TY - JOUR
T1 - An open source toolkit for identifying comparative space-time research questions
AU - Xinyue, Ye
AU - Bing, She
AU - Ling, Wu
AU - Xinyan, Zhu
AU - Yeqing, Cheng
N1 - Funding Information:
Received date: 2013-09-02; accepted date: 2013-11-25 Foundation item: Under the auspices of Humanities and Social Science Research, Major Project of Chinese Ministry of Education (No. 13JJD790008), Basic Research Funds of National Higher Education Institutions of China (No. 2722013JC030), Zhongnan University of Economics and Law 2012 Talent Grant (No. 31541210702), Key Research Program of Chinese Academy of Sciences (No. KZZD-EW-06-03, KSZD-EW-Z-021-03), National Key Science and Technology Support Program of China (No. 2012BAH35B03) Corresponding author: CHENG Yeqing. E-mail: [email protected] © Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag Berlin Heidelberg 2014
PY - 2014/6
Y1 - 2014/6
N2 - Comparative space-time thinking lies at the heart of spatiotemporally integrated social sciences. The multiple dimensions and scales of socioeconomic dynamics pose numerous challenges for the application and evaluation of public policies in the comparative context. At the same time, social scientists have been slow to adopt and implement new spatiotemporally explicit methods of data analysis due to the lack of extensible software packages, which becomes a major impediment to the promotion of spatiotemporal thinking. The proposed framework will address this need by developing a set of research questions based on space-time-distributional features of socioeconomic datasets. The authors aim to develop, evaluate, and implement this framework in an open source toolkit to comprehensively quantify the changes and level of hidden variation of space-time datasets across scales and dimensions. Free access to the source code allows a broader community to incorporate additional advances in perspectives and methods, thus facilitating interdisciplinary collaboration. Being written in Python, it is entirely cross-platform, lowering transmission costs in research and education.
AB - Comparative space-time thinking lies at the heart of spatiotemporally integrated social sciences. The multiple dimensions and scales of socioeconomic dynamics pose numerous challenges for the application and evaluation of public policies in the comparative context. At the same time, social scientists have been slow to adopt and implement new spatiotemporally explicit methods of data analysis due to the lack of extensible software packages, which becomes a major impediment to the promotion of spatiotemporal thinking. The proposed framework will address this need by developing a set of research questions based on space-time-distributional features of socioeconomic datasets. The authors aim to develop, evaluate, and implement this framework in an open source toolkit to comprehensively quantify the changes and level of hidden variation of space-time datasets across scales and dimensions. Free access to the source code allows a broader community to incorporate additional advances in perspectives and methods, thus facilitating interdisciplinary collaboration. Being written in Python, it is entirely cross-platform, lowering transmission costs in research and education.
KW - Comparative
KW - Open source
KW - Spatiotemporally integrated social sciences
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U2 - 10.1007/s11769-014-0679-0
DO - 10.1007/s11769-014-0679-0
M3 - Article
AN - SCOPUS:84938483266
SN - 1002-0063
VL - 24
SP - 348
EP - 361
JO - Chinese Geographical Science
JF - Chinese Geographical Science
IS - 3
ER -