  Organizations across all sectors are increasingly undergoing deep
transformation and restructuring towards data-driven operations. The central
role of data highlights the need for reliable and clean data. Unreliable,
erroneous, and incomplete data lead to critical bottlenecks in processing
pipelines and, ultimately, service failures, which are disastrous for the
competitive performance of the organization. Given its central importance,
those organizations which recognize and react to the need for reliable data
will have the advantage in the coming decade. We argue that the technologies
for reliable data are driven by distinct concerns and expertise which
complement those of the data scientist and the data engineer. Those
organizations which identify the central importance of meaningful, explainable,
reproducible, and maintainable data will be at the forefront of the
democratization of reliable data. We call the new role which must be developed
to fill this critical need the Knowledge Scientist. The organizational
structures, tools, methodologies and techniques to support and make possible
the work of knowledge scientists are still in their infancy. As organizations
not only use data but increasingly rely on data, it is time to empower the
people who are central to this transformation.
