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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., Citation metrics are widely used and misused. This Community Page article presents a publicly available database that provides standardized information on multiple citation indicators and a composite thereof, annotating each author according to his/her main scientific field(s).

Preprints have arrived. In increasing numbers, researchers across the life sciences are embracing the once-niche practice, shaking off decades of reluctance and posting hundreds of papers per week to preprint servers, sharing their findings with the community before embarking on the weary march through peer review. However, there are limited methods for individuals sifting through this avalanche of research to identify the preprints that are most relevant to their interests. Here, we describe Rxivist.org, a website that indexes all preprints posted to bioRxiv.org, the largest preprint server in the life sciences, and allows users to filter and sort papers based on download metrics and Twitter activity over a variety of categories and time periods. In this work, we hope to make it easier for readers to find relevant research on bioRxiv and to improve the visibility of preprints currently being read and discussed online., This Community Page article describes Rxivist.org, a new website that indexes all preprints posted to bioRxiv.org and allows users to filter and sort papers based on download metrics and Twitter activity over a variety of categories and time periods.

The reproducibility crisis triggered worldwide initiatives to improve rigor, reproducibility, and transparency in biomedical research. There are many examples of scientists, journals, and funding agencies adopting responsible research practices. The QUEST (Quality-Ethics-Open Science-Translation) Center offers a unique opportunity to examine the role of institutions. The Berlin Institute of Health founded QUEST to increase the likelihood that research conducted at this large academic medical center would be trustworthy, useful for scientists and society, and ethical. QUEST researchers perform “science of science” studies to understand problems with standard practices and develop targeted solutions. The staff work with institutional leadership and local scientists to incentivize and support responsible practices in research, funding, and hiring. Some activities described in this paper focus on the institution, whereas others may benefit the national and international scientific community. Our experience, approaches, and recommendations will be informative for faculty leadership, administrators, and researchers interested in improving scientific practice., This Community Page article describes an ongoing large-scale structured initiative at the Berlin Institute of Health which aims at improving the robustness, reproducibility and transparency of research in an academic biomedical setting.

The centrifuge is an essential tool for many aspects of research and medical diagnostics. However, conventional centrifuges are often inaccessible outside of standard laboratory settings, such as remote field sites, because they require a constant external power source and can be prohibitively costly in resource-limited settings and Science, technology, engineering, and mathematics (STEM)-focused programs. Here we present the 3D-Fuge, a 3D-printed hand-powered centrifuge, as a novel alternative to standard benchtop centrifuges. Based on the design principles of a paper-based centrifuge, this 3D-printed instrument increases the volume capacity to 2 mL and can reach hand-powered centrifugation speeds up to 6,000 rpm. The 3D-Fuge devices presented here are capable of centrifugation of a wide variety of different solutions such as spinning down samples for biomarker applications and performing nucleotide extractions as part of a portable molecular lab setup. We introduce the design and proof-of-principle trials that demonstrate the utility of low-cost 3D-printed centrifuges for use in remote field biology and educational settings., This Community Page article describes a low-cost 3D-printed centrifuge to enable sequencing in remote field conditions and lowering the barrier to synthetic biology research in high schools to broaden participation in hands-on STEM.

For most experimental biologists, handling the avalanche of data generated is similar to self-learn how to drive. Although that might be doable, it is preferable and safer to learn good practices. One way to achieve this is to build local communities of practice by bringing together scientists that perform code-intensive research to spread know-how and good practices. Here, we indicate important challenges and issues that stand in the way of establishing these local communities of practice. For a given researcher working for an academic institution, their capacity to conduct data-intensive research will be arbitrarily relying on the presence of well-trained bioinformaticians in their neighborhood. In this paper, we propose a model to build a local community of practice for scientific programmers. First, Software/Data Carpentry (SWC) programming workshops designed for researchers new to computational biology can be organized. However, while they provide an immediate solution for learning, more regular long-term assistance is also needed. Researchers need persisting, local support to continue learning and to solve programming issues that hamper their research progress. The solution we describe here is to implement a study group where researchers can meet-up and help each other in a "safe-learning atmosphere". Based on our experience, we describe two examples of building local communities of practice: one in the Netherlands at the Amsterdam Science Park and one in the United States at the University of Wisconsin-Madison. The current challenge is to make these local communities self-sustainable despite the high turnover of researchers at any institution and the lack of academic reward (e.g. publication). Here, we present some lessons learned from our experience. We believe that our local communities of practice will prove useful for other scientists that want to set up similar structures of researchers involved in scientific programming and data science.