Building benchmarking frameworks for supporting replicability and reproducibility: spatial and textual analysis as an example
It addresses replicability issues for GIScience researchers, but is incremental as it builds on existing discussions.
This position paper tackles the problem of replicability and reproducibility in GIScience by proposing benchmarking frameworks, using geoparsing as an example to facilitate method and tool comparisons.
Replicability and reproducibility (R&R) are critical for the long-term prosperity of a scientific discipline. In GIScience, researchers have discussed R&R related to different research topics and problems, such as local spatial statistics, digital earth, and metadata (Fotheringham, 2009; Goodchild, 2012; Anselin et al., 2014). This position paper proposes to further support R&R by building benchmarking frameworks in order to facilitate the replication of previous research for effective and effcient comparisons of methods and software tools developed for addressing the same or similar problems. Particularly, this paper will use geoparsing, an important research problem in spatial and textual analysis, as an example to explain the values of such benchmarking frameworks.