Data Visualization Revisited

Introduction:Data visualization quality is important for the work of a geographic information system operator, determining the conditions under which he or she makes decisions concerning the displayed data. Visual perception patterns associated with the golden ratio properties allow us to formulate a criterion for data visualization quality which would characterize the possibilities of the operator’s complex perception of the video data displayed on a control device screen in the form of an electronic card.Purpose:Substantiation of a data visualization quality criterion for geoinformation systems using the golden ratio properties, and the study of the conditions for providing good visualization quality for geodata and metadata on a video control device screen in accordance with the proposed criterion.Methods:A formal definition of the data visualization quality criterion in geoinformation systems using the coefficient of the screen area information coverage as an index whose optimal value corresponds to the mathematical definition of the golden ratio; and the study of the properties of this criterion. Results: Based on the conducted analysis of visual perception of video data and golden ratio properties during the data visualization, a criterion is proposed for data visualization quality, which uses the golden ratio properties and characterizes the possibilities of complex perception of video data in an electronic map form by a geographic information system operator. Iteration algorithms for choosing the video data display scale are developed, based on the visualization quality criterion and related to the golden ratio properties. These are the basic algorithm used for each geodata layer represented on the electronicmap, and an algorithm of successive analysis of various layers of the displayed geodata. The choice of a video data display scale in accordance with the developed algorithms can be preliminarily carried out by the system operator using the parameters of standard electronic maps and geodata/metadata sets typical for the current applied problem. We have studied how the scale of the geodata and metadata displayed on an electronic map affects their visualization quality on screens of various sizes. For the considered standard volumes of displayed geodata and metadata, the best visualization quality was achieved when they were displayed on a standard computer monitor, as opposed to a portable notebook or visualization screen.Practical relevance:The proposed criterion and the recommendations for choosing a screen size for the video monitoring device or the structures of the displayed geo-objects and metadata can be used in the design of geoinformation systems, or for preliminary choice of the displayed data structure by a geoinformation system operator.

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Data Visualization Indicator Disease (Malaria, Dengue Fever, and Measles) in The Year 2012-2015

International Journal of New Media Technology ◽

10.31937/ijnmt.v4i2.785 ◽

2017 ◽

Vol 4 (2) ◽

pp. 87-93

Author(s):

Immanuel Luigi Da Gusta ◽

Johan Setiawan

Keyword(s):

Data Mining ◽

Human Resources ◽

Data Visualization ◽

Health Sector ◽

Medical Personnel ◽

Database Systems ◽

Process Time ◽

Acceptance Test ◽

Visual Data Mining ◽

The Government

The aim of this paper are: to create a data visualization that can assist the Government in evaluating the return on the development of health facilities in the region and province area in term of human resources for medical personnel, to help community knowing the amount of distribution of hospitals with medical personnel in the regional area and to map disease indicator in Indonesia. The issue of tackling health is still a major problem that is not resolved by the Government of Indonesia. There are three big things that become problems in the health sector in Indonesia: infrastructure has not been evenly distributed and less adequate, the lack of human resources professional health workforce, there is still a high number of deaths in the outbreak of infectious diseases. Data for the research are taken from BPS, in total 10,600 records after the Extract, Transform and Loading process. Time needed to convert several publications from PDF, to convert to CSV and then to MS Excel 3 weeks. The method used is Eight-step Data Visualization and Data Mining methodology. Tableau is chosen as a tool to create the data visualization because it can combine each dasboard inside a story interactive, easier for the user to analyze the data. The result is a story with 3 dashboards that can fulfill the requirement from BPS staff and has been tested with a satisfied result in the UAT (User Acceptance Test). Index Terms—Dashboard, data visualization, disease, malaria, Tableau REFERENCES [1] S. Arianto, Understanding of learning and others, 2008. [2] Rainer; Turban, Introduction to Information Systems, Danvers: John Wiley & Sons, Inc, 2007. [3] V. Friedman, Data Visualization Infographics, Monday Inspirition, 2008. [4] D. A. Keim, "Information Visualization and Visual Data Mining," IEEE Transactions on Visualization and Computer Graphics 8.1, pp. 1-8, 2002. [5] Connolly and Begg, Database Systems, Boston: Pearson Education, Inc, 2010. [6] E. Hariyanti, "Pengembangan Metodologi Pembangunan Information Dashboard Untuk Monitoring kinerja Organisasi," Konferensi dan Temu Nasional Teknologi Informasi dan Komunikasi untuk Indonesia, p. 1, 2008. [7] S. Darudiato, "Perancangan Data Warehouse Penjualan Untuk Mendukung Kebutuhan Informasi Eksekutif Cemerlang Skin Care," Seminar Nasional Informatika 2010, pp. E-353, 2010.

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