@book{johnson2007ghost,
   address = {London},
   edition = {Reprint edition},
   title = {The {{Ghost Map}}: {{The Story}} of {{London}}'s {{Most Terrifying Epidemic}}--and {{How It Changed Science}}, {{Cities}}, and the {{Modern World}}},
   isbn = {978-1-59448-269-4},
   shorttitle = {The {{Ghost Map}}},
   abstract = {A National Bestseller, a New York Times Notable Book, and an Entertainment Weekly Best Book of the Year It's the summer of 1854, and London is just emerging as one of the first modern cities in the world. But lacking the infrastructure-garbage removal, clean water, sewers-necessary to support its rapidly expanding population, the city has become the perfect breeding ground for a terrifying disease no one knows how to cure. As the cholera outbreak takes hold, a physician and a local curate are spurred to action-and ultimately solve the most pressing medical riddle of their time. In a triumph of multidisciplinary thinking, Johnson illuminates the intertwined histories of the spread of disease, the rise of cities, and the nature of scientific inquiry, offering both a riveting history and a powerful explanation of how it has shaped the world we live in.},
   language = {English},
   publisher = {{Riverhead Books}},
   author = {<NAME>},
   month = oct,
   year = {2007},
   doi = {10.1080/01944360802146329}
 }

 @incollection{arribas-bel2017looking,
   address = {Cham},
   series = {Advances in {{Spatial Science}}},
   title = {Looking at {{<NAME>}}'s {{Cholera Map}} from the {{Twenty First Century}}: {{A Practical Primer}} on {{Reproducibility}} and {{Open Science}}},
   isbn = {978-3-319-50590-9},
   shorttitle = {Looking at {{<NAME>}}'s {{Cholera Map}} from the {{Twenty First Century}}},
   abstract = {This chapter (This manuscript is a chapter version of the original document, which is a reproducible online notebook. The entire, version-controlled project can be found online at: https://bitbucket.org/darribas/reproducible\_john\_snow.) presents an entirely reproducible spatial analysis of the classic John Snow's map of the 1854 cholera epidemic in London. The analysis draws on many of the techniques most commonly used by regional scientists, such as choropleth mapping, spatial autocorrelation, and point pattern analysis. In doing so, the chapter presents a practical roadmap for performing a completely open and reproducible analysis in regional science. In particular, we deal with the automation of (1) synchronizing code and text, (2) presenting results in figures and tables, and (3) generating reference lists. In addition, we discuss the significant added value of version control systems and their role in enhancing transparency through public, open repositories. With this chapter, we aim to practically illustrate a set of principles and techniques that facilitate transparency and reproducibility in empirical research, both keys to the health and credibility of regional science in the next 50 years to come.},
   language = {en},
   booktitle = {Regional {{Research Frontiers}} - {{Vol}}. 2: {{Methodological Advances}}, {{Regional Systems Modeling}} and {{Open Sciences}}},
   publisher = {{Springer International Publishing}},
   author = {{Arribas-Bel}, Daniel and {<NAME>}, <NAME> Rey, <NAME>.},
   editor = {<NAME> and <NAME>},
   year = {2017},
   keywords = {Regional Science,Spatial Autocorrelation,Spatial Outlier,Spatial Weight Matrix,Street Segment},
   pages = {283-306},
   doi = {10.1007/978-3-319-50590-9_17}
 }

 @book{tufte2001visual,
   title = {The Visual Display of Quantitative Information},
   publisher = {{Graphics Press Cheshire, CT, USA}},
   author = {<NAME>.},
   year = {2001}
 }

 @article{goodchild2007citizen,
   title = {Citizen as Sensors: The World of Volunteered Geography},
   volume = {69},
   journal = {GeoJournal},
   author = {Goodchild, <NAME>},
   year = {2007},
   keywords = {volunteer geographic information},
   pages = {211--221}
 }

 @article{arribas-bel2014accidental,
   title = {Accidental, Open and Everywhere: {{Emerging}} Data Sources for the Understanding of Cities},
   volume = {49},
   issn = {01436228},
   shorttitle = {Accidental, Open and Everywhere},
   abstract = {In this paper, I review the recent emergence of three groups of data sources and assess some of the opportunities and challenges they pose for the understanding of cities, particularly in the context of the Regional Science and urban research agenda. These are data collected from mobile sensors carried by individuals, data derived from businesses moving their activity online and government data released in an open format. Although very different from each other, they are all becoming available as a side-effect since they were created with different purposes but their degree of popularity, pervasiveness and ease of access is turning them into interesting alternatives for researchers. Existing projects and initiatives that conform to each class are featured as illustrative examples of these new potential sources of knowledge. \'O 2013 Elsevier Ltd. All rights reserved.},
   language = {en},
   journal = {Applied Geography},
   doi = {10.1016/j.apgeog.2013.09.012},
   author = {{Arribas-Bel}, Daniel},
   month = may,
   year = {2014},
   pages = {45-53},
   file = {/home/lw17329/Zotero/storage/I4QFYAPM/Arribas-Bel - 2014 - Accidental, open and everywhere Emerging data sou.pdf}
 }

