Related papers: Towards FAIR Principles for Open Hardware
In the age of big data, it is important for primary research data to follow the FAIR principles of findability, accessibility, interoperability, and reusability. Data harmonization enhances interoperability and reusability by aligning…
The Open Access Movement has been striving to grant universal unrestricted access to the knowledge and data outputs of publicly funded research. leveraging the real time, virtually cost free publishing opportunities offered by the internet…
The openCost project aims to enhance transparency in research funding by making publication-related costs publicly accessible, following FAIR principles. It introduces a metadata schema for cost data, allowing aggregation and analysis…
Our analysis of recent AI4H publications reveals that, despite a trend toward utilizing open datasets and sharing modeling code, 74% of AI4H papers still rely on private datasets or do not share their code. This is especially concerning in…
Context: Fairness in systems has emerged as a critical concern in software engineering, garnering increasing attention as the field has advanced in recent years. While several guidelines have been proposed to address fairness, achieving a…
Voice biomarkers--human-generated acoustic signals such as speech, coughing, and breathing--are promising tools for scalable, non-invasive detection and monitoring of mental health and neurodegenerative diseases. Yet, their clinical…
Open Source Software (OSS) has been widely used in the educational environment largely due to its reduced cost of ownership. While OSS has evolved over the years, challenges exist in its implementation and wide adoption. Foremost among…
The rapid growth of AI in robotics has amplified the need for high-quality, reusable datasets, particularly in human-robot interaction (HRI) and AI-embedded robotics. While more robotics datasets are being created, the landscape of open…
One of the most important goals of digital humanities is to provide researchers with data and tools for new research questions, either by increasing the scale of scholarly studies, linking existing databases, or improving the accessibility…
Context: Software-intensive organizations' rationale for sharing Open Source Software (OSS) may be driven by both idealistic, strategic and commercial objectives, and include both monetary as well as non-monetary benefits. To gain the…
Data makes science possible. Sharing data improves visibility, and makes the research process transparent. This increases trust in the work, and allows for independent reproduction of results. However, a large proportion of data from…
With the increased interest in computational sciences, machine learning (ML), pattern recognition (PR) and big data, governmental agencies, academia and manufacturers are overwhelmed by the constant influx of new algorithms and techniques…
Software systems are increasingly making decisions on behalf of humans, raising concerns about the fairness of such decisions. Such concerns are usually attributed to flaws in algorithmic design or biased data, but we argue that they are…
Today's online platforms heavily lean on algorithmic recommendations for bolstering user engagement and driving revenue. However, these recommendations can impact multiple stakeholders simultaneously -- the platform, items (sellers), and…
We developed a system to run quick analyses of Cherenkov data in compliance with the FAIR Guiding Principles for scientific data management (FAIR: Findable, Accessible, Interoperable and Reusable), through the use of interoperability…
It is widely recognised nowadays that there is no single, accepted, unified definition of Open Science, which motivates our proposal of an Open Science definition as a political and legal framework where research outputs are shared and…
The widespread adoption of open source libraries and frameworks can be attributed to their licensing. Open Source Software Licenses (OSS licenses) ensure that software can be sold or distributed as part of aggregate programs from various…
Although it is possible to increase confidence in Free and Open Source Software (FOSS) by reviewing its source code, trusting code is not the same as trusting its executable counterparts. These are typically built and distributed by…
AI development is embracing open-source paradigm, but the fundamental distinction between AI models and traditional software artifacts may lead to a divergent open-source development paradigm with different collaborative practices, which…
Public availability and tracability of results from publically-funded work is a topic that gets more and more attention from funding agencies and scientific policy makers. However, most policies focus on data as the output of research. In…