Conference Agenda (All times are shown in Greenwich Mean Time (GMT) unless otherwise noted)

The cross-domain knowledge diffusion from science to policy is a prevalent phenomenon that demands academic attention. To investigate the characteristics of cross-domain knowledge diffusion from science to policy, this study suggests using the citation of policies to scientific articles as a basis for quantifying the diffusion strength, breadth, and speed. The study reveals that the strength and breadth of cross-domain knowledge diffusion from scientific papers to policies conform to a power-law distribution, while the speed follows a logarithmic normal distribution. Moreover, the papers with the highest diffusion strength, breadth, and fastest diffusion speed are predominantly from world-renowned universities, scholars, and top journals. The papers with the highest diffusion strength and breadth are mostly from social sciences, especially economics, those with the fastest diffusion speed are mainly from medical and life sciences, followed by social sciences. The findings indicate that cross-domain knowledge diffusion from science to policy follows the Matthew effect, whereby individuals or institutions with high academic achievements are more likely to achieve successful cross-domain knowledge diffusion. Furthermore, papers in the field of economics tend to have the higher cross-domain knowledge diffusion strength and breadth, while those in medical and life sciences have the faster cross-domain knowledge diffusion speed.

The Triple Helix interactions among different institutions have become increasingly important for science and technology development. In this study, we explore the synergic effect of the Triple Helix relationships of universities, industries, and governments in the field of climate change from the perspectives of vertical evolution and horizontal comparison. T indicators are utilized to measure the bilateral and trilateral institutional information transfer quantity based on the Web of Science core collection database from 2001 to 2021. The results indicated that the UIG collaborative innovation system of climate change is basically formed, but the synergic effect has been continuously eroded in recent years. In addition, we focus on a more detailed comparison among different topics and countries. Specifically, the bilateral and trilateral synergetic effects in the United States outperform that of other countries.

While major funding agencies are striving for diversity and fairness, the mechanisms behind funding success have yet to be fully elucidated. Existing studies reveal valuable evidences about the effect of the applicant's individual attributes, e.g., gender and age, on the funding success. However, the relationship between funding success and academic activities, e.g., collaborators’ characteristics, remains underexplored. This work collects massive scholarly data from open academic graphs and public data about National Institutes of Health awards to investigate the effect of various academic graph-based factors on the “K to R” success. Leveraging a heterogeneous graph model for predicting the “K to R” success, we regard the gain in the model performance of a factor as a proxy variable for the magnitude of its effect on the “K to R” success. Our preliminary results suggest that the quality and publishing year of an applicant’s citations are strongly correlated with the outcome. Meanwhile, the applicants’ social connections, e.g., their collaborators, can also contribute to the outcome.

This article investigates the lengths of time that publications with different numbers of policy document mentions take to receive their first mention (the beginning stage), and then compares the lengths of time to receive two or more mentions after receiving the first mention (the accumulative stage) based on complete policy document dataset from Altmetric database. We find that in the beginning stage, that is, from zero to one mention, high- and medium-, mentioned papers exhibit obviously different lengths of time compared with low-mentioned papers. Moreover, in the accumulative stage, that is, from one to N citations, highly mentioned papers begin to receive mentions much more rapidly than medium- and low-mentioned papers. Moreover, as N increases, the difference in receiving new mentions among high-, medium-, and low-mentioned publications increases quite significantly.

There is limited systematic research on understanding the trends of STEM education in libraries. While reviews of STEM education from various funding agencies exist, these reviews encompass STEM education across formal and informal settings, which may not provide specific implications that centers around libraries. This paper aims to examine the trend of collaboration among libraries and other collaborating organizations involved in STEM education that are funded by the Institute of Museum and Library Services (IMLS). Through content analysis and geocode analysis of 128 projects that are funded by IMLS in 2012–2022, this study shows the diverse engagement of different types of informal learning institutions in STEM education over time. Findings also demonstrate that while few informal learning institutions represented the leading and collaborating organizations in IMLS STEM education in the beginning, leading and collaborating organizations diversified with a higher level of collaboration.