Before diving into the analysis, we familiarised ourselves with the IPGOD2022 dataset. This involved examining the structure, columns, and types of data available.
Extract relevant data from the IPGOD2022 dataset:
The top applicants for patents, trademarks and designs.
The industries or technologies the top applicants are active in.
External research is required since the dataset might not have direct information about whether a company is female-led or has female-friendly policies. This includes searching the following for the top applicant:
- Leadership initiatives
- Hiring and diversity policies
- Awards and/or recognitions
Once we have the necessary data, we analyse it to:
- Determine the percentage of top applicants that are female-led.
- Discover how many female-friendly hiring policies or favourable gender/sexual diversity policies are in place.
- Identify the industry or technology that the organisation is active in.
Represent our findings visually, such as pie charts and bar graphs.
Based on our analysis, we provide insights such as trends or patterns we have observed as well as the following:
- Which industries have the highest percentage of female-led companies among top IP applicants?
- Are there specific industries where female-friendly policies are more common?