Systematic mapping assesses the nature of an evidence base, answering how much evidence exists on a particular topic. Perhaps the most useful outputs of a systematic map are an interactive database of studies and their meta-data, along with visualisations of this database. Despite the rapid increase in systematic mapping as an evidence synthesis method, there is currently a lack of Open Source software for producing interactive visualisations of systematic map databases. In April 2018, as attendees at and coordinators of the first ever Evidence Synthesis Hackathon in Stockholm, we decided to address this issue by developing an R-based tool called EviAtlas, an Open Access (i.e. free to use) and Open Source (i.e. software code is freely accessible and reproducible) tool for producing interactive, attractive tables and figures that summarise the evidence base. Here, we present our tool which includes the ability to generate vital visualisations for systematic maps and reviews as follows: a complete data table; a spatially explicit geographical information system (Evidence Atlas); Heat Maps that cross-tabulate two or more variables and display the number of studies belonging to multiple categories; and standard descriptive plots showing the nature of the evidence base, for example the number of studies published per year or number of studies per country. We believe that EviAtlas will provide a stimulus for the development of other exciting tools to facilitate evidence synthesis.
Systematic mapping assesses the nature of an evidence base, answering how much evidence exists on a particular topic. Perhaps the most useful outputs of a systematic map are an interactive database of studies and their meta-data, along with visualisations of this database. Despite the rapid increase in systematic mapping as an evidence synthesis method, there is currently a lack of Open Source software for producing interactive visualisations of systematic map databases. In April 2018, as attendees at and coordinators of the first ever Evidence Synthesis Hackathon in Stockholm, we decided to address this issue by developing an R-based tool called EviAtlas, an Open Access (i.e. free to use) and Open Source (i.e. software code is freely accessible and reproducible) tool for producing interactive, attractive tables and figures that summarise the evidence base. Here, we present our tool which includes the ability to generate vital visualisations for systematic maps and reviews as follows: a complete data table; a spatially explicit geographical information system (Evidence Atlas); Heat Maps that cross-tabulate two or more variables and display the number of studies belonging to multiple categories; and standard descriptive plots showing the nature of the evidence base, for example the number of studies published per year or number of studies per country. We believe that EviAtlas will provide a stimulus for the development of other exciting tools to facilitate evidence synthesis.
The Urban Environment and Social Inclusion Index (UESI) creates a new spatial framework to measure progress toward Sustainable Development Goal 11 (SDG-11). SDG-11 aims for cities to be both sustainable and inclusive by 2030 and conceptualizes this goal in spatially-explicit ways. Few data sources or indices, however, measure its progress in both a comprehensive (global coverage) and detailed (intra-city) manner. To address this gap, we use publicly-available datasets including detailed census data, satellite remote sensing, and crowdsourced data that provide global coverage and regular temporal resolution to develop spatially-explicit indicators to measure neighborhood-level environmental performance in 164 global cities. The UESI framework includes 10 indicators that assess air pollution, urban tree cover, public transit access, and urban heat at the neighborhood scale, and water stress and carbon dioxide emissions from fossil fuels at the city-level. We also present a new method for quantifying distributional equity to measure how evenly or unevenly cities are distributing environmental benefits and burdens across neighborhoods. We find that the majority of the UESI cities disproportionately burden lower-income communities with higher shares of environmental burdens and lower shares of environmental benefits. This finding holds true even in cities that perform highly on environmental indicators. In light of the challenging, rapidly evolving urban contexts, the UESI framework serves as a way of addressing some of the central challenges—data standardization, data gathering, and data localization—around the SDGs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.