Pub Date : 2025-12-10DOI: 10.1016/j.softx.2025.102449
Karim Elasri, Thomas Lagoarde-Ségot
The objective of this paper is to make ecological macroeconomic modeling accessible to all by sharing the code, technical appendix and User Manual of Philia 1.0, an ongoing modeling project used in several academic papers. Philia 1.0 is a middle-sized model of 500 equations describing the interaction between an artificial economy and a simplified Earth system. This model yields analytical insight into the impact of a wide array of sustainable transition policies on the macroeconomy, climate, inequalities, and postgrowth welfare indicators. The E-views code modules discussed in this paper are scalable so that researchers can easily introduce new variables, recalibrate the model, change parameter value or include new structural relationships to develop their own policy scenarios.
{"title":"Ecological macroeconomics with Philia 1.0","authors":"Karim Elasri, Thomas Lagoarde-Ségot","doi":"10.1016/j.softx.2025.102449","DOIUrl":"10.1016/j.softx.2025.102449","url":null,"abstract":"<div><div>The objective of this paper is to make ecological macroeconomic modeling accessible to all by sharing the code, technical appendix and User Manual of <em>Philia 1.0</em>, an ongoing modeling project used in several academic papers. Philia 1.0 is a middle-sized model of 500 equations describing the interaction between an artificial economy and a simplified Earth system. This model yields analytical insight into the impact of a wide array of sustainable transition policies on the macroeconomy, climate, inequalities, and postgrowth welfare indicators. The E-views code modules discussed in this paper are scalable so that researchers can easily introduce new variables, recalibrate the model, change parameter value or include new structural relationships to develop their own policy scenarios.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102449"},"PeriodicalIF":2.4,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-09DOI: 10.1016/j.softx.2025.102473
José Hugo Barrón-Zambrano , Marco Aurelio Nuño-Maganda , Melchor Hernández-Díaz , José de Jesús Rangel-Magdaleno , Yahir Hernández-Mier
Education in Science, Technology, Engineering, Arts, and Mathematics (STEAM) is crucial for developing essential skills in today’s society. A key issue for researchers in the Education and Behavioral Sciences (EBS) fields is to assess the evolution of Computational Thinking (CT) in learners through the use of educational robotics, which is a powerful tool that enhances learning by allowing students to apply theoretical knowledge to real-world scenarios. In this article, we propose a 2D-3D virtual and physical robotic platform for STEM/STEAM education, enabling users to interact with a low-cost line-following educational robotic platform, equipped with an onboard computer, sensors, and actuators. The platform is user-programmable and integrates the ROS operating system to define the robot’s movement and path, as well as to visualize the robot’s movement in real-time. The platform is also accessible to educators and the general public for exploratory and pedagogical use. We report results related to the application of the competent Computational Thinking Test (cCTt) instrument to a small group of students, which may be of particular relevance to the Education and Behavioral Sciences (EBS) community for validating the acquisition of CT skills through the proposed platform for larger learner groups.
