Related papers: Notebook articles: towards a transformative publis…
Open science movement has established reproducibility, transparency, and validation of research outputs as essential norms for conducting scientific research. It advocates for open access to research outputs, especially research data, to…
Computational notebooks, widely used for ad-hoc analysis and often shared with others, can be difficult to understand because the standard linear layout is not optimized for reading. In particular, related text, code, and outputs may be…
The sharing and citation of research data is becoming increasingly recognized as an essential building block in scientific research across various fields and disciplines. Sharing research data allows other researchers to reproduce results,…
The massive trend of integrating data-driven AI capabilities into traditional software systems is rising new intriguing challenges. One of such challenges is achieving a smooth transition from the explorative phase of Machine Learning…
How can we better organize code in computational notebooks? Notebooks have become a popular tool among data scientists, as they seamlessly weave text and code together, supporting users to rapidly iterate and document code experiments.…
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…
Science and technology journalists today face challenges in finding newsworthy leads due to increased workloads, reduced resources, and expanding scientific publishing ecosystems. Given this context, we explore computational methods to aid…
The high incidence of irreproducible research has led to urgent appeals for transparency and equitable practices in open science. For the scientific disciplines that rely on computationally intensive analyses of large data sets, a granular…
The aim of this article is to introduce a reporting framework for reproducible, interactive research applied to Big Clinical Data, based on open source technologies. The framework is constituted by the following three axes: (i) data, (ii)…
Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging.…
With the recognized crisis of credibility in scientific research, there is a growth of reproducibility studies in computer science, and although existing surveys have reviewed reproducibility from various perspectives, especially very…
The term Open Access not only describes a certain model of scholarly publishing -- namely in digital format freely accessible to readers -- but often also implies that free availability of research results is desirable, and hence has a…
Computational reproducibility of scientific results, that is, the execution of a computational experiment (e.g., a script) using its original settings (data, code, etc.), should always be possible. However, reproducibility has become a…
Paper journals use a small number of trusted academics to select information on behalf of all their readers. This inflexibility in the selection was justified due to the expense of publishing. The advent of cheap distribution via the…
Contemporary debates on "open science" mostly focus on the pub- lic accessibility of the products of scientific and academic work. In contrast, this paper presents arguments for "opening" the ongoing work of science. That is, this paper is…
Interactive notebooks, such as Jupyter, have revolutionized the field of data science by providing an integrated environment for data, code, and documentation. However, their adoption by robotics researchers and model developers has been…
Social and technical trends have significantly changed methods for evaluating and disseminating computing research. Traditional venues for reviewing and publishing, such as conferences and journals, worked effectively in the past. Recently,…
Nanopublications are a concept to represent Linked Data in a granular and provenance-aware manner, which has been successfully applied to a number of scientific datasets. We demonstrated in previous work how we can establish reliable and…
Open science represents a transformative research approach essential for enhancing sustainability and impact. Data generation encompasses various methods, from automated processes to human-driven inputs, creating a rich and diverse…
The number of research papers written has been growing at least linearly -- if not exponentially -- in recent years. In proportion, the amount of time a reader allocates per paper has been decreasing. While an accessible paper will be…