 @article{anselin1988spatial,
   title = {Do Spatial Effects Really Matter in Regression Analysis?},
   volume = {65},
   journal = {Papers Regional Science},
   author = {<NAME> <NAME>},
   year = {1988},
   keywords = {Spatial dependence},
   pages = {11--34},
   doi = {10.1111/j.1435-5597.1988.tb01155.x}
 }

 @book{anselin2014modern,
   address = {Chicago, IL},
   title = {Modern {{Spatial Econometrics}} in {{Practice}}, a {{Guide}} to {{GeoDa}}, {{GeoDaSpace}}, and {{PySAL}}},
   publisher = {{GeoDa Press}},
   author = {<NAME> Rey, <NAME>.},
   year = {2014}
 }

 @article{rey2009show,
   title = {Show Me the Code: Spatial Analysis and Open Source},
   volume = {11},
   issn = {1435-5930, 1435-5949},
   shorttitle = {Show Me the Code},
   language = {en},
   number = {2},
   journal = {Journal of Geographical Systems},
   doi = {10.1007/s10109-009-0086-8},
   author = {Rey, <NAME>.},
   month = jun,
   year = {2009},
   pages = {191--207},
   file = {/home/lw17329/Dropbox/literature/Rey - 2009 - Show me the code spatial analysis and open source.pdf;/home/lw17329/Zotero/storage/E6UEYX4F/art\%3A10.1007\%2Fs10109-009-0086-8.pdf;/home/lw17329/Zotero/storage/K9JRHXCG/art\%3A10.1007\%2Fs10109-009-0086-8.pdf}
 }

 @incollection{rey2018code,
   address = {Cham},
   series = {Advances in {{Geographic Information Science}}},
   title = {Code as {{Text}}: {{Open Source Lessons}} for {{Geospatial Research}} and {{Education}}},
   isbn = {978-3-319-59511-5},
   shorttitle = {Code as {{Text}}},
   abstract = {This chapter examines the potential opportunities that open source offers for research and education in spatial analysis. Drawing on lessons learned in the development of PySAL: Python Library for Spatial Analysis, it touches on the opportunities and challenges related to the adoption of open source practices and culture. While open source has had major impacts on pedagogy and research in spatial analysis, these are somewhat under-appreciated and at times seen as separate spheres. A central argument is that a mind shift is required that comes to see code not just as a tool for doing research, but rather to view code as text in the sense it becomes an object of research. The chapter reconsiders open source spatial analysis teaching and research from this lens of code as text.},
   language = {en},
   booktitle = {{{GeoComputational Analysis}} and {{Modeling}} of {{Regional Systems}}},
   publisher = {{Springer International Publishing}},
   author = {<NAME>.},
   editor = {<NAME> and <NAME>},
   year = {2018},
   pages = {7-21},
   doi = {10.1007/978-3-319-59511-5_2}
 }

 @techreport{ucgis2019geographic,
   title = {Geographic {{Information Science}} and {{Technology Body}} of {{Knowledge}}},
   author = {{University Consortium of Geographic Information Science}},
   year = {2019},
   file = {/home/lw17329/Zotero/storage/9INJ4PZ7/gistbok.ucgis.org.html}
 }
 
 @misc{kelsey_jordahl_2019_3333010,
  author       = {<NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  maxalbert and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME> and
                  \"<NAME> and
                  <NAME>},
  title        = {geopandas/geopandas: v0.5.1},
  month        = jul,
  year         = 2019,
  doi          = {10.5281/zenodo.3333010},
  url          = {https://doi.org/10.5281/zenodo.3333010}
}

@misc{aleksey_bilogur_2019_3475569,
  author       = {<NAME> and
                  <NAME> and
                  <NAME> and
                  <NAME>},
  title        = {ResidentMario/geoplot 0.3.3},
  month        = oct,
  year         = 2019,
  doi          = {10.5281/zenodo.3475569},
  url          = {https://doi.org/10.5281/zenodo.3475569}
}

@article{roth2010vba,
  author = {<NAME> and <NAME> and <NAME>},
  title = {Value-by-alpha maps: {An} alternative to the cartogram},
  journal = {The Cartographic Journal},
  year = {2010},
  volume = 47,
  issue = 2,
  pages = {130--140},
  doi = {10.1179/000870409X12488753453372}
  }