{"title":"Mobile2D-3D-RoboticSim: A robotic platform for computational thinking assessment in STEM and STEAM education","authors":"José Hugo Barrón-Zambrano , Marco Aurelio Nuño-Maganda , Melchor Hernández-Díaz , José de Jesús Rangel-Magdaleno , Yahir Hernández-Mier","doi":"10.1016/j.softx.2025.102473","DOIUrl":"10.1016/j.softx.2025.102473","url":null,"abstract":"<div><div>Education in Science, Technology, Engineering, Arts, and Mathematics (STEAM) is crucial for developing essential skills in today’s society. A key issue for researchers in the Education and Behavioral Sciences (EBS) fields is to assess the evolution of Computational Thinking (CT) in learners through the use of educational robotics, which is a powerful tool that enhances learning by allowing students to apply theoretical knowledge to real-world scenarios. In this article, we propose a 2D-3D virtual and physical robotic platform for STEM/STEAM education, enabling users to interact with a low-cost line-following educational robotic platform, equipped with an onboard computer, sensors, and actuators. The platform is user-programmable and integrates the ROS operating system to define the robot’s movement and path, as well as to visualize the robot’s movement in real-time. The platform is also accessible to educators and the general public for exploratory and pedagogical use. We report results related to the application of the competent Computational Thinking Test (cCTt) instrument to a small group of students, which may be of particular relevance to the Education and Behavioral Sciences (EBS) community for validating the acquisition of CT skills through the proposed platform for larger learner groups.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102473"},"PeriodicalIF":2.4,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-09DOI: 10.1016/j.softx.2025.102477
Catherine Gilbert , German Mandrini , Elhan Ersoz , Nicolas Martin
Agricultural research relies on accurate characterization of the growing environment in field trials. Thus, it is critical to describe the crop growing conditions at a particular trial location. We developed the seasonal characterization engine (SCE), an R shiny app which allows researchers to generate seasonal profiles for a given set of trials. The SCE interfaces with APSIM to dynamically model crop development under the specified trial conditions and returns seasonal information to the user. Seasonal profiles are useful for environmental description and analysis in multi-environment crop varietal trials. Seasonal covariates, derived from these profiles, are useful, biologically relevant parameters for capturing environmental effects in models of crop adaptation. We anticipate that this application will be used by researchers and agronomists to facilitate the description of seasonal conditions and the collection of phenologically derived environmental information which may be used in subsequent modeling.
{"title":"The seasonal characterization engine, an application for describing environment from the perspective of crop development","authors":"Catherine Gilbert , German Mandrini , Elhan Ersoz , Nicolas Martin","doi":"10.1016/j.softx.2025.102477","DOIUrl":"10.1016/j.softx.2025.102477","url":null,"abstract":"<div><div>Agricultural research relies on accurate characterization of the growing environment in field trials. Thus, it is critical to describe the crop growing conditions at a particular trial location. We developed the seasonal characterization engine (SCE), an R shiny app which allows researchers to generate seasonal profiles for a given set of trials. The SCE interfaces with APSIM to dynamically model crop development under the specified trial conditions and returns seasonal information to the user. Seasonal profiles are useful for environmental description and analysis in multi-environment crop varietal trials. Seasonal covariates, derived from these profiles, are useful, biologically relevant parameters for capturing environmental effects in models of crop adaptation. We anticipate that this application will be used by researchers and agronomists to facilitate the description of seasonal conditions and the collection of phenologically derived environmental information which may be used in subsequent modeling.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102477"},"PeriodicalIF":2.4,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1016/j.softx.2025.102464
M. Guthrie , M.M. Walsh , K.A. Travis , S.R. Boston , D.L. Caballero , D.D. Dinger , G. Elsarboukh , J.M. Hetrick , A.T. Savici , P.F. Peterson
SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.
{"title":"SNAPRed: Reduction of multidimensional neutron time-of-flight diffraction data","authors":"M. Guthrie , M.M. Walsh , K.A. Travis , S.R. Boston , D.L. Caballero , D.D. Dinger , G. Elsarboukh , J.M. Hetrick , A.T. Savici , P.F. Peterson","doi":"10.1016/j.softx.2025.102464","DOIUrl":"10.1016/j.softx.2025.102464","url":null,"abstract":"<div><div>SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102464"},"PeriodicalIF":2.4,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1016/j.softx.2025.102479
Jakub Śledziowski , Paweł Terefenko , Andrzej Giza , Kamran Tanwari , Dominik Paprotny
Modern climate impact and attribution science requires timely, high-resolution meteorological and hydrological data. The CLIMB workflow is an open-source framework integrating state-of-the-art datasets and methods for operational generation of high-resolution climate datasets tailored for attribution studies of floods, droughts, heatwaves, and other extremes. We show that global climate reanalysis can be efficiently bias-adjusted and downscaled, and further converted into readily-usable climate indicators. The choice of variables and formatting of the data enables direct application in hydrological models. The workflow implements a fully scripted pipeline that can be automated via cron scheduling, providing daily meteorological outputs. We show an application of the workflow for operational monitoring weather extremes in Poland.
