NOESIS | NOvel Decision Support tool for Evaluating Strategic Big Data investments in Transport and Intelligent Mobility Services

Summary
NOESIS project will identify the critical factors/features which lead to successful implementation of Big Data technologies and services in the field of transport and logistics with significant value generation from a socioeconomic viewpoint. This will be achieved through the examination of areas and contexts throughout Europe, in which ICT investments and exploitation of data should be implemented. The impact of Big Data will be evaluated in a series of transportation use cases (Big Data in Transport Library) by developing and applying a ‘Learning framework’ and a Value Capture mechanism which will estimate the expected benefits and costs.
Unfold all
/
Fold all
More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/769980
Start date: 01-11-2017
End date: 31-10-2019
Total budget - Public funding: 1 197 831,25 Euro - 1 197 831,00 Euro
Cordis data

Original description

NOESIS project will identify the critical factors/features which lead to successful implementation of Big Data technologies and services in the field of transport and logistics with significant value generation from a socioeconomic viewpoint. This will be achieved through the examination of areas and contexts throughout Europe, in which ICT investments and exploitation of data should be implemented. The impact of Big Data will be evaluated in a series of transportation use cases (Big Data in Transport Library) by developing and applying a ‘Learning framework’ and a Value Capture mechanism which will estimate the expected benefits and costs.

Status

CLOSED

Call topic

MG-8-2-2017

Update Date

27-10-2022
Images
No images available.
Geographical location(s)
Structured mapping
Unfold all
/
Fold all
Horizon 2020
H2020-EU.3. SOCIETAL CHALLENGES
H2020-EU.3.4. SOCIETAL CHALLENGES - Smart, Green And Integrated Transport
H2020-EU.3.4.0. Cross-cutting call topics
H2020-MG-2017-SingleStage-INEA
MG-8-2-2017 Big data in Transport: Research opportunities, challenges and limitations