Project description
AI answers geographic questions
Geographic information systems (GIS) play a crucial role in answering complex spatial questions across various scientific domains. The rise of AI in geography and geoscience has raised hopes that geographic data could be easily reused without requiring technical GIS expertise. Geographic question-answering (GeoQA) methods, which allow users to query spatial data using natural language, are particularly promising. However, many geographic questions demand more than retrieving stored maps – they require the dynamic transformation of data to generate new maps. In this context, the ERC-funded GeoTrAnsQData project is pioneering an approach that enables AI to interpret spatial questions in terms of analytical transformations. Overall, it will empower scientists to quantify geographic phenomena through natural language-driven map generation.
Objective
Geographic information systems (GIS) and corresponding data sources are of major importance for answering the questions posed by data scientists from various domains of application. The recent trend of adopting Artificial Intelligence (AI)-based methods in Geography and Geoscience has spurred hopes that geographic information can be successfully reused across disciplines without requiring the technical skills of GIS. In this context, geographic question-answering (GeoQA) methods are particularly promising because they enable users without a technical background to answer their questions about geographic space using natural language. However, most geographic questions data scientists may want to answer require some form of geo-analytical transformation of maps. Answer maps need to be (re)generated from data, rather than retrieved from storage. In contrast, stored maps are frequently lacking, outdated, biased, or of insufficient quality. For example, instead of retrieving statistical facts about noise intensity in a city, we might want to know about the coverage of noisy areas in this city. Yet, while the latter map might not be readily available, it could be generated from available sources. State-of-the-art factoid-based GeoQA methods are insufficient for this purpose because they directly match questions to facts, skipping over the problem of how unknown answers may be generated from these sources. In this project, we will develop an entirely novel paradigm for data-based question-answering, called transformative GeoQA, including a theory of geo-analytical transformations. The latter not only allows us to interpret questions in terms of the procedures for answering them but also to describe geodata as a source or purpose of a transformation. In GeoTrAnsQData, we lay the methodical and theoretical foundations for a groundbreaking data ecosystem that enables the quantification of geographic phenomena by generating maps using natural language.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences earth and related environmental sciences physical geography cartography geographic information systems
- natural sciences biological sciences ecology ecosystems
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3584 CS Utrecht
Netherlands
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