Related papers: "Eppur si muove", Software Libero e Ricerca Riprod…
This paper presents a methodology for designing a containerized and distributed open science infrastructure to simplify its reusability, replicability, and portability in different environments. The methodology is depicted in a step-by-step…
As scientific work becomes more computational and data intensive, research processes and results become more difficult to interpret and reproduce. In this poster, we show how the Jupyter notebook, a tool originally designed as a free…
To reproduce eScience, several challenges need to be solved: scientific workflows need to be automated; the involved software versions need to be provided in an unambiguous way; input data needs to be easily accessible; High-Performance…
At the intersection of what I call uncomputable art and computational epistemology, a form of experimental philosophy, we find an exciting and promising area of science related to causation with an alternative, possibly best possible,…
Current concerns about reproducibility in many research communities can be traced back to a high value placed on empirical reproducibility of the physical details of scientific experiments and observations. For example, the detailed…
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…
Replication packages are crucial for enabling transparency, validation, and reuse in software engineering (SE) research. While artifact sharing is now a standard practice and even expected at premier SE venues such as ICSE, the practical…
The fact that the number of users of open source software (OSS) is practically un-limited and that ultimately the software quality is determined by end users experience, makes the usability an even more critical quality attribute than it is…
Improved software discovery is a prerequisite for greater software reuse: after all, if someone cannot find software for a particular task, they cannot reuse it. Understanding people's approaches and preferences when they look for software…
Modern software development methodologies include reuse of open source code. Reuse can be facilitated by architectural knowledge of the software, not necessarily provided in the documentation of open source software. The effort required to…
We present OpenML and mldata, open science platforms that provides easy access to machine learning data, software and results to encourage further study and application. They go beyond the more traditional repositories for data sets and…
The reproducibility of scientific articles is central to the advancement of science. Despite this importance, evaluating reproducibility remains challenging due to the scarcity of ground truth data. Predictive models can address this…
Data analysis in fundamental sciences nowadays is an essential process that pushes frontiers of our knowledge and leads to new discoveries. At the same time we can see that complexity of those analyses increases fast due to a)~enormous…
Scientific workflows are becoming increasingly popular for compute-intensive and data-intensive scientific applications. The vision and promise of scientific workflows includes rapid, easy workflow design, reuse, scalable execution, and…
This paper proposes an interactive repository type for research software metadata which measures and documents software sustainability by accumulating metadata, and computing sustainability metrics over them. Such a repository would help to…
Obviously, the dynamism of software reliability research has speeded up significantly in the last period, and we can state the fact that its intensity is approaching, and in some cases is ahead of the information systems hardware…
Background: The development of scientific software applications is far from trivial, due to the constant increase in the necessary complexity of these applications, their increasing size, and their need for intensive maintenance and reuse.…
Reproducibility of computational research is critical for ensuring transparency, reliability and reusability. Challenges with computational reproducibility have been documented in several fields, but healthcare discrete-event simulation…
Background: Research software plays an important role in solving real-life problems, empowering scientific innovations, and handling emergency situations. Therefore, the correctness and trustworthiness of research software are of absolute…
Human creativity is the ultimate driving force behind scientific progress. While the building blocks of innovations are often embodied in existing knowledge, it is creativity that blends seemingly disparate ideas. Existing studies have made…