The Infectious Disease Ontology in the Age of COVID-19

The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In this paper we present applications of IDO Core within various areas of infectious disease research, together with an overview of all IDO extension ontologies and the methodology on the basis of which they are built. We also survey recent developments involving IDO, including the creation of IDO Virus; the Coronaviruses Infectious Disease Ontology (CIDO); and an extension of CIDO focused on COVID-19 (IDO-CovID-19).We also discuss how these ontologies might assist in information-driven efforts to deal with the ongoing COVID-19 pandemic, to accelerate data discovery in the early stages of future pandemics, and to promote reproducibility of infectious disease research

Understanding Developers Well-being and Productivity: A 2-year Longitudinal Analysis during the COVID-19 Pandemic—RCR Report

The artifact accompanying the paper "Understanding Developers Well-Being and Productivity: A 2-year Longitudinal Analysis during the COVID-19 Pandemic"provides a comprehensive set of tools, data, and scripts that were utilized in the longitudinal study. Spanning 24 months, from April 2020 to April 2022, the study delves into the shifts in well-being, productivity, social contacts, needs, and several other variables of software engineers during the COVID-19 pandemic. The artifact facilitates the reproduction of the study's findings, offering a deeper insight into the systematic changes observed in various variables, such as well-being, quality of social contacts, and emotional loneliness. By providing access to the evidence-generating mechanisms and the generated data, the artifact ensures transparency and reproducibility and allows researchers to use our rich dataset to test their own research question. This Replicated Computational Results report aims to detail the contents of the artifact, its relevance to the main paper, and guidelines for its effective utilization

Availability and issues of 3D-printed skull models for veterinary anatomy laboratories from students’ perspective before and during the COVID-19 pandemic

Three-dimensional (3D)-printed models of bones are a convenient and durable alternative to real bone specimens, and they have been used in anatomy laboratories. It is necessary to identify the precise advantages of 3D-printed models from all perspectives; not only the improvement in students' knowledge of anatomy but also the students' assessment of such models. Here, students of veterinary medicine and animal science evaluated the reproducibility and effectiveness of 3D-printed models as a learning tool by completing our questionnaires, with a focus on their understanding of the skull-morphological differences among dog breeds. With the COVID-19 pandemic having obliged veterinary universities to provide courses online, we also investigated how the pandemic affected the students' evaluation of the 3D-printed models. The questionnaire results revealed that the animal science students were satisfied with the reproducibility of the 3D-printed models, but the veterinary students were not (they preferred to use real specimens). The skull differences were well understood by both types of students, indicating that 3D-printed models are effective for learning about rare skeletal specimens. The veterinary students who experienced the COVID-19 pandemic tended to choose real specimens more often than those who did not have this experience. Our results suggest that the use of 3D-printed models as an introduction and the use of real specimens in anatomy laboratory courses can be adequate for veterinary students. Together our findings suggest ways to improve the educational performance of 3D-printed models for veterinary students who need to understand the anatomy of many species.journal articl

Open Science Saves Lives: Lessons from the COVID-19 Pandemic

In the last decade Open Science principles, such as Open Access, study preregistration, use of preprints, making available data and code, and open peer review, have been successfully advocated for and are being slowly adopted in many different research communities. In response to the COVID-19 pandemic many publishers and researchers have sped up their adoption of some of these Open Science practices, sometimes embracing them fully and sometimes partially or in a sub-optimal manner. In this article, we express concerns about the violation of some of the Open Science principles and its potential impact on the quality of research output. We provide evidence of the misuses of these principles at different stages of the scientific process. We call for a wider adoption of Open Science practices in the hope that this work will encourage a broader endorsement of Open Science principles and serve as a reminder that science should always be a rigorous process, reliable and transparent, especially in the context of a pandemic where research findings are being translated into practice even more rapidly

Searching for evidence in public health emergencies: a white paper of best practices

Objectives: Information professionals have supported medical providers, administrators and decision-makers, and guideline creators in the COVID-19 response. Searching COVID-19 literature presented new challenges, including the volume and heterogeneity of literature and the proliferation of new information sources, and exposed existing issues in metadata and publishing. An expert panel developed best practices, including recommendations, elaborations, and examples, for searching during public health emergencies. Methods: Project directors and advisors developed core elements from experience and literature. Experts, identified by affiliation with evidence synthesis groups, COVID-19 search experience, and nomination, responded to an online survey to reach consensus on core elements. Expert participants provided written responses to guiding questions. A synthesis of responses provided the foundation for focus group discussions. A writing group then drafted the best practices into a statement. Experts reviewed the statement prior to dissemination. Results: Twelve information professionals contributed to best practice recommendations on six elements: core resources, search strategies, publication types, transparency and reproducibility, collaboration, and conducting research. Underlying principles across recommendations include timeliness, openness, balance, preparedness, and responsiveness. Conclusions: The authors and experts anticipate the recommendations for searching for evidence during public health emergencies will help information specialists, librarians, evidence synthesis groups, researchers, and decision-makers respond to future public health emergencies, including but not limited to disease outbreaks. The recommendations complement existing guidance by addressing concerns specific to emergency response. The statement is intended as a living document. Future revisions should solicit input from a broader community and reflect conclusions of meta-research on COVID-19 and health emergencies