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Replicability and reproducibility (R&R) are critical for the long-termprosperity of a scientific discipline. In GIScience, researchers have discussedR&R related to different research topics and problems, such as local spatialstatistics, digital earth, and metadata (Fotheringham, 2009; Goodchild, 2012;Anselin et al., 2014). This position paper proposes to further support R&R bybuilding benchmarking frameworks in order to facilitate the replication ofprevious research for effective and effcient comparisons of methods andsoftware tools developed for addressing the same or similar problems.Particularly, this paper will use geoparsing, an important research problem inspatial and textual analysis, as an example to explain the values of suchbenchmarking frameworks.

Building benchmarking frameworks for supporting replicability and reproducibility: spatial and textual analysis as an example