{"title":"CLIMB: Framework for CLIMate data bias-adjustment and downscaling","authors":"Jakub Śledziowski , Paweł Terefenko , Andrzej Giza , Kamran Tanwari , Dominik Paprotny","doi":"10.1016/j.softx.2025.102479","DOIUrl":"10.1016/j.softx.2025.102479","url":null,"abstract":"<div><div>Modern climate impact and attribution science requires timely, high-resolution meteorological and hydrological data. The CLIMB workflow is an open-source framework integrating state-of-the-art datasets and methods for operational generation of high-resolution climate datasets tailored for attribution studies of floods, droughts, heatwaves, and other extremes. We show that global climate reanalysis can be efficiently bias-adjusted and downscaled, and further converted into readily-usable climate indicators. The choice of variables and formatting of the data enables direct application in hydrological models. The workflow implements a fully scripted pipeline that can be automated via cron scheduling, providing daily meteorological outputs. We show an application of the workflow for operational monitoring weather extremes in Poland.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102479"},"PeriodicalIF":2.4,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1016/j.softx.2025.102470
Iztok Fister Jr , Gerlinde Emsenhuber , Jan Hendrik Plümer , Iztok Fister , Andreas Holzinger
Numerical association rule mining remains comparatively underexplored in interpretable machine learning, largely due to the challenges of handling continuous variables and the limited availability of effective visualization techniques. We introduce niarules, an open-source R package that provides a complete and extensible pipeline for numerical association rule mining, complemented by advanced post-processing and interactive 3D visualization. The package integrates bio-inspired optimization-based rule mining methods within a modular architecture that encompasses data preprocessing, rule mining, and visualization. A novel radial layout engine, implemented in C++, generates Coral Plots, which depict rules sharing a common consequent as radial trees. This design facilitates intuitive exploration of antecedent specificity, alongside key quality measures such as support, confidence, and lift. By combining methodological innovation with user-friendly visualization, niarules lowers the entry barrier to numerical association rule mining and supports the development of explainable AI systems for numerical datasets.
{"title":"niarules: Advancing interpretable machine learning through numerical association rule mining and 3D coral plot visualization","authors":"Iztok Fister Jr , Gerlinde Emsenhuber , Jan Hendrik Plümer , Iztok Fister , Andreas Holzinger","doi":"10.1016/j.softx.2025.102470","DOIUrl":"10.1016/j.softx.2025.102470","url":null,"abstract":"<div><div>Numerical association rule mining remains comparatively underexplored in interpretable machine learning, largely due to the challenges of handling continuous variables and the limited availability of effective visualization techniques. We introduce <span>niarules</span>, an open-source R package that provides a complete and extensible pipeline for numerical association rule mining, complemented by advanced post-processing and interactive 3D visualization. The package integrates bio-inspired optimization-based rule mining methods within a modular architecture that encompasses data preprocessing, rule mining, and visualization. A novel radial layout engine, implemented in C++, generates Coral Plots, which depict rules sharing a common consequent as radial trees. This design facilitates intuitive exploration of antecedent specificity, alongside key quality measures such as support, confidence, and lift. By combining methodological innovation with user-friendly visualization, <span>niarules</span> lowers the entry barrier to numerical association rule mining and supports the development of explainable AI systems for numerical datasets.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102470"},"PeriodicalIF":2.4,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.softx.2025.102463
Damian Frąszczak, Edyta Frąszczak
Website phishing represents a significant cyber threat, where attackers create fraudulent websites that imitate legitimate sites to deceive users. Continuous monitoring and detection of malicious websites are crucial for mitigating this threat. This paper introduces PhishingWebCollector, an open-source Python library designed to simplify the collection and integration of phishing feeds. It is an appropriate tool for real-time blacklist updates, creating historical datasets for research, and serving as a foundation for developing AI-based phishing detection systems. Identifying phishing and spoofed websites helps generate high-quality datasets necessary for training models in automated website classification and threat identification. Leveraging Python’s asyncio, it processes multiple feeds concurrently to achieve optimal performance. Available on PyPI with extensive documentation and examples, PhishingWebCollector offers a resource-efficient solution for cybersecurity professionals and researchers.
