TY - JOUR
T1 - Urban data and urban design
T2 - A data mining approach to architecture education
AU - Valls, Francesc
AU - Redondo, Ernesto
AU - Fonseca, David
AU - Torres-Kompen, Ricardo
AU - Villagrasa, Sergi
AU - Martí, Nuria
N1 - Funding Information:
Acknowledgments. The authors are grateful to the field investigators for their work and the participants for their cooperation. Funding. This work is supported by the National Key Research and Development Program (grants 2016YFC1304801, 2017YFC1310703), Shanghai Science and Technology Commission Scientific
Funding Information:
Research Plan (18411951804, 17411962900), and Shanghai Municipal Science and Technology Major Project (grant 2017SHZDZX01). Duality of Interest. No potential conflicts of interest relevant to this article were reported. Author Contributions. Y.C. and H.L. analyzed and interpreted the data and wrote the manuscript. Y.C., H.L., L.Q., L.Z., M.X., J.J., Xiaom.L., and X.G. collected the data. Y.L. and C.Y. measured the samples. G.Z., Y.Z., and Xiaoy.L. interpreted the data and revised the manuscript. Q.S. and Xiaoy.L. designed the study. All authors approved the final version of the manuscript. Q.S. and Xiaoy.L. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Funding Information:
This work is supported by the National Key Research and Development Program (grants 2016YFC1304801, 2017YFC1310703), Shanghai Science and Technology Commission Scientific Research Plan (18411951804, 17411962900), and Shanghai Municipal Science and Technology Major Project (grant 2017SHZDZX01).
Publisher Copyright:
© 2017 The Authors
PY - 2018/7
Y1 - 2018/7
N2 - The configuration of urban projects using Information and Communication Technologies is an essential aspect in the education of future architects. Students must know the technologies that will facilitate their academic and professional development, as well as anticipating the needs of the citizens and the requirements of their designs. In this paper, a data mining approach was used to outline the strategic requirements for an urban design project in an architecture course using a Project-Based Learning strategy. Informal data related to an award-winning public space (Gillett Square in London, UK) was retrieved from two social networks (Flickr and Twitter), and from its official website. The analysis focused on semantic, temporal and spatial patterns, aspects generally overlooked in traditional approaches. Text-mining techniques were used to relate semantic and temporal data, focusing on seasonal and weekly (work-leisure) cycles, and the geographic patterns were extracted both from geotagged pictures and by geocoding user locations. The results showed that it is possible to obtain and extract valuable data and information in order to determine the different uses and architectural requirements of an urban space, but such data and information can be challenging to retrieve, structure, analyze and visualize. The main goal of the paper is to outline a strategy and present a visualization of the results, in a way designed to be attractive and informative for both students and professionals – even without a technical background – so the conducted analysis may be reproducible in other urban data contexts.
AB - The configuration of urban projects using Information and Communication Technologies is an essential aspect in the education of future architects. Students must know the technologies that will facilitate their academic and professional development, as well as anticipating the needs of the citizens and the requirements of their designs. In this paper, a data mining approach was used to outline the strategic requirements for an urban design project in an architecture course using a Project-Based Learning strategy. Informal data related to an award-winning public space (Gillett Square in London, UK) was retrieved from two social networks (Flickr and Twitter), and from its official website. The analysis focused on semantic, temporal and spatial patterns, aspects generally overlooked in traditional approaches. Text-mining techniques were used to relate semantic and temporal data, focusing on seasonal and weekly (work-leisure) cycles, and the geographic patterns were extracted both from geotagged pictures and by geocoding user locations. The results showed that it is possible to obtain and extract valuable data and information in order to determine the different uses and architectural requirements of an urban space, but such data and information can be challenging to retrieve, structure, analyze and visualize. The main goal of the paper is to outline a strategy and present a visualization of the results, in a way designed to be attractive and informative for both students and professionals – even without a technical background – so the conducted analysis may be reproducible in other urban data contexts.
KW - Architecture education
KW - Data mining
KW - Informal learning
KW - Urban data
UR - http://www.scopus.com/inward/record.url?scp=85031407152&partnerID=8YFLogxK
U2 - 10.1016/j.tele.2017.09.015
DO - 10.1016/j.tele.2017.09.015
M3 - Article
AN - SCOPUS:85031407152
SN - 0736-5853
VL - 35
SP - 1039
EP - 1052
JO - Telematics and Informatics
JF - Telematics and Informatics
IS - 4
ER -