Related papers: Experimental Research Data Quality In Materials Sc…

Software is now a vital scientific instrument, providing the tools for data collection and analysis across disciplines from bioinformatics and computational physics, to the humanities. The software used in research is often home-grown and…

Since its launch in 2011, Materials Genome Initiative (MGI) has drawn the attention of researchers from across academia, government, and industry worldwide.As one of the three tools of MGI, the materials data, for the first time, emerged as…

Companies and academic researchers may collect, process, and distribute large quantities of personal data without the explicit knowledge or consent of the individuals to whom the data pertains. Existing forms of consent often fail to be…

The "reproducibility crisis" has been a highly visible source of scientific controversy and dispute. Here, I propose and review several avenues for identifying and prioritizing research studies for the purpose of targeted validation. Of the…

Like it or not, attempts to evaluate and monitor the quality of academic research have become increasingly prevalent worldwide. Performance reviews range from at the level of individuals, through research groups and departments, to entire…

To retrieve and compare scientific data of simulations and experiments in materials science, data needs to be easily accessible and machine readable to qualify and quantify various materials science phenomena. The recent progress in open…

The discovery of new materials as well as the determination of a vast set of materials properties for science and technology is a fast growing field of research, with contributions from many groups worldwide. Materials data from individual…

Sharing scientific data, with the objective of making it fully discoverable, accessible, assessable, intelligible, usable, and interoperable, requires work at the disciplinary level to define in particular how the data should be formatted…

The widespread adoption of big data has ushered in a new era of data-driven decision-making, transforming numerous industries and sectors. However, the efficacy of these decisions hinges on the quality of the underlying data. Poor data…

Data are essential for the experiments of relevant scientific publication recommendation methods but it is difficult to build ground truth data. A naturally promising solution is using publications that are referenced by researchers to…

Data science requires time-consuming iterative manual activities. In particular, activities such as data selection, preprocessing, transformation, and mining, highly depend on iterative trial-and-error processes that could be sped-up…

Accurate and comprehensive diatomic molecular spectroscopic data have long been vital in a wide variety of applications for measuring and monitoring astrophysical, industrial and other gaseous environments. These data are also used…

In this paper we discuss the notion of research data for the field of mathematics and report on the status quo of research-data management and planning. A number of decentralized approaches are presented and compared to needs and challenges…

Software repositories are rich sources of qualitative artifacts, including source code comments, commit messages, issue descriptions, and documentation. These artifacts offer many interesting insights when analyzed through quantitative…

There is increasing interest in combining information from experimental studies, including randomized and single-group trials, with information from external experimental or observational data sources. Such efforts are usually motivated by…

There is an emerging consensus in the scientific software community that progress in scientific research is dependent on the "quality and accessibility of software at all levels" (wssspe.researchcomputing.org.uk/). This progress depends on…

This special volume of Statistical Sciences presents some innovative, if not provocative, ideas in the area of reliability, or perhaps more appropriately named, integrated system assessment. In this age of exponential growth in science,…

Scientists today collect, analyze, and generate TeraBytes and PetaBytes of data. These data are often shared and further processed and analyzed among collaborators. In order to facilitate sharing and data interpretations, data need to carry…

Data-driven methods for mental health treatment and surveillance have become a major focus in computational science research in the last decade. However, progress in the domain, in terms of both medical understanding and system performance,…

This paper presents a tertiary review of software quality measurement research. To conduct this review, we examined an initial dataset of 7,811 articles and found 75 relevant and high-quality secondary analyses of software quality research.…