{"title":"PhishingWebCollector: Async python library for automated phishing feed collection","authors":"Damian Frąszczak, Edyta Frąszczak","doi":"10.1016/j.softx.2025.102463","DOIUrl":"10.1016/j.softx.2025.102463","url":null,"abstract":"<div><div>Website phishing represents a significant cyber threat, where attackers create fraudulent websites that imitate legitimate sites to deceive users. Continuous monitoring and detection of malicious websites are crucial for mitigating this threat. This paper introduces PhishingWebCollector, an open-source Python library designed to simplify the collection and integration of phishing feeds. It is an appropriate tool for real-time blacklist updates, creating historical datasets for research, and serving as a foundation for developing AI-based phishing detection systems. Identifying phishing and spoofed websites helps generate high-quality datasets necessary for training models in automated website classification and threat identification. Leveraging Python’s asyncio, it processes multiple feeds concurrently to achieve optimal performance. Available on PyPI with extensive documentation and examples, PhishingWebCollector offers a resource-efficient solution for cybersecurity professionals and researchers.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102463"},"PeriodicalIF":2.4,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.softx.2025.102478
Anastasia S. Saridou, Ioannis Kansizoglou, Athanasios P. Vavatsikos
“Spatial-CustSat” is a GIS-based package that includes three models aiming to extent customer satisfaction (CS) analysis to the spatial context using MUlticriteria Satisfaction Analysis (MUSA) methods. The first two models use spatial datasets to perform the -means algorithm and create homogeneous customer zones (clusters). The distinction between the two lies in the method of declaring the number of clusters. Supported by the MUSA method, CS analysis allows the identification of areas where the company's strengths and weaknesses lie. The latter model supports the implementation of CS benchmarking analysis for companies with store networks. Based on Walter's theory that customers shop at the nearest store, it identifies the service area of each store and implements the MUSAplus method. This option enables comparative performance analysis of the stores under evaluation.
{"title":"Spatial-CustSat: An opensource package for customer satisfaction analysis in GIS environment","authors":"Anastasia S. Saridou, Ioannis Kansizoglou, Athanasios P. Vavatsikos","doi":"10.1016/j.softx.2025.102478","DOIUrl":"10.1016/j.softx.2025.102478","url":null,"abstract":"<div><div>“Spatial-CustSat” is a GIS-based package that includes three models aiming to extent customer satisfaction (CS) analysis to the spatial context using MUlticriteria Satisfaction Analysis (MUSA) methods. The first two models use spatial datasets to perform the <span><math><mi>k</mi></math></span>-means algorithm and create homogeneous customer zones (clusters). The distinction between the two lies in the method of declaring the number of clusters. Supported by the MUSA method, CS analysis allows the identification of areas where the company's strengths and weaknesses lie. The latter model supports the implementation of CS benchmarking analysis for companies with store networks. Based on Walter's theory that customers shop at the nearest store, it identifies the service area of each store and implements the MUSAplus method. This option enables comparative performance analysis of the stores under evaluation.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102478"},"PeriodicalIF":2.4,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-04DOI: 10.1016/j.softx.2025.102462
Tianyu Wang , Xiaozhou He , Bernd R. Noack
The Downhill Simplex Method (DSM) is a fast-converging derivative-free optimization technique for nonlinear systems. However, the optimization process is often subject to premature convergence due to degenerate simplices or noise-induced spurious minima. This study introduces a software package for the robust Downhill Simplex Method (rDSM), which incorporates two key enhancements. First, simplex degeneracy is detected and corrected by volume maximization under constraints. Second, the real objective value of noisy problems is estimated by reevaluating the long-standing points. Thus, rDSM improves the convergence of DSM, and may increase the applicability of DSM to higher dimensions, even in the presence of noise. The rDSM software package thus provides a robust and efficient solution for both analytical and experimental optimization scenarios. This methodological advancement extends the applicability of simplex-based optimization to complex experimental systems where gradient information remains inaccessible and measurement noise proves non-negligible.
