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ScienceGraph

Financiado

Knowledge Graph based Representation Augmentation and Exploration of Scholarly...

Knowledge Graph based Representation Augmentation and Exploration of Scholarly Communication Despite an improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. The document-oriented workflows i... ver más

30/04/2024

LUH

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOV... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 4 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-04-30

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2018-COG: ERC Consolidator Grant

I+D

Cerrada hace 6 años

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4 Participantes

LUH

1.38M€ | Lider

FRIMANCHA INDUSTRIAS CARNICA...

343.92K€ | Participante

TIB

447.00K€ | Participante

INFAI

167.50K€ | Participante

Últimas noticias

29-11-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

29-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 2 concesiones

29-11-2024: CMVAMADRID En las últimas 48 horas el Organismo CMVAMADRID ha otorgado 37 concesiones

Duración del proyecto: 62 meses Fecha Inicio: 2019-02-25
Fecha Fin: 2024-04-30

Presupuesto del proyecto 2M€

Descripción del proyecto Despite an improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. The document-oriented workflows in science have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis. In ScienceGRAPH we aim to develop a novel model for representing, analysing, augmenting and exploiting scholarly communication in a knowledge-based way by expressing and linking scientific contributions and related artefacts through semantically rich, interlinked knowledge graphs. The model is based on deep semantic representation of scientific contributions, their manual, crowd-sourced and automatic augmentation and finally the intuitive exploration and interaction employing question answering on the resulting ScienceGRAPH base. Currently, knowledge graphs are still confined to representing encyclopaedic, factual information. ScienceGRAPH advances the state-of-the-art by enabling to represent complex interdisciplinary scientific information including fine-grained provenance preservation, discourse capture, evolution tracing and concept drift. Also, we will demonstrate that we can synergistically combine automated extraction and augmentation techniques, with large-scale collaboration to reach an unprecedented level of knowledge graph breadth and depth. As a result, we expect a paradigm shift in the methods of academic discourse towards knowledge-based information flows, which facilitate completely new ways of search and exploration. The efficiency and effectiveness of scholarly communication will significant increase, since ambiguities are reduced, reproducibility is facilitated, redundancy is avoided, provenance and contributions can be better traced and the interconnections of research contributions are made more explicit and transparent.

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