This paper reflects on a number of trends towards a more open and reproducible approach
to geographic and spatial data science over recent years. In particular, it considers trends …

… (such as writing base code or guiding data collection). Under current … reproducibility is
hampered by honest errors, one promising alternative is to provide prepublication code and data …

… The researcher’s documentation of their work allows the research community to “check the
work” of the individual researcher, identify flaws, and even find new insights using open data. …

… with the aspirations, methods, and advances in statistics and operations research, and
we get the field of data science, which broadly aims to extract insights or conclusions from …

… making modeling better and more trustworthy. (Establishing logical … we could re-frame scientific
reproducibility as a triangulation … and social studies of science, in addition to the sciences …

… concept of assessable reproducible research artifacts and point … rigor, and trustworthiness
of published computational research. … and detailed observations and insights are central to the …

… Insights from the open science movement can help … to honest and transparent specification
of all steps in the data … previously, open data allows different forms of reproducibility analyses. …

… on, and potentially limited insight into how data was collected. Accordingly, … data scientists
willing to engage in HARKing only need to look for patterns in data sets (also called data …

… to extract knowledge, make decisions, discover new insights, and reveal new phenomena
from data. The concept of data science has appeared in the literature for several decades and …

… for social justice, transparency, and trustworthy science should … forward as critical thinkers
and thoughtful researchers. In a … studies to provide a foundation for rigor, reproducibility, and …