C. Giovannella, Diana Andone, M. Dascalu, E. Popescu, M. Rehm, Ó. Mealha
{"title":"评估自下而上方法的弹性,该方法用于检测和基准大学校园的智慧","authors":"C. Giovannella, Diana Andone, M. Dascalu, E. Popescu, M. Rehm, Ó. Mealha","doi":"10.1109/ISC2.2016.7580792","DOIUrl":null,"url":null,"abstract":"A new method to perform a bottom-up extraction and benchmark of the perceived multilevel smartness of complex ecosystems has been recently described and applied to territories and learning ecosystems like university campuses and schools. In this paper we study the resilience of our method by comparing and integrating the data collected in several European Campuses during two different academic years, 2014-15 and 2015-16. The overall results are: a) a more adequate and robust definition of the orthogonal multidimensional space of representation of the smartness, and b) the definition of a procedure to identify data that exhibits a limited level of trust.","PeriodicalId":171503,"journal":{"name":"2016 IEEE International Smart Cities Conference (ISC2)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Evaluating the resilience of the bottom-up method used to detect and benchmark the smartness of university campuses\",\"authors\":\"C. Giovannella, Diana Andone, M. Dascalu, E. Popescu, M. Rehm, Ó. Mealha\",\"doi\":\"10.1109/ISC2.2016.7580792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method to perform a bottom-up extraction and benchmark of the perceived multilevel smartness of complex ecosystems has been recently described and applied to territories and learning ecosystems like university campuses and schools. In this paper we study the resilience of our method by comparing and integrating the data collected in several European Campuses during two different academic years, 2014-15 and 2015-16. The overall results are: a) a more adequate and robust definition of the orthogonal multidimensional space of representation of the smartness, and b) the definition of a procedure to identify data that exhibits a limited level of trust.\",\"PeriodicalId\":171503,\"journal\":{\"name\":\"2016 IEEE International Smart Cities Conference (ISC2)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Smart Cities Conference (ISC2)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISC2.2016.7580792\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Smart Cities Conference (ISC2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISC2.2016.7580792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating the resilience of the bottom-up method used to detect and benchmark the smartness of university campuses
A new method to perform a bottom-up extraction and benchmark of the perceived multilevel smartness of complex ecosystems has been recently described and applied to territories and learning ecosystems like university campuses and schools. In this paper we study the resilience of our method by comparing and integrating the data collected in several European Campuses during two different academic years, 2014-15 and 2015-16. The overall results are: a) a more adequate and robust definition of the orthogonal multidimensional space of representation of the smartness, and b) the definition of a procedure to identify data that exhibits a limited level of trust.