Imperial has developed an analytics tool that presents data on the geographic distribution of the institutional affiliations of authors cited on Imperial’s reading lists. It also includes information on the country income level of  the countries in which those institutions are located.

There is currently data for close to 12,000 articles from approximately 3,300 Imperial reading lists published on Leganto between 2016 and 2024.

The tool has been created to help staff or students access data that may inform broader discussions about representation on reading lists and in curricula. Creation of the tool has been supported by Imperial’s President’s Excellence Fund for Learning and Teaching Innovation and  NIHR ARC NW London.

Access the tool

Two versions of the tool exist. The main version of the tool is hosted on Power BI. This version incorporates reading list data from Leganto. It gathers article metadata from Scopus and integrates this with country income data from the World Bank.

The image below shows the Power BI dashboard with information on all reading lists at Imperial published on Leganto since 2016. Dots on the map represent countries with affiliated authors, with the size of each dot in proportion to the number of authors affiliated with an institution in that country.

 

The tool is available to all staff here. Please note you will need to be given permission to access Power BI if you do not already have it. You can also request a consultation meeting if you need assistance navigating the platform and wish to learn more about how to engage in meaningful exploration of your reading list or curriculum using the Power BI platform.

A “lite” version of the tool also exists. This version allows users to input a DOI, or a list of DOIs, rather than obtaining data automatically from Leganto. Article metadata for this version comes from OpenAlex. The lite version is intended for staff or students who may wish to interrogate the geographic distribution of author institutional affiliations of articles they are citing on a research paper or an assessment.  

 

Events

To learn more about the tool and how to use it in your practice, you may wish to attend any of the following events:

Networks and communities

Imperial College Union Liberation & Community networks

Research

  • Price R, Skopec M. MacKenzie S, Nijhoff C, Harrison R, Seabrook G, Harris M.  A novel data solution to analyse curriculum decolonisation–the case of Imperial College London Masters in Public Health. Scientometrics 2022, 127;1021-1037
  • Skopec, M., Fyfe, M., Issa, H., Ippolito, K., Anderson, M. and Harris, M. (2021) ‘Decolonization in a higher education STEMM institution – is “epistemic fragility” a barrier?’ London Review of Education, 19 (1), 1–21. https://doi.org/10.14324/LRE.19.1.18
  • Skopec M, Issa H, Reed J, Harris M. The role of geographic bias in knowledge diffusion: a systematic review. Research Integrity and Peer Review 2020 5(2)
  • Harris M, Marti J, Bhatti Y, Watt H, Macinko J, Darzi A. Explicit bias towards high-income country research: a randomized, blinded crossover trial of decision-making by English clinicians. Health Affairs 2017: 36(11); 1994-2007
  • Harris M, Macinko J, Jimenez G and Mulacherry P. Measuring the bias against low-income country research: an Implicit Association Test. Globalization and Health 2017; 13:80
  • Harris M, Weisberger E, Silver D, Macinko J. ‘They hear “Africa” and think there are no good services there’ - perceived context in cross-national learning: a qualitative study. Globalization and Health 2015: 11;45
Request consultation for access to the tool