Wednesday, November 22, 2017

Using Orcid for migration studies

ORCID provides a persistent digital identifier that distinguishes every  researcher and, through integration in key research workflows such as manuscript and grant submission, supports automated linkages between professional activities ensuring that one's work is recognized.

ORCID wasn't intended as a massive longitudinal survey of the global population of scientists, but with 3 million profiles and growing, it is becoming just that. So far a quarter of those researchers have voluntarily added personal information to their public ORCID profiles including the years, locations, and descriptions of their education and employment histories. As this voluntary sampling grows, the demographic and migration patterns of the scientific workforce is coming into focus. The biases are also apparent: ORCID users skew young, and certain countries are over- and underrepresented.

Bohannon J and Doran K prepared a set of tools and datasets allowing to use more easily such data:

A file contains 2.8 million public profiles from ORCID in both XML and JSON format. You will need 300 GB of free space to decompress the data and work with it.

A IPython Notebook provides code for processing the data from public_profiles.tar into manageable data files for analysis.

http://datadryad.org/resource/doi:10.5061/dryad.48s16

Another examples of usage of such data in migration studies:

https://towardsdatascience.com/analyse-the-migration-of-scientific-researchers-5184a9500615

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