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CORDIS

QROWD - Because Big Data Integration is Humanly Possible

Objective

Big Data integration in European cities is of utmost importance for municipalities and companies to offer effective information services, enable efficient data-driven transportation and mobility, reduce CO2 emissions, assess the efficiency of infrastructure, as well as enhance the quality of life of citizens. At present this integration is substantially limited due to the following factors: 1) Urban Big Data is locked in isolated industrial and public sectors, and 2) The actual Big Data integration is an extremely hard technical problem due to the heterogeneity of data sources, variety of formats, sizes, quality as well as update rates, such that the integration requires significant human intervention.

QROWD addresses these challenges by offering methods to perform cross-sectoral streaming Big Data integration including geographic, transport, meteorological, cross domain and news data, while capitalizing on human feedback channels. The main objectives of QROWD are: (1) Facilitating cross-sectoral Big Data stream integration for urban mobility including real-time data on individual and public transportation combined with further available sources, such as weather conditions and infrastructure information to create a comprehensive overview of the city traffic; (2) Supporting participation and feedback of various stakeholder groups to foster data-driven innovation in cities; and (3) Building a platform providing hybrid computational methods relying on efficient algorithms complemented with human computation and feedback.

The main outcomes of QROWD are: (1) Two data value chains in the sectors of urban mobility and public transportation using a mix of large scale heterogeneous multilingual datasets; and (2) Cross-sectoral and cross-lingual technology, including algorithms and tools covering all phases of the cross-sectoral Big Data Value Chain building on W3C standards and capitalizing on a flexible and efficient combination of human and machine-based computation.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

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Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

IA - Innovation action

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-ICT-2016-2017

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Coordinator

UNIVERSITY OF SOUTHAMPTON
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 651 504,99
Address
Highfield
SO17 1BJ Southampton
United Kingdom

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Region
South East (England) Hampshire and Isle of Wight Southampton
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 651 504,99

Participants (10)

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