DATA EXTRACTION PROCESS OF ROAD MAJOR ACCIDENT REPORTS AND USABILITY TESTING OF INFORMATION PRESENTATION BY DATA VISUALIZATION ON WEBSITE
Keywords:
Data Extraction, Road Accidents, Usability Testing, Data VisualizationAbstract
Thailand has an accident database to be used for road safety planning. The major accident report is one of the qualitative data waiting to be utilized, because users have to synthesize the content themselves. Therefore published only in a limited. However, some of the information still contains errors and is not standardized from the context of different informants. The research aims 1) to design and develop of a data extraction process. By accessing and collecting data on the website using web scraping techniques for extract data in 6 issues: province, date, number of deaths, number of injured, vehicle type and number of vehicles involved in the accident for presented to user on data visualization and use in the part of road safety planning at the local level in area or periodic. The results of accuracy evaluation from data extraction process in the issue: “province name”, “date” and “vehicle type” by corpus-based approach and Named Entity Recognition (NER) method is highly accurate, depend on completely of corpus-based. However, the accuracy of the “number of deaths”, “number of injured” and “number of vehicles involved in the accident” by set regular expression for NER method is relatively low compared to corpus-based approach and NER method. Due to a non-standard report format. 2) to usability testing of information presentation by data visualization on website from 30 users determine the sample size on non-probability sampling with purposive sampling, by having each user try it out and evaluate the results through questionnaires 3 times. The usability testing evaluation is good level. When the user was divided into 3 groups according to the context of use: computer user group, traffic information group and general user groups for F-test analysis with LSD found statistically significant difference between the computer experts group and traffic information groups at the 0.05 level in Learnability component. Demonstrate the experience of using relevant traffic systems, which affects the user experience more than the experience of computers and smartphones. At a computer expert group, despite having more using computers and smartphones experience, but the assessment of learnability component is lower than. Which is the design and development of semi-structured data extraction and information presentation by data visualization in the future.
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