{"title":"rDSM—A robust Downhill Simplex Method software package for high-dimensional optimization problems","authors":"Tianyu Wang , Xiaozhou He , Bernd R. Noack","doi":"10.1016/j.softx.2025.102462","DOIUrl":"10.1016/j.softx.2025.102462","url":null,"abstract":"<div><div>The Downhill Simplex Method (DSM) is a fast-converging derivative-free optimization technique for nonlinear systems. However, the optimization process is often subject to premature convergence due to degenerate simplices or noise-induced spurious minima. This study introduces a software package for the robust Downhill Simplex Method (rDSM), which incorporates two key enhancements. First, simplex degeneracy is detected and corrected by volume maximization under constraints. Second, the real objective value of noisy problems is estimated by reevaluating the long-standing points. Thus, rDSM improves the convergence of DSM, and may increase the applicability of DSM to higher dimensions, even in the presence of noise. The rDSM software package thus provides a robust and efficient solution for both analytical and experimental optimization scenarios. This methodological advancement extends the applicability of simplex-based optimization to complex experimental systems where gradient information remains inaccessible and measurement noise proves non-negligible.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102462"},"PeriodicalIF":2.4,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-03DOI: 10.1016/j.softx.2025.102457
Carlos Sandoval Olascoaga , Nicholas de Monchaux
While architects and planners routinely rely on Geospatial Information Systems (GIS) and Computer Aided Design (CAD) tools, both types of tools are infrastructurally incompatible leading to cumbersome workarounds, lack of adoption in practice, and missed opportunities to incorporate the large-scale geographic insights of GIS with the building-scale precision of CAD into a seamless design process. Local Software (LS) inquires into how bringing together CAD and GIS tools and workflows can lead to more sustainable urban design proposals. The framework introduces Site Packages (SP), a cross-platform information model based on GeoJSON that enables seamless integration between design and analysis tools and a new design methodology that connects large scale modeling with small scale design decisions. LS provides a web interface and open-source plugins for Grasshopper and QGIS, that allow designers to parametrically generate networked urban interventions while evaluating their ecological and social impacts through GIS. Case studies have demonstrated that proposals created with the LS framework can replace 88–96 % of traditional stormwater systems at 50 % lower cost of underground work, while enhancing urban resilience, reducing heat island effects, and providing community benefits.
{"title":"Local software: Integrated design and geo-computing workflows for urban design","authors":"Carlos Sandoval Olascoaga , Nicholas de Monchaux","doi":"10.1016/j.softx.2025.102457","DOIUrl":"10.1016/j.softx.2025.102457","url":null,"abstract":"<div><div>While architects and planners routinely rely on Geospatial Information Systems (GIS) and Computer Aided Design (CAD) tools, both types of tools are infrastructurally incompatible leading to cumbersome workarounds, lack of adoption in practice, and missed opportunities to incorporate the large-scale geographic insights of GIS with the building-scale precision of CAD into a seamless design process. Local Software (LS) inquires into how bringing together CAD and GIS tools and workflows can lead to more sustainable urban design proposals. The framework introduces Site Packages (SP), a cross-platform information model based on GeoJSON that enables seamless integration between design and analysis tools and a new design methodology that connects large scale modeling with small scale design decisions. LS provides a web interface and open-source plugins for Grasshopper and QGIS, that allow designers to parametrically generate networked urban interventions while evaluating their ecological and social impacts through GIS. Case studies have demonstrated that proposals created with the LS framework can replace 88–96 % of traditional stormwater systems at 50 % lower cost of underground work, while enhancing urban resilience, reducing heat island effects, and providing community benefits.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"33 ","pages":"Article 102457"},"PeriodicalIF":2.4,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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