitor.org. This viewer has been designed using web standards HTML, CSS and Javascript libraries, which have been adapted for our project. The core JavaScript code library used is the OpenLayer project version 2.13.1 (OpenLayers n.d.), as this is an effective scripting language for online mapping (Pavlicko and Peterson 2005; Peterson 2012). The interactive charts were built by means of the JavaScript charting engine HighCharts (Highcharts n.d.).
Implementing a web-based optimized artificial intelligence system with metaheuristic optimization for improving building energy performance
Published in Journal of Asian Architecture and Building Engineering, 2023
Ngoc-Tri Ngo, Ngoc-Son Truong, Thi Thu Ha Truong, Anh-Duc Pham, Nhat-To Huynh
Highcharts library is a software library for charting written in pure JavaScript (Hønsi et al. 2021). This library was used in the development of a web application for plotting and visualizing the data in this study. With the aid of the Highcharts library, the design of a dashboard is easy and dynamic. It provides users with various features for interacting with data.