Resources

Dimensions API Labs – code examples

This page contains Jupyter notebooks to show how to carry out common scholarly data analytics tasks using the Dimensions Analytics API.

API on Github

Learn about the Dimensions Analytics API via code examples and Jupyter notebooks.

Using Dimensions’ robust grants database to assess the state of Canadian climate science

Tristan’s objective was to assess the current state of climate science resources and funding in Canada and use the results to offer recommendations to strengthen the field.

Identifying Global Expertise in CAR-T

Digital Science offers data capabilities and the connected data to help life science organizations understand the Car-T research and development landscape.

Providing valuable data on funding flows to academia for market model development

Aruna Rajan is a Staff Market Research Analyst at Illumina. Aruna’s role involves providing strategic insights and actionable information from market models and other analyses.

An A&I database on steroids

Jenny Wooldridge, Senior Analyst in the analysis and evaluation team at the UK-based National Physical Laboratory describes how powerful Dimensions is at helping conduct vital research and strategic analyses.

Using Dimensions to understand Open Access adoption rates

Philipp Pollack, Data & Metrics Specialist in the Central Library at Forschungszentrum Jülich, highlights the vital role Dimensions and GRID data play in monitoring Germany’s Open Access activity.

An easy to use and powerful API for topic analysis

John de Mello, Head of Nano at Norwegian University of Science & Technology, describes how he has used the Dimensions API to help his university understand what it does - and what it could do - in nanoscience and technology

Reproducibility or Producibility? Metrics and their Masters

Access to large scale data to produce new insights or reproduce existing results is a necessity for scientometric research and access cannot be limited by commercial considerations.

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