{"title":"在基于图形的分析中可视化与时间相关的关键性能指标","authors":"Stefan Hesse, M. Spehr, S. Gumhold, Rainer Groh","doi":"10.1109/ETFA.2014.7005110","DOIUrl":null,"url":null,"abstract":"The usage of visual analytics during the analysis of business warehouse calculated key performance indicators is one emerging challenge in modern business applications. On the one hand, a complex network of key performance indicators has to be supervised. On the other hand, within this network only few key performance indicators change obviously within a short period of time. The sole mapping of the complexity of a network of key performance indicators to a graph-based visualization only covers static information and neglects temporal dependencies. We present a new visualization approach for the enrichment of graph-based visualizations of key performance indicator networks by introducing a multi-encoded visualization of additional functional, contextual and temporal information. The should help the user to understand relationships between KPIs and alert him if something is going wrong.","PeriodicalId":20477,"journal":{"name":"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Visualizing time-dependent key performance indicator in a graph-based analysis\",\"authors\":\"Stefan Hesse, M. Spehr, S. Gumhold, Rainer Groh\",\"doi\":\"10.1109/ETFA.2014.7005110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The usage of visual analytics during the analysis of business warehouse calculated key performance indicators is one emerging challenge in modern business applications. On the one hand, a complex network of key performance indicators has to be supervised. On the other hand, within this network only few key performance indicators change obviously within a short period of time. The sole mapping of the complexity of a network of key performance indicators to a graph-based visualization only covers static information and neglects temporal dependencies. We present a new visualization approach for the enrichment of graph-based visualizations of key performance indicator networks by introducing a multi-encoded visualization of additional functional, contextual and temporal information. The should help the user to understand relationships between KPIs and alert him if something is going wrong.\",\"PeriodicalId\":20477,\"journal\":{\"name\":\"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETFA.2014.7005110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2014.7005110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visualizing time-dependent key performance indicator in a graph-based analysis
The usage of visual analytics during the analysis of business warehouse calculated key performance indicators is one emerging challenge in modern business applications. On the one hand, a complex network of key performance indicators has to be supervised. On the other hand, within this network only few key performance indicators change obviously within a short period of time. The sole mapping of the complexity of a network of key performance indicators to a graph-based visualization only covers static information and neglects temporal dependencies. We present a new visualization approach for the enrichment of graph-based visualizations of key performance indicator networks by introducing a multi-encoded visualization of additional functional, contextual and temporal information. The should help the user to understand relationships between KPIs and alert him if something is going wrong.