Innovating Works

H2020

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HORIZON-CL4-2022-DATA-01-...
HORIZON-CL4-2022-DATA-01-01: Methods for exploiting data and knowledge for extremely precise outcomes (analysis, prediction, decision support), reducing complexity and presenting insights in understandable way (RIA)
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 05-04-2022.
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:

Improving automated ways for extracting meaning and providing insights from data extremely fast and/or accurately in order to optimize decision making (ranging from crisis/emergency management to predictive maintenance) or action planning, as well as demonstrating how these improvements can have great positive impacts for society, people, economy, or the environment
Scope:The actions under this topic are expected to exploit “extreme data”: (defined as data that exhibits one or more of the following characteristics, to an extent that makes current technologies fail: increasing volume, speed, variety; complexity/diversity/multilinguality of data; the dispersed data sources; sparse/missing/insufficient data/extreme variations in values) to push the frontiers of analytics, prediction, simulation and visualisation to provide extremely precise, timely and useful results from data and knowledge, to support (human or automated) decision-making, saving lives or otherwise providing great positive impact (economic, societal, environmental) compared to traditional methods of dec... ver más

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

Improving automated ways for extracting meaning and providing insights from data extremely fast and/or accurately in order to optimize decision making (ranging from crisis/emergency management to predictive maintenance) or action planning, as well as demonstrating how these improvements can have great positive impacts for society, people, economy, or the environment
Scope:The actions under this topic are expected to exploit “extreme data”: (defined as data that exhibits one or more of the following characteristics, to an extent that makes current technologies fail: increasing volume, speed, variety; complexity/diversity/multilinguality of data; the dispersed data sources; sparse/missing/insufficient data/extreme variations in values) to push the frontiers of analytics, prediction, simulation and visualisation to provide extremely precise, timely and useful results from data and knowledge, to support (human or automated) decision-making, saving lives or otherwise providing great positive impact (economic, societal, environmental) compared to traditional methods of decision making. Integrity and ethical aspects of the outcomes should be in line with the principles of responsible/trustworthy AI. The use of European data sources (such as Copernicus, Galileo/EGNOS for satellite data) is encouraged in the use cases, where appropriate. Analytics should be transparent, trustworthy, flexible, fit for the purpose and user needs, intuitive and (when necessary) provided as efficient and scalable “Analytics-as-a-Service”, including, where appropriate, federated analytics on distributed/decentralized data. Prediction should be extremely precise and/or span over longer time period and/or account for uncertainty factors. Simulation should allow precise replication and modelling of the real phenomenon or system (generating accurate synthetic data, when appropriate), with minimal differences and/or minimize the footprint/cost of the simulation model while generating useful data (considering context), exploiting augmented reality when appropriate. Actions should consider quality standards and assessment criteria for data generated by simulation. Visualisation should be interactive (and facilitate human interaction and collaboration), intuitive, accessible and allow people (with different needs, interests and backgrounds) to understand complex phenomena by smart selection of parameters, anticipation of user needs/interest and by novel ways of combining visual and non-visual elements and/or augmented reality.

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


Specific Topic Conditions:Activities are expected to start at TRL 2-3 and achieve TRL 4-5 by the end of the project – see General Annex B.




Cross-cutting Priorities:Artificial 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 4:. Es el primer paso para determinar si los componentes individuales funcionarán juntos como un sistema en un entorno de laboratorio. Es un sistema de baja fidelidad para demostrar la funcionalidad básica y se definen las predicciones de rendimiento asociadas en relación con el entorno operativo final. + 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 como minimo un 100%.
The funding rate for RIA projects is 100 % of the eligible costs for all types of organizations. The funding rate for RIA projects is 100 % of the eligible costs for all types of organizations.
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.