Objective
Social Sciences and Humanities (SSH) provide essential knowledge to society, informing our shared cultural, economical and ethical decisions. However, SSH knowledge remains largely disconnected and poorly available, impeding its full potential in research and societal applications. The GRAPHIA project aims to build the first comprehensive SSH Knowledge Graph (KG) that integrates currently disconnected data into a single entry point, leveraging existing infrastructure and data resources. GRAPHIA aspires to significantly improve SSH data visualisation and analysis capacities, pioneer advanced AI solutions tailored for SSH and develop re-usable, cutting-edge digital tools. GRAPHIA addresses the unique opportunities posed by the qualitative, diverse and context-rich data typical of SSH research where existing solutions fall short. GRAPHIA's innovative approach, centered around the KG, provides an expansive representation of SSH knowledge, while leveraging AI for its enrichment, access and deeper analysis, including an LLM4SSH. GRAPHIA aims to empower researchers to uncover patterns and insights from unstructured data, illuminating social phenomena and cultural trends with unprecedented clarity. A key component of GRAPHIA is the SSH Citation Index, an innovative framework for citation data extraction and enrichment across all SSH disciplines that dramatically speeds up access and understanding of previous literature on any topic. GRAPHIA transcends traditional research approaches by integrating industry partners into a cohesive partnership, which is pivotal to amplify the project's impact, drive forward innovations that are not only academically significant but also commercially viable, provide access to new markets and technologies and foster an environment of co-innovation. GRAPHIA is committed to open science and increasing EU Research Infrastructures capabilities, enhancing global competitiveness, while facilitating broad and long-lasting impact of project results.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Keywords
Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
1000 BRUXELLES
Belgium
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Participants (19)
00185 Roma
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75794 Paris
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2121 Nicosia
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34000 MONTPELLIER
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
92130 Issy Les Moulineaux
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
56017 SAN GIULIANO TERME
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
68159 Mannheim
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00-330 Warszawa
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111 20 Stockholm
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1050 Bruxelles / Brussel
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1011 JV AMSTERDAM
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3000 Leuven
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56124 Pisa
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
2595 BE Den Haag
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61-704 POZNAN
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30167 Hannover
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40126 Bologna
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DD1 1HG Dundee
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30167 Hannover
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Partners (1)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
1003 Lausanne
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.