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Dataset for assessing the scope and nature of global stream daylighting practices

This paper presents five publicly available datasets (I through V) of which two are interactive and visual tools (a Tableau Dashboard and an Interactive Map). These five datasets were extracted from 115 literature sources on the daylighting of streams that were published between 1992 and 2018. Datas...

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Autores principales: Khirfan, Luna, Mohtat, Niloofar, Peck, Megan, Chan, Andrew, Ma, Lucas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578685/
https://www.ncbi.nlm.nih.gov/pubmed/33102650
http://dx.doi.org/10.1016/j.dib.2020.106366
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author Khirfan, Luna
Mohtat, Niloofar
Peck, Megan
Chan, Andrew
Ma, Lucas
author_facet Khirfan, Luna
Mohtat, Niloofar
Peck, Megan
Chan, Andrew
Ma, Lucas
author_sort Khirfan, Luna
collection PubMed
description This paper presents five publicly available datasets (I through V) of which two are interactive and visual tools (a Tableau Dashboard and an Interactive Map). These five datasets were extracted from 115 literature sources on the daylighting of streams that were published between 1992 and 2018. Dataset I consist of 19 variables that combine two types of data extracted from these sources: ten manifest variables (indisputable, obvious, factual) and nine variables extracted from the sources’ latent content (indirect, hence, based on careful reading of the sources’ contents). Manifest variables include, among others, authors’ names and affiliations, authorship location, and publication year. Latent variables include primarily the literature sources’ underlying themes and their sub-themes (sub-categories), the daylighting case studies/projects discussed, and the geographic coverage or scope addressed in the literature sources. Datasets II identifies 16 literature sources that delve into the climate change adaptation and/or mitigation theme and reveal how it was tackled vis-à-vis the other themes/sub-themes. Dataset III identifies and provides detailed information on the 145 different stream daylighting case studies/projects mentioned in the literature's sources, such as each project's location, daylighted length, completion date, cost, and type of treatment. Dataset IV is a Tableau Dashboard that offers interactive analytical querying in the form of relational analyses and data visualization while Dataset V is an Interactive Map created in Google My Map that maps the 145 stream daylighting case studies/projects mentioned in the literature sources over and provides a synopsis on each based on the literature's contents. The combination of these five datasets and their diversity in type and presentation yields a comprehensive, global, and unique repository of information on the daylighting of urban streams for all types of audiences (academic, professional, and laypeople).
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spelling pubmed-75786852020-10-23 Dataset for assessing the scope and nature of global stream daylighting practices Khirfan, Luna Mohtat, Niloofar Peck, Megan Chan, Andrew Ma, Lucas Data Brief Data Article This paper presents five publicly available datasets (I through V) of which two are interactive and visual tools (a Tableau Dashboard and an Interactive Map). These five datasets were extracted from 115 literature sources on the daylighting of streams that were published between 1992 and 2018. Dataset I consist of 19 variables that combine two types of data extracted from these sources: ten manifest variables (indisputable, obvious, factual) and nine variables extracted from the sources’ latent content (indirect, hence, based on careful reading of the sources’ contents). Manifest variables include, among others, authors’ names and affiliations, authorship location, and publication year. Latent variables include primarily the literature sources’ underlying themes and their sub-themes (sub-categories), the daylighting case studies/projects discussed, and the geographic coverage or scope addressed in the literature sources. Datasets II identifies 16 literature sources that delve into the climate change adaptation and/or mitigation theme and reveal how it was tackled vis-à-vis the other themes/sub-themes. Dataset III identifies and provides detailed information on the 145 different stream daylighting case studies/projects mentioned in the literature's sources, such as each project's location, daylighted length, completion date, cost, and type of treatment. Dataset IV is a Tableau Dashboard that offers interactive analytical querying in the form of relational analyses and data visualization while Dataset V is an Interactive Map created in Google My Map that maps the 145 stream daylighting case studies/projects mentioned in the literature sources over and provides a synopsis on each based on the literature's contents. The combination of these five datasets and their diversity in type and presentation yields a comprehensive, global, and unique repository of information on the daylighting of urban streams for all types of audiences (academic, professional, and laypeople). Elsevier 2020-10-06 /pmc/articles/PMC7578685/ /pubmed/33102650 http://dx.doi.org/10.1016/j.dib.2020.106366 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Khirfan, Luna
Mohtat, Niloofar
Peck, Megan
Chan, Andrew
Ma, Lucas
Dataset for assessing the scope and nature of global stream daylighting practices
title Dataset for assessing the scope and nature of global stream daylighting practices
title_full Dataset for assessing the scope and nature of global stream daylighting practices
title_fullStr Dataset for assessing the scope and nature of global stream daylighting practices
title_full_unstemmed Dataset for assessing the scope and nature of global stream daylighting practices
title_short Dataset for assessing the scope and nature of global stream daylighting practices
title_sort dataset for assessing the scope and nature of global stream daylighting practices
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578685/
https://www.ncbi.nlm.nih.gov/pubmed/33102650
http://dx.doi.org/10.1016/j.dib.2020.106366
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