
This work introduces GeoChangesQA, a novel spatiotemporal QA dataset for historical geospatial knowledge. We first developed the Historical County Boundaries Ontology (HCB-O) to create this dataset. Then, we leveraged geospatial historical data spanning regions in the United States from 1630 to 2000 to populate the novel Historical CountyBoundaries Knowledge Graph (HCB-KG). Subsequently, we developed a semi-automated procedure for generating questions, GeoSPARQL queries, and corresponding answers over HCB-KG by leveraging subgraph and query template extraction techniques. Through this method, we automatically generated 8, 900 question-query-answer triples. The code used to create this dataset is available here: github repo The knowledge graph (rdf dumps) which the queries refer to is available here: DOI 10.5281/zenodo.11508198 // Knowledge Graph
Columns Description: Subgraph ID: Unique Subgraph type id SparqlQuery: The SPARQL query Questions: The Question after replacing Uris_match with template variables Sample Answer: One sample answer to the SPARQL query Question_Templates: Subgraph ID: Unique Subgraph type id Graph: The graph schema for every Subgraph ID Questions Templates: A list with every question template
New Version4 Updates: More queries-questions-answers pairs were produced. The dataset contains around 8900 examples Corrections on question templates Update KG
semantic knowledge, Knowledge Graphs, SPARQL, NLP
semantic knowledge, Knowledge Graphs, SPARQL, NLP
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
