C. Kadow, S. Illing, E. Lucio-Eceiza, M. Bergemann, Mahesh Ramadoss, P. Sommer, Oliver Kunst, T. Schartner, K. Pankatz, J. Grieger, M. Schuster, Andy Richling, H. Thiemann, I. Kirchner, H. Rust, T. Ludwig, U. Cubasch, U. Ulbrich
Freva – Free Evaluation System Framework for Earth system modeling is an efficient solution to handle evaluation systems of research projects, institutes or universities in the climate community. It is a scientific software framework for high performance computing that provides all its available features both in a shell and web environment. The main system design is equipped with the programming interface, history of evaluations, and a standardized model database. Plugin – a generic application programming interface allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language. History – the configuration sub-system stores every analysis performed with the evaluation system in a database. Databrowser – an implemented meta data system with its advanced but easy-to-handle search tool supports scientists and their plugins to retrieve the required information of the database. The combination of these three core components, increases the scientific outcome and enables transparency and reproducibility for research groups using Freva as their framework for evaluation of Earth system models.
{"title":"Introduction to Freva – A Free Evaluation System Framework for Earth System Modeling","authors":"C. Kadow, S. Illing, E. Lucio-Eceiza, M. Bergemann, Mahesh Ramadoss, P. Sommer, Oliver Kunst, T. Schartner, K. Pankatz, J. Grieger, M. Schuster, Andy Richling, H. Thiemann, I. Kirchner, H. Rust, T. Ludwig, U. Cubasch, U. Ulbrich","doi":"10.5334/JORS.253","DOIUrl":"https://doi.org/10.5334/JORS.253","url":null,"abstract":"Freva – Free Evaluation System Framework for Earth system modeling is an efficient solution to handle evaluation systems of research projects, institutes or universities in the climate community. It is a scientific software framework for high performance computing that provides all its available features both in a shell and web environment. The main system design is equipped with the programming interface, history of evaluations, and a standardized model database. Plugin – a generic application programming interface allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language. History – the configuration sub-system stores every analysis performed with the evaluation system in a database. Databrowser – an implemented meta data system with its advanced but easy-to-handle search tool supports scientists and their plugins to retrieve the required information of the database. The combination of these three core components, increases the scientific outcome and enables transparency and reproducibility for research groups using Freva as their framework for evaluation of Earth system models.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46776049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
FastGAPP (Fast Geoscientific Analyses Plotting Program) is a MATLAB-based graphical user interface. It is developed to quickly explore and interpret geochemical major and trace element analyses of igneous rocks in over 100 published classification and discrimination plots, variation diagrams and normalised rare-earth element and multi-elements plots. All plots can be modified (fonts, lines, frame etc.) to produce publication-ready and high-quality raster or vector graphics. Among geochemical analyses of magmatic rocks, several other sub-programs are integrated to display petrographic analyses of igneous rocks, composition and grain size analyses of sedimentary rocks, and grain size analyses of soils. FastGAPP also provides several tools to support data handling, to extend the integrated geochemical databases and/or even create new sub-programs for different fields of geosciences. FastGAPP v2.0 is available on GitHub and Zenodo. CORRESPONDING AUTHOR: Florian Riefstahl University of Bremen, Department 5 Geosciences, Bremen, Germany; Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany; Now at: Landesamt für Geologie und Bergwesen Sachsen-Anhalt, Halle, Germany f.riefstahl@outlook.com
{"title":"FastGAPP – A MATLAB-Based Program Supports Earth Scientists Interpreting Geochemical, Petrological and Sedimentological Data","authors":"F. Riefstahl, F. Gross","doi":"10.5334/JORS.333","DOIUrl":"https://doi.org/10.5334/JORS.333","url":null,"abstract":"FastGAPP (Fast Geoscientific Analyses Plotting Program) is a MATLAB-based graphical user interface. It is developed to quickly explore and interpret geochemical major and trace element analyses of igneous rocks in over 100 published classification and discrimination plots, variation diagrams and normalised rare-earth element and multi-elements plots. All plots can be modified (fonts, lines, frame etc.) to produce publication-ready and high-quality raster or vector graphics. Among geochemical analyses of magmatic rocks, several other sub-programs are integrated to display petrographic analyses of igneous rocks, composition and grain size analyses of sedimentary rocks, and grain size analyses of soils. FastGAPP also provides several tools to support data handling, to extend the integrated geochemical databases and/or even create new sub-programs for different fields of geosciences. FastGAPP v2.0 is available on GitHub and Zenodo. CORRESPONDING AUTHOR: Florian Riefstahl University of Bremen, Department 5 Geosciences, Bremen, Germany; Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany; Now at: Landesamt für Geologie und Bergwesen Sachsen-Anhalt, Halle, Germany f.riefstahl@outlook.com","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45383590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PIVlab is a free toolbox and app for MATLAB ® . It is used to perform Particle Image Velocimetry (PIV) with image data: A light sheet illuminates particles that are suspended in a fluid. A digital camera records a series of images of the illuminated particles. The input images are divided into sub-images (interrogation areas), and for each of these, a cross-correlation is performed. The resulting correlation matrix is used to estimate the most probable displacement within each interrogation area. PIV is extensively used for flow analyses where a thin laser sheet illuminates suspended particles in the fluid, but also for other moving textures, like cell migration or ultrasonic images. This paper presents several improvements that were implemented in PIVlab, enhancing the robustness of displacement estimates. The benefit of these improvements is evaluated using experimental images and synthetic images of particle and non-particle textures. Linear correlation and repeated correlation increase the robustness and decrease bias and root-mean-square (RMS) error of the displacement estimates. Particle images have a significantly lower bias and RMS error than non-particle images.
