The Collaborative Archive & Data Research Environment is a science gateway to standardized text- and data-mining services for large datasets—with reproducibility and collaboration in mind. All in a cloud-based platform.
Access over 220 million scientific publications and 1.7 billion citations from leading academic datasets.
Easily query large datasets with the CADRE Query Builder GUI and instantly export results to your profile for analysis.
Reproduce your research, query outputs, and data-analysis tools in the Marketplace and utilize the tools and research others share.
The Collaborative Archive & Data Research Environment (CADRE) began rolling out the beta version of its platform today and invites institutions to access CADRE through a free trial period. Users will have full access to all aspects of the release by Friday, Oct. 23.
This project is part of a series of studies in which researchers are assessing the rise of China in scholarship. In particular, the project aims to provide a comprehensive assessment of the nature of China's publications in science and engineering over the past 20 years.Read More
Researchers will perform a comparative analysis on papers published in four mathematical biology legacy journals and on newer journals with different publication models and disciplinary scope.Read More
This project will build on the WoS report “Navigating the Structure of Research on Sustainable Development Goals (SDG),” as the researchers search for patterns of global collaboration and support the United Nations’ SDG call for action.Read More
This research team wants to better characterize scientific influence of papers, typically measured by how many times papers are cited, by distinguishing between papers that destabilize existing knowledge with novel concepts and papers that consolidate existing knowledge.Read More
This project will create a map of papers on COVID-19 that will be compared with maps for similar viruses, such as SARS and influenza, to better understand unexplored and concentration areas in the research. Kojaku will employ neural embedding methods, used to project research papers onto a low dimen...Read More
These researchers plan to address the recent flood of COVID-19 studies into preprint repositories. The sudden influx makes it difficult for researchers to stay on top of research that is relevant to their particular field using metrics or citations. The research team proposes a network-driven study...Read More
This project will address the quality of recently published COVID-19 publications. The team says COVID-19 related research is being performed and published hastily, adding that turnaround times for medical journal publications have decreased by almost 50 percent. Speedy research and condensed public...Read More
Samuel’s project uses reference and citation aging, bibliographic coupling, and network breadth and depth to find similarities and differences between research fields in mathematics and the sciences.Read More
Researchers plan to determine the impact of the introduction and availability of long-distance flights on international scientific collaboration. The team will measure collaboration through co-authorship and co-affiliation.Read More
This research team plans to study the international collaborations that are forming to perform COVID-19 research. The researchers say the combination of an intense research focus and a demand for quick results provides a rare opportunity for social scientists who study collaboration, teaming, and sc...Read More
The research team seeks to find the “deeper” and “broader” impact of network-based citation measurements in the scientific community. This project will determine the citation impact of scientific publications using an ego-centered citation network.Read More
Researchers will characterize citation of data from the literature in the field of STEM education research. A sample of relevant publication venues in the field will be identified from WoS and MAG.Read More