Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Bertha: Project skeleton for scientific software.

ABSTRACT: Science depends heavily on reliable and easy-to-use software packages, such as mathematical libraries or data analysis tools. Developing such packages requires a lot of effort, which is too often avoided due to the lack of funding or recognition. In order to reduce the efforts required to create sustainable software packages, we present a project skeleton that ensures the best software engineering practices from the start of a project, or serves as reference for existing projects.

SUBMITTER: Riesch M

PROVIDER: S-EPMC7089539 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

bertha: Project skeleton for scientific software.

Riesch Michael M Nguyen Tien Dat TD Jirauschek Christian C

PloS one 20200323 3

Science depends heavily on reliable and easy-to-use software packages, such as mathematical libraries or data analysis tools. Developing such packages requires a lot of effort, which is too often avoided due to the lack of funding or recognition. In order to reduce the efforts required to create sustainable software packages, we present a project skeleton that ensures the best software engineering practices from the start of a project, or serves as reference for existing projects. ...[more]

PMID: 32203531

Similar Datasets

Rampant software errors may undermine scientific results.

Project description:The opportunities for both subtle and profound errors in software and data management are boundless, yet they remain surprisingly underappreciated. Here I estimate that any reported scientific result could very well be wrong if data have passed through a computer, and that these errors may remain largely undetected. It is therefore necessary to greatly expand our efforts to validate scientific software and computed results.

| S-EPMC4629271 | biostudies-literature

Dissemination of scientific software with Galaxy ToolShed.

Project description:The proliferation of web-based integrative analysis frameworks has enabled users to perform complex analyses directly through the web. Unfortunately, it also revoked the freedom to easily select the most appropriate tools. To address this, we have developed Galaxy ToolShed.

| S-EPMC4038738 | biostudies-literature

Software Framework for Controlling Unsupervised Scientific Instruments.

Project description:Science outreach and communication are gaining more and more importance for conveying the meaning of today's research to the general public. Public exhibitions of scientific instruments can provide hands-on experience with technical advances and their applications in the life sciences. The software of such devices, however, is oftentimes not appropriate for this purpose. In this study, we describe a software framework and the necessary computer configuration that is well suited for exposing a complex self-built and software-controlled instrument such as a microscope to laymen under limited supervision, e.g. in museums or schools. We identify several aspects that must be met by such software, and we describe a design that can simultaneously be used to control either (i) a fully functional instrument in a robust and fail-safe manner, (ii) an instrument that has low-cost or only partially working hardware attached for illustration purposes or (iii) a completely virtual instrument without hardware attached. We describe how to assess the educational success of such a device, how to monitor its operation and how to facilitate its maintenance. The introduced concepts are illustrated using our software to control eduSPIM, a fluorescent light sheet microscope that we are currently exhibiting in a technical museum.

| S-EPMC5003368 | biostudies-literature

Software engineering for scientific big data analysis.

Project description:The increasing complexity of data and analysis methods has created an environment where scientists, who may not have formal training, are finding themselves playing the impromptu role of software engineer. While several resources are available for introducing scientists to the basics of programming, researchers have been left with little guidance on approaches needed to advance to the next level for the development of robust, large-scale data analysis tools that are amenable to integration into workflow management systems, tools, and frameworks. The integration into such workflow systems necessitates additional requirements on computational tools, such as adherence to standard conventions for robustness, data input, output, logging, and flow control. Here we provide a set of 10 guidelines to steer the creation of command-line computational tools that are usable, reliable, extensible, and in line with standards of modern coding practices.

| S-EPMC6532757 | biostudies-literature

Unit Tests of Scientific Software: A Study on SWMM

Project description:Testing helps assure software quality by executing program and uncovering bugs. Scientific software developers often find it challenging to carry out systematic and automated testing due to reasons like inherent model uncertainties and complex floating point computations. We report in this paper a manual analysis of the unit tests written by the developers of the Storm Water Management Model (SWMM). The results show that the 1,458 SWMM tests have a 54.0% code coverage and a 82.4% user manual coverage. We also observe a “getter-setter-getter” testing pattern from the SWMM unit tests. Based on these results, we offer insights to improve test development and coverage.

| S-EPMC7304759 | biostudies-literature

Channeling Community Contributions to Scientific Software: A Sprint Experience.

Project description:In 2014, the khmer software project participated in a two-day global sprint coordinated by the Mozilla Science Lab. We offered a mentored experience in contributing to a scientific software project for anyone who was interested. We provided entry-level tasks and worked with contributors as they worked through our development process. The experience was successful on both a social and a technical level, bringing in 13 contributions from 9 new contributors and validating our development process. In this experience paper we describe the sprint preparation and process, relate anecdotal experiences, and draw conclusions about what other projects could do to enable a similar outcome. The khmer software is developed openly at http://github.com/dib-lab/khmer/.

| S-EPMC5104275 | biostudies-other

Scientific data from precipitation driver response model intercomparison project.

Project description:This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth's radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.

| S-EPMC8967886 | biostudies-literature

Knowledge reuse in software projects: Retrieving software development Q&A posts based on project task similarity.

Project description:Software developers need to cope with a massive amount of knowledge throughout the typical life cycle of modern projects. This knowledge includes expertise related to the software development phases (e.g., programming, testing) using a wide variety of methods and tools, including development methodologies (e.g., waterfall, agile), software tools (e.g., Eclipse), programming languages (e.g., Java, SQL), and deployment strategies (e.g., Docker, Jenkins). However, there is no explicit integration of these various types of knowledge with software development projects so that developers can avoid having to search over and over for similar and recurrent solutions to tasks and reuse this knowledge. Specifically, Q&A sites such as Stack Overflow are used by developers to share software development knowledge through posts published in several categories, but there is no link between these posts and the tasks developers perform. In this paper, we present an approach that (i) allows developers to associate project tasks with Stack Overflow posts, and (ii) recommends which Stack Overflow posts might be reused based on task similarity. We analyze an industry dataset, which contains project tasks associated with Stack Overflow posts, looking for the similarity of project tasks that reuse a Stack Overflow post. The approach indicates that when a software developer is performing a task, and this task is similar to another task that has been associated with a post, the same post can be recommended to the developer and possibly reused. We believe that this approach can significantly advance the state of the art of software knowledge reuse by supporting novel knowledge-project associations.

| S-EPMC7745967 | biostudies-literature

Better together: Elements of successful scientific software development in a distributed collaborative community.

Project description:Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities.

| S-EPMC7197760 | biostudies-literature

The SoftWipe tool and benchmark for assessing coding standards adherence of scientific software.

Project description:Scientific software from all areas of scientific research is pivotal to obtaining novel insights. Yet the coding standards adherence of scientific software is rarely assessed, even though it might lead to incorrect scientific results in the worst case. Therefore, we have developed an open source tool and benchmark called SoftWipe, that provides a relative software coding standards adherence ranking of 48 computational tools from diverse research areas. SoftWipe can be used in the review process of software papers and to inform the scientific software selection process.

| S-EPMC8113446 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data