Collaborative Open Source Software Research Articles

The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

Agcounts: An R Package to Calculate ActiGraph Activity Counts From Portable Accelerometers

Portable accelerometers are used to capture physical activity in free-living individuals with the ActiGraph being one of the most widely used device brands in physical activity and health research. Recently, in February 2022, ActiGraph published their activity count algorithm and released a Python package for generating activity counts from raw acceleration data for five generations of ActiGraph devices. The nonproprietary derivation of the ActiGraph count improved the transparency and interpretation of accelerometer device-measured physical activity, but the Python release of the count algorithm does not integrate with packages developed by the physical activity research community using the R Statistical Programming Language. In this technical note, we describe our efforts to create an R-based translation of ActiGraph’s Python package with additional extensions to make data processing easier and faster for end users. We call the resulting R package agcounts and provide an inside look at its key functionalities and extensions while discussing its prospective impacts on collaborative open-source software development in physical behavior research. We recommend that device manufacturers follow ActiGraph’s lead by providing open-source access to their data processing algorithms and encourage physical activity researchers to contribute to the further development and refinement of agcounts and other open-source software.

Developing the Chinese Academic Map Publishing Platform

The discipline of the humanities has long been inseparable from the exploration of space and time. With the rapid advancement of digitization, databases, and data science, humanities research is making greater use of quantitative spatiotemporal analysis and visualization. In response to this trend, our team developed the Chinese academic map publishing platform (AMAP) with the aim of supporting the digital humanities from a Chinese perspective. In compiling materials mined from China’s historical records, AMAP attempts to reconstruct the geographical distribution of entities including people, activities, and events, using places to connect these historical objects through time. This project marks the beginning of the development of a comprehensive database and visualization system to support humanities scholarship in China, and aims to facilitate the accumulation of spatiotemporal datasets, support multi-faceted queries, and provide integrated visualization tools. The software itself is built on Harvard’s WorldMap codebase, with enhancements which include improved support for Asian projections, support for Chinese encodings, the ability to handle long text attributes, feature level search, and mobile application support. The goal of AMAP is to make Chinese historical data more accessible, while cultivating collaborative opensource software development.

Lifting Industrial Ecology Modeling to a New Level of Quality and Transparency: A Call for More Transparent Publications and a Collaborative Open Source Software Framework

SummaryIndustrial ecology (IE) is a maturing scientific discipline. The field is becoming more data and computation intensive, which requires IE researchers to develop scientific software to tackle novel research questions. We review the current state of software programming and use in our field and find challenges regarding transparency, reproducibility, reusability, and ease of collaboration. Our response to that problem is fourfold: First, we propose how existing general principles for the development of good scientific software could be implemented in IE and related fields. Second, we argue that collaborating on open source software could make IE research more productive and increase its quality, and we present guidelines for the development and distribution of such software. Third, we call for stricter requirements regarding general access to the source code used to produce research results and scientific claims published in the IE literature. Fourth, we describe a set of open source modules for standard IE modeling tasks that represent our first attempt at turning our recommendations into practice. We introduce a Python toolbox for IE that includes the life cycle assessment (LCA) framework Brightway2, the ecospold2matrix module that parses unallocated data in ecospold format, the pySUT and pymrio modules for building and analyzing multiregion input‐output models and supply and use tables, and the dynamic_stock_model class for dynamic stock modeling. Widespread use of open access software can, at the same time, increase quality, transparency, and reproducibility of IE research.

Making Deliberate Changes Possible in an Organizational Context of an Open Source Software Community

In a task-executing environment of self-assignment, tasks that are less challenging but still important (for the overall work) face a risk of not being delivered on-time or executed at all. Based on longitudinal qualitative data collected over a period of four years, we seek to answer how deliberate changes are accomplished in an actor-oriented and collaborative open source software (OSS) community context. Our study makes four contributions. First, deliberate changes are made possible by four mechanisms of governance: self-leadership, reputation transfer, social influence and task redesign. Second, the study shows that a meritocracy- based OSS career system does not necessarily restrict power exclusively to the holder of community reputation. Power may in fact be distributed by reputation transfer to another significant agent involved in the change process (e.g. the change agent). Third, our results show that the potential risk of task negligence following from the principle of self-assignment may be mit...

Biogem: an effective tool-based approach for scaling up open source software development in bioinformatics

Summary: Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices.Biogem, with its targeted modular and decentralized approach, software generator, tools and tight web integration, is an improved general model for scaling up collaborative open source software development in bioinformatics.Availability: Biogem and modules are free and are OSS. Biogem runs on all systems that support recent versions of Ruby, including Linux, Mac OS X and Windows. Further information at http://www.biogems.info. A tutorial is available at http://www.biogems.info/howto.htmlContact: bonnal@ingm.org

Health Informatics for Development: a Threepronged Strategy of Partnerships, Standards, and Mobile Health

Describe the issues surrounding health informatics in developing countries and the challenges faced by practitioners in building internal capacity. From these issues, the authors propose cost-effective strategies that can fast track health informatics development in these low to medium income countries (LMICs). The authors conducted a review of literature and consulted key opinion leaders who have experience with health informatics implementations around the world. Despite geographic and cultural differences, many LMICs share similar challenges and opportunities in developing health informatics. Partnerships, standards, and inter-operability are well known components of successful informatics programs. Establishing partnerships can be comprised of formal inter-institutional collaborations on training and research, collaborative open source software development, and effective use of social networking. Lacking legacy systems, LMICs can discuss standards and inter-operability more openly and have greater potential for success. Lastly, since cellphones are pervasive in developing countries, they can be leveraged as access points for delivering and documenting health services in remote under-served areas. Mobile health or mHealth gives LMICs a unique opportunity to leapfrog through most issues that have plagued health informatics in developed countries. By employing this proposed roadmap, LMICs can now develop capacity for health informatics using appropriate and cost-effective technologies.