Terabytes of Tobler: Evaluating the First Law in a Massive, Domain-Neutral Representation of World Knowledge

Abstract. The First Law of Geography states, “everything is related to everything else, but near things are more related than distant things. ” Despite the fact that it is to a large degree what makes “spatial special, ” the law has never been empirically evaluated on a large, domain-neutral representation of world knowledge. We address the gap in the literature about this critical idea by statistically examining the multitude of entities and relations between entities present across 22 different language editions of Wikipedia. We find that, at least according to the myriad authors of Wikipedia, the First Law is true to an overwhelming extent regardless of language-defined cultural domain

Addressing quality issues of historical GIS data: An example of Republican Beijing

This article addresses several issues related to historical GIS data using a project studying the social culture of Republican Beijing as an illustration. For large-scale historical GIS projects, certain data layers or themes are fundamental to and provide the context for various types of investigation. We suggested that these data may be regarded as framework data, similar to the concept of the core dataset identified in the US National Spatial Data Infrastructure (NSDI) framework, but in a GIS project context. Due to various reasons, most historical GIS data always invite concerns about their quality. We discussed how typical spatial data quality concepts are partially applicable to historical GIS data. We also highlighted the data quality aspects that are more significant to historical than contemporary GIS data. Compiling high-quality historical GIS data is challenging. We used the data layer of temple locations as an example to illustrate the process of using a set of principles to resolve the inconsistencies of data from multiple sources to deal with location accuracy and data completeness problems. Two common but related quality concerns of historical GIS data are their relatively low spatial resolution and imprecise locations. The original population dataset of Republican Beijing suffers from these two issues. Using ancillary data, more precise population locations and population distribution at a higher resolution were estimated. Compilation of historical GIS data requires fusing data of different sources in order to enhance the quality of the data. © 2012 Taylor and Francis Group, LLC

Comparing expert and non-expert conceptualisations of the land: An analysis of crowdsourced land cover data

This research compares expert and non-expert conceptualisations of land cover data collected through a Google Earth web-based interface. In so doing it seeks to determine the impacts of varying landscape conceptualisations held by different groups of VGI contributors on decisions that may be made using crowdsourced data, in this case to select the best global land cover dataset in each location. Whilst much other work has considered the quality of VGI, as yet little research has considered the impact of varying semantics and conceptualisations on the use of VGI in formal scientific analyses. This study found that conceptualisation of cropland varies between experts and non-experts. A number of areas for further research are outlined