Descripción del proyecto
Un nuevo enfoque de la comunicación académica
El acceso a las publicaciones científicas ha ido mejorando con la introducción de la tecnología digital y la inteligencia artificial. Desgraciadamente, los procedimientos tradicionales usados en la comunicación académica, basados en flujos de trabajo centrados en documentos, no pueden responder al rápido aumento de la bibliografía académica. Con ayuda de expertos en la materia, la interconexión de datos y algoritmos de aprendizaje automático, se está desarrollando un nuevo gráfico de conocimientos. El proyecto financiado con fondos europeos ScienceGraph desarrollará una revolucionaria fórmula para representar, analizar, expandir y aprovechar la comunicación académica basándose en los conocimientos. Expresará y vinculará los resultados científicos mediante gráficos de conocimientos interrelacionados y de gran riqueza semántica que permitirán la representación de información científica interdisciplinaria compleja, el rastreo de toda su evolución, un discurso conectado y el cambio de conceptos.
Objetivo
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.
Ámbito científico
Programa(s)
Régimen de financiación
ERC-COG - Consolidator GrantInstitución de acogida
30167 Hannover
Alemania