Search

Citation metrics are widely used and misused. We have created a publicly available database of 100,000 top scientists that provides standardized information on citations, h-index, coauthorship-adjusted hm-index, citations to papers in different authorship positions, and a composite indicator. Separate data are shown for career-long and single-year impact. Metrics with and without self-citations and ratio of citations to citing papers are given. Scientists are classified into 22 scientific fields and 176 subfields. Field- and subfield-specific percentiles are also provided for all scientists who have published at least five papers. Career-long data are updated to end of 2017 and to end of 2018 for comparison. [ABSTRACT FROM AUTHOR]

In this paper, we describe why and how to build a local community of practice in scientific programming for life scientists who use computers and programming in their research. A community of practice is a small group of scientists who meet regularly to help each other and promote good practices in scientific programming. While most life scientists are well trained in the laboratory to conduct experiments, good practices with (big) data sets and their analysis are often missing. We propose a model on how to build such a community of practice at a local academic institution, present two real-life examples, and introduce challenges and implemented solutions. We believe that the current data deluge that life scientists face can benefit from the implementation of these small communities. Good practices spread among experimental scientists will foster open, transparent, and sound scientific results beneficial to society. [ABSTRACT FROM AUTHOR]

Data, including information generated from them by processing and analysis, are an asset with measurable value. The assets that biological research funding produces are the data generated, the information derived from these data, and, ultimately, the discoveries and knowledge these lead to. From the time when Henry Oldenburg published the first scientific journal in 1665 (Proceedings of the Royal Society) to the founding of the United States National Library of Medicine in 1879 to the present, there has been a sustained drive to improve how researchers can record and discover what is known. Researchers’ experimental work builds upon years and (collectively) billions of dollars’ worth of earlier work. Today, researchers are generating data at ever-faster rates because of advances in instrumentation and technology, coupled with decreases in production costs. Unfortunately, the ability of researchers to manage and disseminate their results has not kept pace, so their work cannot achieve its maximal impact. Strides have recently been made, but more awareness is needed of the essential role that biological data resources, including biocuration, play in maintaining and linking this ever-growing flood of data and information. The aim of this paper is to describe the nature of data as an asset, the role biocurators play in increasing its value, and consistent, practical means to measure effectiveness that can guide planning and justify costs in biological research information resources’ development and management. [ABSTRACT FROM AUTHOR]

In Europe, responsible research and innovation (RRI) has emerged as a science policy measure that demands the early integration of a broad range of social actors and perspectives into research and development (R&D). More collaboration of the social sciences and humanities (SSH) with science and engineering appears within this policy framework as a crucial element that will enable better technological development. However, RRI is new to both natural scientists and SSH scholars, and interdisciplinary collaborations are challenging for many reasons. In this paper, we discuss these challenges while suggesting that what RRI can be in a particular project is not a given but remains an empirical question. Natural scientists and SSH scholars need to coresearch RRI in an experimental mode. [ABSTRACT FROM AUTHOR]