{"title":"Particle Image Velocimetry for MATLAB: Accuracy and enhanced algorithms in PIVlab","authors":"William Thielicke, René Sonntag","doi":"10.5334/JORS.334","DOIUrl":"https://doi.org/10.5334/JORS.334","url":null,"abstract":"PIVlab is a free toolbox and app for MATLAB ® . It is used to perform Particle Image Velocimetry (PIV) with image data: A light sheet illuminates particles that are suspended in a fluid. A digital camera records a series of images of the illuminated particles. The input images are divided into sub-images (interrogation areas), and for each of these, a cross-correlation is performed. The resulting correlation matrix is used to estimate the most probable displacement within each interrogation area. PIV is extensively used for flow analyses where a thin laser sheet illuminates suspended particles in the fluid, but also for other moving textures, like cell migration or ultrasonic images. This paper presents several improvements that were implemented in PIVlab, enhancing the robustness of displacement estimates. The benefit of these improvements is evaluated using experimental images and synthetic images of particle and non-particle textures. Linear correlation and repeated correlation increase the robustness and decrease bias and root-mean-square (RMS) error of the displacement estimates. Particle images have a significantly lower bias and RMS error than non-particle images.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43610687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Madden-Julian Oscillation (MJO) is a prominent feature of the intraseasonal variability of the atmosphere. The MJO strongly modulates tropical precipitation and has implications around the globe for weather, climate and basic atmospheric research. The time-dependent state of the MJO is described by MJO indices, which are calculated through sometimes complicated statistical approaches from meteorological variables. One of these indices is the OLR-based MJO Index (OMI; OLR stands for outgoing longwave radiation). The Python package mjoindices, which is described in this paper, provides the first open source implementation of the OMI algorithm, to our knowledge. The package meets state-of-the-art criteria for sustainable research software, like automated tests and a persistent archiving to aid the reproducibility of scientific results. The agreement of the OMI values calculated with this package and the original OMI values is also summarized here. There are several reuse scenarios; the most probable one is MJO-related research based on atmospheric models, since the index values have to be recalculated for each model run.
{"title":"A Python Package to Calculate the OLR-Based Index of the Madden-Julian-Oscillation (OMI) in Climate Science and Weather Forecasting","authors":"C. Hoffmann, G. Kiladis, M. Gehne, C. von Savigny","doi":"10.5334/JORS.331","DOIUrl":"https://doi.org/10.5334/JORS.331","url":null,"abstract":"The Madden-Julian Oscillation (MJO) is a prominent feature of the intraseasonal variability of the atmosphere. The MJO strongly modulates tropical precipitation and has implications around the globe for weather, climate and basic atmospheric research. The time-dependent state of the MJO is described by MJO indices, which are calculated through sometimes complicated statistical approaches from meteorological variables. One of these indices is the OLR-based MJO Index (OMI; OLR stands for outgoing longwave radiation). The Python package mjoindices, which is described in this paper, provides the first open source implementation of the OMI algorithm, to our knowledge. The package meets state-of-the-art criteria for sustainable research software, like automated tests and a persistent archiving to aid the reproducibility of scientific results. The agreement of the OMI values calculated with this package and the original OMI values is also summarized here. There are several reuse scenarios; the most probable one is MJO-related research based on atmospheric models, since the index values have to be recalculated for each model run.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44954282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pymrio is an open source tool for Environmentally Extended Multi-Regional Input-Output (EE MRIO) analysis developed in Python. It provides a high-level abstraction layer for global EE MRIO databases in order to simplify common EE MRIO data tasks. Among others, Pymrio includes parsers for several openly available EE MRIO databases (EXIOBASE v1 – v3, WIOD, Eora26, OECD-ICIO) as well as methods for production and consumption based accounts calculation, aggregation, stressor origin estimation and visualization. The use of a consistent storage format including meta data and modification history for MRIOs allows to exchange data with other analysis tools, aiming for an increased interoperability of Industrial Ecology analysis software.
