The use of data to guide action is growing. Even the public uses data to guide everyday decisions! How do we develop data acumen across a broad range of fields and varying levels of expertise? How do we foster the development of effective data translators? This book explores these questions, presenting an interdisciplinary collection of edited contributions across fields such as education, health sciences, natural sciences, politics, economics, business and management studies, social sciences, and humanities. Authors illustrate how to use data within a discipline, including visualization and analysis, translating and communicating results, and pedagogical considerations. This book is of interest to scholars and anyone looking to understand the use of data science across disciplines. It is ideal in a course for non-data science majors exploring how data translation occurs in various contexts and for professionals looking to engage in roles requiring data translation.

Explores data science across disciplines to illustrate the applications in disciplinary context Focuses on effective application and communication as case studies Highlight how data is used within a discipline but also the way in which data is translated to inform discipline

Klappentext

Translating science into actionable policy information - a perspective on the IPCC process.- Data in Observational Astronomy.- On Becoming a Data-Scientist , Beyond Translation: Discovering Best Practices for Evidence-Informed Decision Making for Public Health Practices.- Concern for self-health during the COVID-19 pandemic in Canada: How to use quantitative data to tell an intersectional story?- Community-based participatory research and respondent-driven sampling: A statistician's, community partner's and students' perspectives on a successful partnership.

Inhalt
Translating science into actionable policy information a perspective on the IPCC process.- Data in Observational Astronomy.- On Becoming a Data-Scientist , Beyond Translation: Discovering Best Practices for Evidence-Informed Decision Making for Public Health Practices.- Concern for self-health during the COVID-19 pandemic in Canada: How to use quantitative data to tell an intersectional story?- Community-based participatory research and respondent-driven sampling: A statistician's, community partner's and students' perspectives on a successful partnership.