Global patterns of migration of scholars with economic development.

We leverage metadata on over 36 million journal articles and reviews indexed by Scopus in order to estimate migration of scholars based on information on changes in their institutional affiliations over time. We produce a database of yearly international migration flows of scholars, for all countries from 1998 to 2017. We use the open-access database to provide descriptive evidence on the relationship between economic development and the emigration propensity of scholars. Statistical analysis using generalized additive mixed models reveals that emigration rates initially decrease as GDP per capita increases. Then, starting from around 25,000 dollars (2017 constant international dollars at purchasing power parity), the trend reverses and emigration propensity increases as countries get richer. This U-shaped pattern contrasts with what has been found in the literature for emigration rates for the general population and calls for theoretical frameworks to understand the heterogeneous responses of migration to development.

Bilateral flows and rates of international migration of scholars for 210 countries for the period 1998-2020.

A lack of comprehensive migration data is a major barrier for understanding the causes and consequences of migration processes, including for specific groups like high-skilled migrants. We leverage large-scale bibliometric data from Scopus and OpenAlex to trace the global movements of scholars. Based on our empirical validations, we develop pre-processing steps and offer best practices for the measurement and identification of migration events. We have prepared a publicly accessible dataset that shows a high level of correlation between the counts of scholars in Scopus and OpenAlex for most countries. Although OpenAlex has more extensive coverage of non-Western countries, the highest correlations with Scopus are observed in Western countries. We share aggregated yearly estimates of international migration rates and of bilateral flows for 210 countries and areas worldwide for the period 1998-2020 and describe the data structure and usage notes. We expect that the publicly shared dataset will enable researchers to further study the causes and the consequences of migration of scholars to forecast the future mobility of academic talent worldwide.

Toward Community Standards and Software for Whole-Cell Modeling.

OBJECTIVE: Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate comprehensive models of complex cells. METHODS: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in the Systems Biology Markup Language. RESULTS: Our analysis revealed several challenges to representing WC models using the current standards. CONCLUSION: We, therefore, propose several new WC modeling standards, software, and databases. SIGNIFICANCE: We anticipate that these new standards and software will enable more comprehensive models.