Assuntos
Conjuntos de Dados como Assunto/normas , Ciências da Terra/estatística & dados numéricos , Disseminação de Informação/métodos , Armazenamento e Recuperação da Informação/métodos , Armazenamento e Recuperação da Informação/normas , Publicação de Acesso Aberto/normas , Reciclagem/normas , Conjuntos de Dados como Assunto/economia , Conjuntos de Dados como Assunto/tendências , Ciências da Terra/economia , Armazenamento e Recuperação da Informação/economia , Armazenamento e Recuperação da Informação/tendências , Metadados/normas , Metadados/estatística & dados numéricos , Meteorologia/economia , Meteorologia/estatística & dados numéricos , Publicação de Acesso Aberto/economia , Publicação de Acesso Aberto/tendências , Reciclagem/economia , Reciclagem/métodos , Reciclagem/tendências , Reprodutibilidade dos TestesRESUMO
Urgent responses to the COVID-19 pandemic depend on increased collaboration and sharing of data, models, and resources among scientists and researchers. In many scientific fields and disciplines, institutional norms treat data, models, and resources as proprietary, emphasizing competition among scientists and researchers locally and internationally. Concurrently, long-standing norms of open data and collaboration exist in some scientific fields and have accelerated within the last two decades. In both cases-where the institutional arrangements are ready to accelerate for the needed collaboration in a pandemic and where they run counter to what is needed-the rules of the game are "on the table" for institutional-level renegotiation. These challenges to the negotiated order in science are important, difficult to study, and highly consequential. The COVID-19 pandemic offers something of a natural experiment to study these dynamics. Preliminary findings highlight: the chilling effect of politics where open sharing could be expected to accelerate; the surprisingly conservative nature of contests and prizes; open questions around whether collaboration will persist following an inflection point in the pandemic; and the strong potential for launching and sustaining pre-competitive initiatives.
RESUMO
Software is as integral as a research paper, monograph, or dataset in terms of facilitating the full understanding and dissemination of research. This article provides broadly applicable guidance on software citation for the communities and institutions publishing academic journals and conference proceedings. We expect those communities and institutions to produce versions of this document with software examples and citation styles that are appropriate for their intended audience. This article (and those community-specific versions) are aimed at authors citing software, including software developed by the authors or by others. We also include brief instructions on how software can be made citable, directing readers to more comprehensive guidance published elsewhere. The guidance presented in this article helps to support proper attribution and credit, reproducibility, collaboration and reuse, and encourages building on the work of others to further research.