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Visual Analytics of Happiness Index In Parallel Coordinate Graph

机译：并行坐标图中的幸福指数的视觉分析

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For decades, quality of work life has always been associated with human wellbeing, which eventually results in happiness. This concept of happiness consistently correlated with increase in business performance, health, marital success, friendship, longevity, creativity, profit and promotion. Thus, a survey work through happiness index assessments method has been undertaken by a university to understand its employees' state of wellbeing. The method accesses the employee happiness index as a mean to understand the employees' wellbeing state. The process starts by first conducting surveys among the employees. The survey data are indexed by responses to nine respondent profiles attributes, which are campus, type of work, group of work, age, sex, and working duration, duration in the current position, marital status and number of children. They are categorized as independent parameters. Then, the employees' happiness is assessed through eight working elements which are selected based on PERMAIg? model. The elements are general, positive emotion, engagement, relationship, meaning, accomplishment, infrastructure and gratitude. These profiles are classified as dependent parameters. Next, the relationship patterns between the two parameters need to be identified. Parallel coordinate graph has been found suitable for the relationships discovery. Since the data are big and complex with huge number of parameters, the graph tends cluttering and the relationship patterns are not revealed. Thus, filtering techniques are performed on the graph as a means to extract the relationship patterns. It is recommended that the result of the analysis to be utilized by the university management in an attempt to increase quality of working life and in supporting human wellbeing as a whole.
机译：几十年来，工作生活质量一直与人类福祉有关，最终会导致幸福。这种幸福的概念始终与业务绩效，健康，婚姻成功，友谊，长寿，创造力，利润和促进的增加相关。因此，通过幸福指数评估方法进行了调查工作，通过大学进行了解其员工的福祉状态。该方法将员工幸福指数访问，作为了解员工的幸福状态。该过程首先在员工中进行调查开始。调查数据通过对九个受访者配置文件的响应来索引，这些属性是校园，工作类型，工作组，性别，性别和工作持续时间，当前位置的持续时间，婚姻状况和儿童人数。它们被分类为独立参数。然后，通过基于Permaig选择的八个工作元素来评估员工的幸福？模型。元素是一般的，积极的情感，参与，关系，意义，成就，基础设施和感恩。这些配置文件被归类为依赖参数。接下来，需要识别两个参数之间的关系模式。发现并行坐标图是适合于关系发现的。由于数据与大量参数大而复杂，因此图表趋于杂乱，并且不透露关系模式。因此，在图中执行过滤技术作为提取关系模式的装置。建议通过大学管理层利用分析的结果，以提高工作生活质量和整体支持人类健康。

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