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HORIZON-CL4-2021-DATA-01-...
HORIZON-CL4-2021-DATA-01-03: Technologies for data management (AI, Data and Robotics Partnership) (IA)
ExpectedOutcome:Proposal results are expected to contribute to the following expected outcomes:
Sólo fondo perdido 0 €
Europeo
Esta convocatoria está cerrada Esta línea ya está cerrada por lo que no puedes aplicar. Cerró el pasado día 21-10-2021.
Se espera una próxima convocatoria para esta ayuda, aún no está clara la fecha exacta de inicio de convocatoria.
Por suerte, hemos conseguido la lista de proyectos financiados!
Presentación: Consorcio Consorcio: Esta ayuda está diseñada para aplicar a ella en formato consorcio..
Esta ayuda financia Proyectos:

ExpectedOutcome:Proposal results are expected to contribute to the following expected outcomes:

provide new secure and energy-efficient data management tools improving the usability and discoverability of data in different contexts, covering data provenance, synthetic data generation, data quality management (such as data cleaning, validation, enrichment, co-creation, identification of bias and correlations), improving data interoperability, metadata management (automated ways of labelling and describing data, data linkage), and ensuring data security, privacy and integrity, especially in the context of data spaces.
Scope:The actions under this topic are expected to provide practical, robust and scalable tools to improve the interoperability, quality, and integrity of data and metadata, in the context of other topics of the heading “Data sharing in the common European data space”. The data management tools and systems should support a holistic approach of the data life cycle and comply with accountability, fairness and confidentiality as well as the FAIR principles (Findable, Accessible, Interoperable, Reusable) for data and metadata management. Building on resu... ver más

ExpectedOutcome:Proposal results are expected to contribute to the following expected outcomes:

provide new secure and energy-efficient data management tools improving the usability and discoverability of data in different contexts, covering data provenance, synthetic data generation, data quality management (such as data cleaning, validation, enrichment, co-creation, identification of bias and correlations), improving data interoperability, metadata management (automated ways of labelling and describing data, data linkage), and ensuring data security, privacy and integrity, especially in the context of data spaces.
Scope:The actions under this topic are expected to provide practical, robust and scalable tools to improve the interoperability, quality, and integrity of data and metadata, in the context of other topics of the heading “Data sharing in the common European data space”. The data management tools and systems should support a holistic approach of the data life cycle and comply with accountability, fairness and confidentiality as well as the FAIR principles (Findable, Accessible, Interoperable, Reusable) for data and metadata management. Building on results of relevant past and current initiatives, data management tools, systems and processes are expected to enable, support and/or automate the creation and maintenance of common ontologies, vocabularies and data models and/or structured, standardised and automated authoring, co-creation, curation, annotation and labelling of data, in view of different later uses (especially AI) made of the data. The actions are expected to create links with relevant initiatives collecting/using heterogeneous/linguistic data, including AI initiatives (such as AI4EU, European Language Grid, or the projects from the H2020 topic ICT-48), and liaise with standardization bodies, where appropriate.

Actions are expected to deal with gaps and needs identified in real-world data space management and real-world data heterogeneity challenges (encoding formats, multiple languages, collection mechanisms, access methods, etc.), supporting, where necessary, hybrid/adaptive approaches and models, leading to robust, reliable and automated annotation of unstructured data sources. The tools should contribute to minimization of the energy footprint, be adaptable to different user needs and support and encourage new business models and (where appropriate) citizen involvement and social innovation. The tools should be demonstrated by diverse use cases. Provision of open source tools is encouraged to contribute to outreach and impact.

In this topic the integration of the gender dimension (sex and gender analysis) in research and innovation content is not a mandatory requirement.

This topic implements the co-programmed European Partnership on Artificial Intelligence, Data and Robotics.


Specific Topic Conditions:Activities are expected to start at TRL 5 and achieve TRL 8 by the end of the project – see General Annex B.




Cross-cutting Priorities:Social InnovationCo-programmed European PartnershipsArtificial IntelligenceDigital Agenda


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Temáticas Obligatorias del proyecto: Temática principal:

Características del consorcio

Ámbito Europeo : La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Tipo y tamaño de organizaciones: El diseño de consorcio necesario para la tramitación de esta ayuda necesita de:

Características del Proyecto

Requisitos de diseño: Duración:
Requisitos técnicos: ExpectedOutcome:Proposal results are expected to contribute to the following expected outcomes: ExpectedOutcome:Proposal results are expected to contribute to the following expected outcomes:
¿Quieres ejemplos? Puedes consultar aquí los últimos proyectos conocidos financiados por esta línea, sus tecnologías, sus presupuestos y sus compañías.
Capítulos financiables: Los capítulos de gastos financiables para esta línea son:
Personnel costs.
Subcontracting costs.
Purchase costs.
Other cost categories.
Indirect costs.
Madurez tecnológica: La tramitación de esta ayuda requiere de un nivel tecnológico mínimo en el proyecto de TRL 6:. Representa un paso importante en demostrar la madurez de una tecnología. Se construye un prototipo de alta fidelidad que aborda adecuadamente las cuestiones críticas de escala, que opera en un entorno relevante, y que debe ser a su vez una buena representación del entorno operativo real. + info.
TRL esperado:

Características de la financiación

Intensidad de la ayuda: Sólo fondo perdido + info
Fondo perdido:
0% 25% 50% 75% 100%
Para el presupuesto subvencionable la intensidad de la ayuda en formato fondo perdido podrá alcanzar desde un 70% hasta un 100%.
The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities. The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities.
Garantías:
No exige Garantías
No existen condiciones financieras para el beneficiario.

Información adicional de la convocatoria

Efecto incentivador: Esta ayuda no tiene efecto incentivador. + info.
Respuesta Organismo: Se calcula que aproximadamente, la respuesta del organismo una vez tramitada la ayuda es de:
Meses de respuesta:
Muy Competitiva:
No Competitiva Competitiva Muy Competitiva
No conocemos el presupuesto total de la línea
Minimis: Esta línea de financiación NO considera una “ayuda de minimis”. Puedes consultar la normativa aquí.

Otras ventajas

Sello PYME: Tramitar esta ayuda con éxito permite conseguir el sello de calidad de “sello pyme innovadora”. Que permite ciertas ventajas fiscales.