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Publish with us

Applying to the Lab

Before granting access, we check that the data sources and technical capabilities required for your research plan are available in the Lab.

ICSR Lab is intended for scholarly research only, and due to the nature of the data inside it is important that we understand who needs access to which data as well as approximate timelines for access.

The application process checks that your research is in line with the ICSR research themes and assesses whether your plan is feasible given the ICSR Lab's capabilities and your expertise.

Submitting your research proposal

The first step is to submit a research proposal application via the submission system, Digital Commons. You will have to register and may receive a registration confirmation email. The ICSR Lab application form asks for the following:

  1. Contact and affiliation information for everyone who will need access to the Lab.

  2. Proposal details including: title and abstract, your expected timelines and outcomes, relevant supporting research, and details of technical experience and expertise.

You can save and return to your application later as required.

Application review

Applications are initially screened by the ICSR Lab team and (if relevant) sent for peer-review by ICSR Advisory Board members. Reviewers consider the following during the review process:

  • Applicability and alignment of your proposal to the ICSR research themes

  • The potential of the research results to inform practice in research evaluation and policy

  • Feasibility, overall quality and whether additional consideration should be given to maximize inclusivity

  • Intention of the project is to produce and publish scholarly research, rather than produce an analysis for your (internal) organizational purposes

Application result

We aim to process applications as quickly as possible. Where we send the application for peer review, we will communicate a decision at most within eight weeks of applying. Please note that applications which include access to a Specialized Workbench, such as the Peer Review Workbench, are reviewed by external experts in this field. This process may, therefore, take longer than for regular ICSR Lab applications.

If successful, you and your collaborators are then invited to review and agree to the terms of use and can access the Lab immediately thereafter. To get started you can then refer to example code illustrating common scenarios as well as dataset documentation.

Getting started in the Lab

Preparing your analysis and working with the full datasets

When you first enter the Lab you can explore the data sources and their structure. However, in order to use resources efficiently, make your test queries run faster and ensure data security, your exploratory analyses are run on large and varied subsets of the full datasets available in the Lab.

Once you have prepared your final data processing pipeline you can reach out to us via email. Our team will quickly review your notebook and run your code over the entire dataset, giving you access to the results of your analysis.

Downloading, using and sharing your results

You are encouraged to share and publish the output of your experiments in ICSR Lab within the bounds of our data-sharing policy:

  • At the aggregated (e.g., country, year, subject area) or calculated (e.g., a new metric) level, data may be exported from ICSR Lab and processed in local environments, e.g., for visualization, and published or shared along with your findings

  • During your application process the ICSR Lab team may correspond with you to define the datasets you plan to export

  • Should your research result in a published output (e.g., article, conference paper, poster or blog), we ask that you inform the ICSR Lab team about your publication and acknowledge ICSR Lab as the source of your data with the text, e.g., "This work uses Scopus data provided by Elsevier through ICSR Lab." We encourage you to also make your aggregated data and (where appropriate) code publicly accessible at the time of publishing your results, e.g., on Mendeley Data(opens in new tab/window) or similar platforms

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