scholarly journals Assessment of a livestock GPS collar based on an open-source datalogger informs best practices for logging intensity

2018 ◽  
Vol 8 (11) ◽  
pp. 5649-5660 ◽  
Author(s):  
Devan Allen McGranahan ◽  
Benjamin Geaumont ◽  
Jonathan W. Spiess
Keyword(s):  
Best Practices ◽  
Open Source ◽  
Gps Collar

Experiences Enhancing Open Source Security in the POSSE Project

2005 ◽  
pp. 242-258
Author(s):  
Jonathan M. Smith ◽  
Michael B. Greenwald ◽  
Sotiris Ioannidis ◽  
Angelos D. Keromytis ◽  
Ben Laurie ◽  
...  
Keyword(s):  
Best Practices ◽  
Open Source ◽  
Careful Study ◽  
Significant Acceleration ◽  
Secure Software ◽  
High Assurance ◽  
Open Source Systems

This chapter reports on our experiences with POSSE, a project studying “Portable Open Source Security Elements” as part of the larger DARPA effort on Composable High Assurance Trusted Systems. We describe the organization created to manage POSSE and the significant acceleration in producing widely used secure software that has resulted. POSSE’s two main goals were, first, to increase security in open source systems and, second, to more broadly disseminate security knowledge, “best practices,” and working code that reflects these practices. POSSE achieved these goals through careful study of systems (“audit”) and starting from a well-positioned technology base (OpenBSD). We hope to illustrate the advantages of applying OpenBSD-style methodology to secure, open-source projects, and the pitfalls of melding multiple open-source efforts in a single project.

scholarly journals Bionitio: demonstrating and facilitating best practices for bioinformatics command-line software

GigaScience ◽  
2019 ◽  
Vol 8 (9) ◽  
Author(s):  
Peter Georgeson ◽  
Anna Syme ◽  
Clare Sloggett ◽  
Jessica Chung ◽  
Harriet Dashnow ◽  
...  
Keyword(s):  
Best Practices ◽  
Software Development ◽  
Open Source ◽  
Open Source Software ◽  
Command Line ◽  
Use Of Resources ◽  
Excellent Starting Point ◽  
Starting Point ◽  
Bioinformatics Software ◽  
Programming Practices

Abstract Background Bioinformatics software tools are often created ad hoc, frequently by people without extensive training in software development. In particular, for beginners, the barrier to entry in bioinformatics software development is high, especially if they want to adopt good programming practices. Even experienced developers do not always follow best practices. This results in the proliferation of poorer-quality bioinformatics software, leading to limited scalability and inefficient use of resources; lack of reproducibility, usability, adaptability, and interoperability; and erroneous or inaccurate results. Findings We have developed Bionitio, a tool that automates the process of starting new bioinformatics software projects following recommended best practices. With a single command, the user can create a new well-structured project in 1 of 12 programming languages. The resulting software is functional, carrying out a prototypical bioinformatics task, and thus serves as both a working example and a template for building new tools. Key features include command-line argument parsing, error handling, progress logging, defined exit status values, a test suite, a version number, standardized building and packaging, user documentation, code documentation, a standard open source software license, software revision control, and containerization. Conclusions Bionitio serves as a learning aid for beginner-to-intermediate bioinformatics programmers and provides an excellent starting point for new projects. This helps developers adopt good programming practices from the beginning of a project and encourages high-quality tools to be developed more rapidly. This also benefits users because tools are more easily installed and consistent in their usage. Bionitio is released as open source software under the MIT License and is available at https://github.com/bionitio-team/bionitio.

scholarly journals Lesson Development for Open Source Software Best Practices Adoption

2018 ◽  
Author(s):  
Mateusz Kuzak ◽  
Jen Harrow ◽  
Rafael C. Jimenez ◽  
Paula Andrea Martinez ◽  
Fotis E. Psomopoulos ◽  
...  
Keyword(s):  
Best Practices ◽  
Open Source ◽  
Open Source Software ◽  
Lesson Development

scholarly journals Accurate, scalable cohort variant calls using DeepVariant and GLnexus

