The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. WiDS is administered by the Institute for Computational & Mathematical Engineering, Stanford University, USA. The WiDS conference, associated events, and data challenges are all aimed at nurturing human resources in the field of data science.
Since 2015, there have been approximately 150+ regional WiDS events worldwide. Japan Yokohama City University YCU) held its first event, WiDS Tokyo@YCU, on 22nd March 2019 with the cooperation of universities, industry players and public sector participants.
Japan's big data/analytics (BDA) software market is expected to reach 380 billion by 2022, according to IDC Japan. However, there is a considerable shortage of data science personnel in this growing market. It is predicted that data science related vacancies, handled by major companies could increase by 6 folds (DODA survey). To address the growing demand for data scientists, there has been an increase in the number of universities and training organizations providing specialized courses. Additionally, even within the traditional faculties, be it humanities or engineering, there are data science-focused courses on offer.
Furthermore, there has also been a public sector movement to develop interest and expertize in data science through the “Data Scientist Development Project for Realizing Society 5.0” by Ministry of Education, Culture, Sports, Science and Technology (MEXT), and “Data Science Online Course” by Ministry of Internal Affairs and Communications. Educational programs provided by private sector organizations are also gaining momentum. Given the high demand for data science personnel, the different avenues available for gaining the necessary skills have also increased.
However, acquiring skills in this field is said to have many barriers. One of the biggest barriers is the perceived weakness in science or technological literacy and fear of programming. Many of the data science-related courses are expensive and are not easy to learn. For women, in particular, learning opportunities may be limited due to life-cycle effects.