Human Factors in Data Science

Data Science (DS) has been shifting from libraries and stacks to usage and impact. While "database thinking" is permeating all levels in a DS stack, the DS lifecycle can only be fully realized by looping in humans in a principled and safe fashion. This paper focuses on the role of humans and user data in DS. It starts with the impact of human factors on the design of sustainable and fair data generation and curation. It then reviews how data processing and mining are being revisited to derive insights from user data. That is followed by how human-data interaction shapes the way we think about evaluating DS applications. The paper ends with opportunities that arise when bringing together database thinking and DS for humans.