In a world where data is more abundant than ever before, data scientists are often tasked with the responsibility of providing insights and decision support to inform and assist decision makers. To do this effectively, they must address authentic problems with integrity and ethics, taking into consideration cross-cultural perspectives and working within collaborative, interdisciplinary teams.
To this end, we aim to provide a data science platform that is both transparent and trustworthy. Our data is collected from multiple sources and made publicly available to the research community, and our visualization tools allow users to easily explore the data for themselves, in ways that are most relevant to their work. By making our data and tools available in this way, we hope to create a platform that will help support the growing number of researchers who are using machine learning techniques in their work.
This article discusses the key features of our platform, including our approach to openness, transparency, and accountability. It also provides an overview of our methodology and workflows. Finally, it offers tips for best practices in data science.
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