2020 ◽  
Author(s):  
Taedong Yun ◽  
Helen Li ◽  
Pi-Chuan Chang ◽  
Michael F. Lin ◽  
Andrew Carroll ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Best Practices ◽  
Open Source ◽  
Variant Calling ◽  
Cost Savings ◽  
Quality Improvements ◽  
1000 Genomes Project ◽  
Genetic Analyses ◽  
1000 Genomes ◽  
Population Scale

AbstractPopulation-scale sequenced cohorts are foundational resources for genetic analyses, but processing raw reads into analysis-ready variants remains challenging. Here we introduce an open-source cohort variant-calling method using the highly-accurate caller DeepVariant and scalable merging tool GLnexus. We optimized callset quality based on benchmark samples and Mendelian consistency across many sample sizes and sequencing specifications, resulting in substantial quality improvements and cost savings over existing best practices. We further evaluated our pipeline in the 1000 Genomes Project (1KGP) samples, showing superior quality metrics and imputation performance. We publicly release the 1KGP callset to foster development of broad studies of genetic variation.

scholarly journals TeachOpenCADD 2021: Open Source and FAIR Python Pipelines to Assist in Structural Bioinformatics and Cheminformatics Research

2021 ◽  
Author(s):  
Dominique Sydow ◽  
Jaime Rodríguez-Guerra ◽  
Talia B. Kimber ◽  
David Schaller ◽  
Corey J. Taylor ◽  
...  
Keyword(s):  
Best Practices ◽  
Open Source ◽  
Theoretical Background ◽  
Structural Bioinformatics ◽  
Research Projects ◽  
Domain Specific ◽  
Modern Drug ◽  
Hands On ◽  
Novice Scientists ◽  
Crucial Part

Computational pipelines have become a crucial part of modern drug discovery campaigns. Setting up and maintaining such pipelines, however, can be challenging and time-consuming --- especially for novice scientists in this domain. TeachOpenCADD is a platform that aims to teach domain-specific skills and to provide pipeline templates as starting points for research projects. We offer Python-based solutions for common tasks in cheminformatics and structural bioinformatics in the form of Jupyter notebooks and based on open source resources only. Including the 12 newly released additions, TeachOpenCADD now contains 22 notebooks that each cover both theoretical background as well as hands-on programming. To promote reproducible and reusable research, we apply software best practices to our notebooks such as testing with an automated continuous integration and adhering to a more idiomatic Python style. The new TeachOpenCADD website is available at https://projects.volkamerlab.org/teachopencadd and all code is deposited on GitHub.

scholarly journals Afterword: Novel Knowledge, or Cleansing Dirty Data: Toward Open-Source Histories of the Novel

2021 ◽  
pp. 351-370
Author(s):  
Emily C. Friedman
Keyword(s):  
Best Practices ◽  
Open Source ◽  
Data Visualization ◽  
Small Scale ◽  
The Novel ◽  
Collective Knowledge ◽  
Dirty Data

AbstractThis afterword discusses the most important, most under-rewarded, and most unsexy aspect of data visualization: the production and use of reliable underlying data. Starting from the premise that visualizations are only as good as their underlying evidentiary base, Freidman addresses the contributions of digital projects that have laid the foundation for such practices, including massive multi-institution projects like Orlando, mid-sized projects like The Early Novels Database (END), and the author’s own small-scale project, Manuscript Fiction in the Age of Print (MFAP). Following this assessment, the author proposes a set of guidelines for best practices in creating new data so that amendable, transformable visualizations can be produced, built on collective knowledge.

