In the age of big data, geographic information has become a central means for data scientists of various disciplines to embed their analysis into a spatio-temporal context, from human mobility patterns and social inequality to the investigation of personal health. However, as the variety of data sources and software available on the Web increases, it becomes more and more impossible to comprehend and utilize all tools and data available to answer geo-analytical questions. Hence, whenever a functionality is needed but not available in one tool, analysts are forced to reformulate their questions in terms of technicalities of another tool or other datasets. This procedure does not scale with the increasing variety of geo-analytic sources on the web, preventing analysts from tapping its full potential. Consider, in contrast, how easy it is for a user of a digital smartphone assistant such as Amazon's Alexa to ask a question like "What is the weather today?" and get back an answer from the Web. It would mean a tremendous breakthrough if analysts could similarly ask questions in order to get the tools and data required to answer them. Unfortunately, geo-analytic technology currently cannot handle questions.
To realize this vision, it is necessary to understand how geo-analytic resources can be captured with the questions they answer. The QuAnGIS project, a 5-year research project at Utrecht University, starting in January 2019 funded by the European Research Commission (ERC), develops a theory about interrogative spatial concepts needed to turn geo-analytical questions into a machine-readable form using Semantic Web and Question-Answering (QA) technology. Concepts include "spatial core concepts" field, object, network, event (Kuhn 2012), as well as analytical concepts such as accessibility, exposure, density, distance and aggregation. In this form, questions can be matched with the capacity of major analytical GIS tools and data sources on the Web.
The 2 PhD positions in this project focus on the semantic concepts required and the information technology needed to enable GIS analysts to formulate questions and to retrieve resources for analysis. This involves the following two questions:
PhD 1: How can geo-analytical questions be captured in terms of semantic queries in a machine readable way? This involves an ontological investigation into spatial concepts and geo-analytical questions in project scenarios and literature, into the expressiveness of query languages, as well as into technical interfaces to let users formulate spatial questions for analysis.
PhD 2: How can the intention of geo-analytical resources (data and tools) be described in terms of the questions they answer? This involves an investigation into GIS tools and their functionality in terms of spatial concepts, as well as standard web data sources, and how both can be linked using semantic concepts. The purpose is to build an integrated extensible Web repository about analytical tools and data sources.
Important tasks of the PhD candidates are:
conducting scientific research in the fields of Geospatial Semantics, Geographic Information Science, Ontology Engineering, and Semantic Web relevant to handling spatial questions and analytic resources;
collection and semantic description of geographic information scenarios for developing a gold standard of question-answers as well as analytic (web) resources for geospatial analysis (filling web repository with content);
perform user studies for specifying test scenarios and for testing both the question formulation interface as well as the tool/data repository with geospatial analysts;
publication of results in scientific journals and presentation in high quality international conferences in these fields;
organizing multi-stakeholder meetings and workshops to test and discuss the technology;
to develop teaching skills, students are also expected to contribute to the teaching programme of the Department of Human Geography and Spatial Planning to a limited degree (up to 10%).
Your responsibilities are:
start with the project in February or later in 2019;
meet the goals/deadlines as set out in the project proposal;
complete a PhD thesis within the 4-year contract period.
