In the first six months, we conducted preparatory actions and reviewed literature on geoQA, AI, Linguistics, and GIScience. In Year 1, we performed a systematic survey of geo-analytic questions answerable with GIS workflows (WP1), generating the GeoAnQu corpus with 429 example questions from academic sources, which forms the empirical foundation and gold standard for evaluation (WP5.1).
In Year 2, we developed a geo-analytic question grammar (WP2), capturing question patterns, formalizing them based on interrogative concepts, and enabling concept transformations. The grammar was tested on the corpus and online sources, forming the basis for a query interface.
We also developed a conceptual model of information components for geo-analytic QA (WP3/5). The Core Concept Data Types (CCD) ontology enables automatic workflow composition using tools and geodata, successfully tested in GIS workflow studies. Annotations support our data/tool repository (WP4).
The Core Concept Transformation (CCT) algebra was created to interpret geo-analytical questions as concept transformations for querying workflows, and we explored amounts in Geography. CCT is being implemented as a Python library.
In Year 2, User Study 1 (WP1.3) evaluated GIS workflow design with 40 participants. Despite delays due to the pandemic, this study provided valuable insights for automation and informed the gold standard.
In Year 3, User Study 2 (WP4.2) assessed the usability and interpretability of the GeoQA grammar and Blockly interface, leading to refinements based on participant feedback. User Study 3 (WP4.3) tested human analysts’ ability to recognize core concepts in geographic tasks, validating the CCD ontology and guiding its improvement.
In Year 4, User Study 4 (WP5.2) was intended to evaluate the full technology stack, but due to incomplete prototype development, we instead conducted a cognitive map interpretation survey, essential for the project’s progress.
A retrieval and query study (Steenbergen et al., 2023) also evaluated the technology stack, testing the ability of the GeoQA grammar, CCD ontology, and CCT algebra to retrieve workflows and data based on geo-analytical questions. Results confirmed the system’s effectiveness in automating workflow composition and data retrieval.
The detailed outcomes of these studies validate the GeoQA framework’s feasibility and practical utility in advancing geographic question-answering and spatial analytics.