{"title":"Pymrio – A Python Based Multi-Regional Input-Output Analysis Toolbox","authors":"Konstantin Stadler","doi":"10.5334/JORS.251","DOIUrl":"https://doi.org/10.5334/JORS.251","url":null,"abstract":"Pymrio is an open source tool for Environmentally Extended Multi-Regional Input-Output (EE MRIO) analysis developed in Python. It provides a high-level abstraction layer for global EE MRIO databases in order to simplify common EE MRIO data tasks. Among others, Pymrio includes parsers for several openly available EE MRIO databases (EXIOBASE v1 – v3, WIOD, Eora26, OECD-ICIO) as well as methods for production and consumption based accounts calculation, aggregation, stressor origin estimation and visualization. The use of a consistent storage format including meta data and modification history for MRIOs allows to exchange data with other analysis tools, aiming for an increased interoperability of Industrial Ecology analysis software.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47429944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this article is to describe an open-source application (Vifeco) that makes it possible to manually identify features on a video. Vifeco also allows to: manage the number of users, create a category (feature) and a collection of categories, read video and identify the features on it, and analyze the counting concordance between two users. Written in Java 11 with the JavaFX UI toolkit, Vifeco is a stand-alone, multiplatform (Windows, Mac and Linux) and multi-language (3 languages supported) application. The software is available under Apache Licence on GitHub ( https://github. com/LAEQ/vifeco ).
{"title":"VIFECO: An Open-Source Software for Counting Features on a Video","authors":"P. Apparicio, David Maignan, Jérémy Gelb","doi":"10.5334/JORS.300","DOIUrl":"https://doi.org/10.5334/JORS.300","url":null,"abstract":"The aim of this article is to describe an open-source application (Vifeco) that makes it possible to manually identify features on a video. Vifeco also allows to: manage the number of users, create a category (feature) and a collection of categories, read video and identify the features on it, and analyze the counting concordance between two users. Written in Java 11 with the JavaFX UI toolkit, Vifeco is a stand-alone, multiplatform (Windows, Mac and Linux) and multi-language (3 languages supported) application. The software is available under Apache Licence on GitHub ( https://github. com/LAEQ/vifeco ).","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47658616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"oemof.tabular – Introducing Data Packages for Reproducible Workflows in Energy System Modeling","authors":"S. Hilpert, Stephan Günther, M. Söthe","doi":"10.5334/JORS.320","DOIUrl":"https://doi.org/10.5334/JORS.320","url":null,"abstract":"","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49352661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"PBTK Optimizer: An Open Source Application for PBTK Model Parameter Optimization in Python","authors":"Ian Edhlund, M. Macauley, Cindy Lee","doi":"10.5334/JORS.285","DOIUrl":"https://doi.org/10.5334/JORS.285","url":null,"abstract":"","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43216204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ExpressInHost (https://gitlab.com/a.raguin/expressinhost) is a GTK/C++ based user friendly graphical interface that allows tuning the codon sequence of an mRNA for recombinant protein expression in a host microorganism. Heterologous gene expression is widely implemented in biotechnology companies and academic research laboratories. However, expression of recombinant proteins can be challenging. On the one hand, maximising translation speed is important, especially in scalable production processes relevant to biotechnology companies, but on the other hand, solubility problems often arise as a consequence, since translation"pauses"might be key to allow the nascent polypeptide chain to fold appropriately. To address this challenge, we have developed a software that offers three distinct modes to tune codon sequences using the genetic code redundancy. The tuning strategies implemented take into account the specific tRNA resources of the host and that of the native organism. They balance rapid translation and native speed mimicking, which might be important to allow proper protein folding, thereby avoiding protein solubility problems.
{"title":"ExpressInHost: A Codon Tuning Tool for the Expression of Recombinant Proteins in Host Microorganisms","authors":"Adélaïde Raguin, I. Stansfield, M. Carmen Romano","doi":"10.5334/jors.385","DOIUrl":"https://doi.org/10.5334/jors.385","url":null,"abstract":"ExpressInHost (https://gitlab.com/a.raguin/expressinhost) is a GTK/C++ based user friendly graphical interface that allows tuning the codon sequence of an mRNA for recombinant protein expression in a host microorganism. Heterologous gene expression is widely implemented in biotechnology companies and academic research laboratories. However, expression of recombinant proteins can be challenging. On the one hand, maximising translation speed is important, especially in scalable production processes relevant to biotechnology companies, but on the other hand, solubility problems often arise as a consequence, since translation\"pauses\"might be key to allow the nascent polypeptide chain to fold appropriately. To address this challenge, we have developed a software that offers three distinct modes to tune codon sequences using the genetic code redundancy. The tuning strategies implemented take into account the specific tRNA resources of the host and that of the native organism. They balance rapid translation and native speed mimicking, which might be important to allow proper protein folding, thereby avoiding protein solubility problems.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46929927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"OpenOpticalFlow_PIV: An Open Source Program Integrating Optical Flow Method with Cross-Correlation Method for Particle Image Velocimetry","authors":"Tianshu Liu, D. Salazar","doi":"10.5334/JORS.326","DOIUrl":"https://doi.org/10.5334/JORS.326","url":null,"abstract":"","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44178375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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