The VAPOR Visualization Application

Building information modelling is further globalizing architecture, engineering, and construction (AEC) professional partnerships. However, little is known on the effect of cultural and human factors on BIM-enabled visualization applications. This desktop study examined the extant literature on factors relating to application of BIM-enabled visualization technologies as a process that can improve, leverage, and conduct visual communication for coordination during implementation of global projects. It identifies BIM-enabled visualization having the capability in facilitating knowledge flows in complex discontinuous working environment of a property development's life cycle, and supports designers' understanding in its early working phases. This chapter presents the development of a theoretical proposition for embedding local work culture etiquette in BIM-enabled visualization application for augmenting dynamic knowledge transfer among discontinuous members in a building project. The result is expected to benefit rapidly developing countries (e.g., Malaysia) in enabling successful partnerships with counterparts from developed countries.

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VISUALIZATION OF E-COMMERCE DATA USING AUGMENTED REALITY

Journal of Information System and Technology Management ◽

10.35631/jistm.519009 ◽

2020 ◽

Vol 5 (19) ◽

pp. 104-122

Author(s):

Azzan Amin ◽

Haslina Arshad ◽

Ummul Hanan Mohamad

Keyword(s):

Machine Learning ◽

Augmented Reality ◽

Data Visualization ◽

Data Science ◽

Moving Average ◽

Open Data ◽

Visual Presentation ◽

Depth Dimension ◽

2D Data ◽

Visualization Application

Data visualization is viewed as a significant element in data analysis and communication. As the data engagement becomes more and more complex, visual presentation of data does help users understand the data. So far, two-dimensional (2D) data visuals are often used for the data visualization process, but the lack of depth dimension leads to inefficient and limited understanding of the data. Therefore, the effectiveness of augmented reality (AR) in data visualization was studied through the development of an AR Data Visualization application using E-commerce data. Machine learning models are also involved in the development of this AR application for the provision of data using predictive analysis functions. To provide quality E-commerce data and an optimal machine learning model, the data science process is carried out using the python programming language. The E-commerce data selected for this study is open data taken through the Kaggle Website. This database has 9994 data numbers and 21 attributes. This AR data visualization application will make it easier for users to understand the E-commerce data in-depth through the use of AR technology and be able to visualize the forecasts for sales profit based on the algorithm model "Auto-Regressive Integrated Moving Average" (ARIMA).

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Web-Based Job Aids Using RESTXQ and JavaScript for Authors of XML Documents

Proceedings of Balisage: The Markup Conference 2016 ◽

10.4242/balisagevol17.galtman01 ◽

2016 ◽

Cited By ~ 2

Author(s):

Amanda Galtman

Keyword(s):

Web Applications ◽

Web Based ◽

Job Aids ◽

Xml Documents ◽

Software Company ◽

Technical Writers ◽

Visualization Application ◽

Exchange Data ◽

The Web

Using XML as the source format for authoring technical publications creates opportunities to develop tools that provide analysis, author guidance, and visualization. This case study describes two web applications that take advantage of the XML source format of documents. The applications provide a browser-based tool for technical writers and editors in a 100-person documentation department of a software company. Compared to desktop tools, the web applications are more convenient for users and less affected by hard-to-predict inconsistencies among users' computers. One application analyzes file dependencies and produces custom reports that facilitate reorganizing files. The other helps authors visualize their network of topics in their documentation sets. Both applications rely on the XQuery language and its RESTXQ web API. The visualization application also uses JavaScript, including the powerful jQuery and D3 libraries. After discussing what the applications do and why, this paper describes some architectural highlights, including how the different technologies fit together and exchange data.

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