Using Open Data to Monitor the Status of a Metropolitan Area: The Case of the Metropolitan Area of Turin

被引：6
作者：
Candela F. [1 ]
Mulassano P. [2 ]
机构：
[1] Compagnia di San Paolo, Turin
[2] Compagnia di San Paolo Foundation, Turin
来源：
Data and Information Management | 2021年 / 5卷 / 02期
关键词：
COVID-19; metropolitan area; monitoring; open data; Turin;
D O I：
10.2478/dim-2021-0001
中图分类号：
学科分类号：
摘要：
The paper presents and discusses the method adopted by Compagnia di San Paolo, one of the largest European philanthropic institutions, to monitor the advancement, despite the COVID-19 situation, in providing specific input to the decision-making process for dedicated projects. An innovative approach based on the use of daily open data was adopted to monitor the metropolitan area with a multidimensional perspective. Several open data indicators related to the economy, society, culture, environment, and climate were identified and incorporated into the decision support system dashboard. Indicators are presented and discussed to highlight how open data could be integrated into the foundation's strategic approach and potentially replicated on a large scale by local institutions. Moreover, starting from the lessons learned from this experience, the paper analyzes the opportunities and critical issues surrounding the use of open data, not only to improve the quality of life during the COVID-19 epidemic but also for the effective regulation of society, the participation of citizens, and their well-being. © 2021 Filippo Candela et al., published by Sciendo
引用
收藏
页码：299 / 307
页数：8
相关论文
共 39 条
  • [1] Achrekar H., Gandhe A., Lazarus R., Yu S., Liu B., Predicting flu trends using Twitter data, (2011)
  • [2] Allisio L., Mussa V., Bosco C., Patti V., Ruffo G.F., Felicittà: Visualizing and estimating happiness in Italian cities from geotagged Tweets, Proceedings of the 1st International Workshop on Emotion and Sentiment in Social and Expressive Media: Approaches and Perspectives from AI 1096, pp. 95-106, (2013)
  • [3] Arneodo F., Castelli R., Botta D., Towards a “Smart Region” paradigm: Beyond Smart Cities borders: Piedmont Region experience, (2017)
  • [4] Associazione di Fondazioni e Casse di Risparmio Spa, Ventiquattresimo Rapporto sulle Fondazioni di origine bancaria – Anno 2018, (2018)
  • [5] Battiston R., Il diritto di contare (bene), (2020)
  • [6] Beckwith R., Sherry J., Prendergast D., Data flow in the smart city: Open data versus the commons, The Hackable City, pp. 205-221, (2019)
  • [7] Boseley S., How can coronavirus models get it so wrong?, The Guardian, (2020)
  • [8] Brooks S.K., Webster R.K., Smith L.E., Woodland L., Wessely S., Greenberg N., Rubin G.J., The psychological impact of quarantine and how to reduce it: Rapid review of the evidence, Lancet, 395, 10227, pp. 912-920, (2020)
  • [9] Candela F., Mulassano P., The 120-day COVID-19 epidemic in the metropolitan area of Turin, Italy. The Lancet Preprints, (2020)
  • [10] Dodds P.S., Clark E.M., Desu S., Frank M.R., Reagan A.J., Williams J.R., Danforth C.M., Human language reveals a universal positivity bias, Proceedings of the National Academy of Sciences of the United States of America, 112, 8, pp. 2389-2394, (2015)
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