In many applications, the management of geographic knowledge is very important (e.g., travel planning, urban and environmental planning, territorial intelligence etc.). The widespread adoption of digital technology coupled with management, storage and analysis of very large spatial data sets effectively has opened a new door for research. Storing and Indexing geospatial data, doing business intelligence over it, querying etc. are major challenges that have emerged in this domain. The majority of system which support geospatial queries over the Web of Data take as input GeoSPARQL queries. But most of the users may not be able to write GeoSPARQL queries as they are not experts. ESR3 is working on answering geospatial questions asked by users in natural language. The question answering system will then convert these questions into GeoSPARQL queries and return results to the user. The system developed by ESR3 will be part of the Qanary framework.



Towards an Integrated Graph Algebra for Graph Pattern Matching with Gremlin. Harsh Thakkar, Dharmen Punjani, Sören Auer, and Maria-Esther Vidal. DEXA (1) 2017: 81-91. URL PDF

QAestro–semantic-based composition of question answering pipelines. Kuldeep Singh, Ionna Lytra, Maria Esther-Vidal, Dharmen Punjani, Harsh Thakkar, Christoph Lange, Sören Auer. DEXA 2017: 19-34 URL PDF