Best Practices for Teaching and Designing a Pure Online Science Classroom

2010 ◽  
pp. 291-313
Author(s):  
Ricardo Javier Rademacher Mena
Keyword(s):  
Higher Education ◽  
Education Research ◽  
Best Practices ◽  
Open Source ◽  
Physics Education ◽  
Science Classroom ◽  
Science Class ◽  
Teaching Online ◽  
Science Courses ◽  
Teaching Physics

With the modification of the 50/50 rule by the Higher Education Reconciliation Act of 2005, the purely online university has become increasingly popular and thus so has the purely online science class. In this chapter, the author will use over a decade of teaching physics and math at traditional offline and pure online universities to compare the two. In the process, the author will uncover what techniques have successfully carried over from the traditional to the online environment and how physics education research and technology are changing the physics classroom. The main purpose of this chapter is to identify best practices in designing and teaching online science courses and to provide recommendations on improving existing online science classrooms. Throughout the chapter, Moodle™, an open source LMS, will be used to showcase and implement the ideas being presented.

Using Video and Web Conferencing Tools to Support Online Learning

2013 ◽  
pp. 149-165 ◽  
Author(s):  
Paula Jones ◽  
Fred Kolloff ◽  
MaryAnn Kolloff
Keyword(s):  
Online Learning ◽  
Best Practices ◽  
Open Source ◽  
Online Courses ◽  
Web Conferencing ◽  
Software Programs ◽  
The Impact ◽  
Do So

This chapter examines effective methods for using video and web conferencing tools to support online learning. The authors discuss the concept of presence, how web conferencing can be used to support presence in online courses, and why it is important to do so. Because of the impact web conferencing can have in learning, this chapter explores a variety of teaching roles that best leverage these conferencing tools. The chapter includes information on various web conferencing software programs (paid and open source). Best practices for using web conferencing tools in online learning are also explored.

Raiders of the Lost Code: Preserving the MOSS Codebase - Significance, Status, Challenges and Opportunities 

2021 ◽  
Author(s):  
Peter Löwe ◽  
Māris Nartišs ◽  
Carl N Reed
Keyword(s):  
Best Practices ◽  
Open Source ◽  
Economic Research ◽  
Current Status ◽  
Colorado State University ◽  
Challenges And Opportunities ◽  
Open Source Gis ◽  
Long Term Preservation ◽  
The U.S

<p>We report on the current status of the software repository of the Map Overlay and Statistical System (MOSS) and upcoming actions to ensure long term preservation of the codebase as a historic geospatial source. MOSS is the earliest known open source Geographic Information System (GIS). Active development of the vector-based interactive GIS by the U.S. Department of Interior began in 1977 on a CDC mainframe computer located at Colorado State University. Development continued until 1985 with MOSS being ported to multiple platforms, including DG-AOS, UNIX, VMS and Microsoft DOS. Many geospatial programming techniques and functionalities were first implemented in MOSS, including a fully interactive user interface and integrated vector and raster processing. The public availability of the WWW in the early 1990s sparked a growth of new Open Source GIS projects, which led to the formation of the Open Source Geospatial Foundation (OSGeo). The goal of OSGeo is to support and promote the collaborative development of open geospatial technologies and data. This includes best practices for project management and repositories for codebases. From its start, OSGeo recognised MOSS as the original forerunner project. After the decline of active use of MOSS since the 1990s, the U.S. Bureau of Land Management (BLM) continued to provide the open source MOSS codebase on an FTP-Server, which allowed use, analysis and reference by URL. This service was discontinued at some point before 2018, which was eventually discovered due to a broken URL link. This led to a global search and rescue effort among the OSGeo communities to track down remaining offline copies of the codebase. In mid 2020 a surviving copy of the MOSS codebase was discovered at the University of Latvia, which is temporarily preserved at the German Institute of Economic Research (DIW Berlin). OSGeo has agreed to make MOSS the first OSGeo Heritage Project to ensure long term preservation in a OSGeo code repository. This is a significant first step to enable MOSS-related research based on the FAIR (Findable, Accessible, Interoperable, Reusable) paradigm. Follow up actions will be required to enable scientific citation and credit by persistent identifiers for code and persons, such as Digital Object Identifiers (DOI) and Open Researcher Contributor Identification Initiative-ID (ORCID-ID) within the OSGeo repository environment. This will advance the OSGeo portfolio of best practices also for other open geospatial projects.</p><p> </p>

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