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Register a new userMandated data archiving greatly improves access to research data
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The data underlying scientific papers should be accessible to researchers both now and in the future, but how best can we ensure that these data are available? Here we examine the effectiveness of four approaches to data archiving: no stated archiving policy, recommending (but not requiring) archiving, and t
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Lifecycle models for research data are often abstract and simple. This comes at the danger of oversimplifying the complex concepts of research data management. The analysis of 90 different lifecycle models lead to two approaches to assess the quality of these models. While terminological issues make direct comparisons of models hard, an empirical evaluation seems possible.
Without sufficient information about researchers data sharing, there is a risk of mismatching FAIR data service efforts with the needs of researchers. This study describes a methodology where departmental publications are used to analyse the ways in which computer scientists share research data. All journal articles published by researchers in the computer science department of the case studys university during 2019 were extracted for scrutiny from the current research information system. For these 193 articles, a coding framework was developed to capture the key elements of acquiring and sharing research data. Furthermore, a rudimentary classification of the main study types exhibited in the investigated articles was developed to accommodate the multidisciplinary nature of the case departments research agenda. Human interaction and intervention studies often collected original data, whereas research on novel computational methods and life sciences more frequently used openly available data. Articles that made data available for reuse were most often in life science studies, whereas data sharing was least frequent in human interaction studies. The use of open code was most frequent in life science studies and novel computational methods. The findings highlight that multidisciplinary research organisations may include diverse subfields that have their own cultures of data sharing, and suggest that research information system-based methods may be valuable additions to the questionnaire and interview methodologies eliciting insight into researchers data sharing. The collected data and coding framework are provided as open data to facilitate future research.
Ocean modelling requires the production of high-fidelity computational meshes upon which to solve the equations of motion. The production of such meshes by hand is often infeasible, considering the complexity of the bathymetry and coastlines. The use of Geographical Information Systems (GIS) is therefore a key component to discretising the region of interest and producing a mesh appropriate to resolve the dynamics. However, all data associated with the production of a mesh must be provided in order to contribute to the overall recomputability of the subsequent simulation. This work presents the integration of research data management in QMesh, a tool for generating meshes using GIS. The tool uses the PyRDM library to provide a quick and easy way for scientists to publish meshes, and all data required to regenerate them, to persistent online repositories. These repositories are assigned unique identifiers to enable proper citation of the meshes in journal articles.
AstroCloud is a cyber-Infrastructure for Astronomy Research initiated by Chinese Virtual Observatory (China-VO) under funding support from NDRC (National Development and Reform commission) and CAS (Chinese Academy of Sciences){url{http://astrocloud.china-vo.org}}citep{O8-5_Cui_adassxxiv}. To archive the astronomical data in China, we present the implementation of the astronomical data archiving system (ADAS). Data archiving and quality control are the infrastructure for the AstroCloud. Throughout the data of the entire life cycle, data archiving system standardized data, transferring data, logging observational data, archiving ambient data, And storing these data and metadata in database. Quality control covers the whole process and all aspects of data archiving.
As a part of science of science (SciSci) research, the evolution of scientific disciplines has been attracting a great deal of attention recently. This kind of discipline level analysis not only give insights of one particular field but also shed light on general principles of scientific enterprise. In this paper we focus on graphene research, a fast growing field covers both theoretical and applied study. Using co-clustering method, we split graphene literature into two groups and confirm that one group is about theoretical research (T) and another corresponds to applied research (A). We analyze the proportion of T/A and found applied research becomes more and more popular after 2007. Geographical analysis demonstrated that countries have different preference in terms of T/A and they reacted differently to research trend. The interaction between two groups has been analyzed and shows that T extremely relies on T and A heavily relies on A, however the situation is very stable for T but changed markedly for A. No geographic difference is found for the interaction dynamics. Our results give a comprehensive picture of graphene research evolution and also provide a general framework which is able to analyze other disciplines.
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