Critical knowledge geographies of the geospatial semantic web – exploring social dimensions of Wikidata

The semantic web of interlinked data sources has become an integral element of our digital information ecosystem. In the semantic web, knowledge is being “datafied” into highly formalized and factual information pieces that can be processed, computed and recombined across different contexts and application scenarios. A significant part of the semantic web comprises geographical knowledge, i.e. semantic data about places and spaces. This geospatial semantic web represents a shift in how we produce, organize and acquire geographical knowledge, which is being segmented into a myriad of semantically structured machine-readable spatial data points. However, in a datafied form, knowledge loses context, nuance and provenance and end users of semantic web services, like search engines for example, can hardly assess the biases and partialities inherent to the results they are confronted with. Thus, while the geosemantic web is becoming an ever more seamless digital infrastructure, we still know little about the contingent social production contexts of semantic data.

Drawing on literature from the fields of critical knowledge geographies and digital geographies, this project intends to open a critical perspective onto the geospatial semantic web. In particular, it aims to explore the social dimensions of the geo-knowledge base Wikidata – a universal, highly dynamic, freely editable, semantic database of factual knowledge which is currently evolving into a core component of the semantic web’s architecture.

Blogeinträge zu diesem Forschungsprojekt

  • Mapping geosemantics - In Wikidata, different knowledge items are interrelated through properties in countless semantic statements. For example: “Germany‘s capital is currently Berlin“; “Berlin‘s head of government is currently Michael Müller“; “Michael Müller is a member of the Social Democratic Party of Germany” (SPD); “the SPD‘s headquaters location is the  Willy-Brandt-Haus; “the  Willy-Brandt-Haus has a coordinate location of 52°30’N, […]
  • First macro analyses of spatial content in wikidata - Through, our self-hosted Wikidata database we can perform large-scale queries of geographic content in Wikidata and check some spatial distributions. Places of worship, for example can be queried through this SPARQL query: (you can test the query here) # all instances of places of worship (or of subclasses), with coordinates SELECT ?item ?itemLabel ?coords WHERE […]
  • Wikidata database prototype successfully set up - With kind assistance by the GeoDatenZentrum, I have managed to set up a prototype of a self-hosted Blazegraph database on a Linux server and populate it with a Wikidata dump file from 6.11.2017. I was basically following the instructions on . The import took the virtual machine (64GB RAM, 4 cores, TB) about three […]