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QROWD - Because Big Data Integration is Humanly Possible

Total Cost €


EC-Contrib. €






Project "QROWD" data sheet

The following table provides information about the project.


Organization address
address: Highfield
postcode: SO17 1BJ

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website
 Total cost 3˙993˙505 €
 EC max contribution 2˙969˙367 € (74%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2016-1
 Funding Scheme IA
 Starting year 2016
 Duration (year-month-day) from 2016-12-01   to  2019-11-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
3    UNIVERSITA DEGLI STUDI DI TRENTO IT (TRENTO) participant 376˙625.00
4    ATOS SPAIN SA ES (MADRID) participant 336˙437.00
5    COMUNE DI TRENTO IT (TRENTO) participant 249˙375.00
6    INMARK EUROPA SA ES (MADRID) participant 219˙100.00
9    AI4BD GMBH CH (ZURICH) participant 0.00


 Project 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.


List of deliverables.
Benchmarking registry, reporting, and crowdsourcing monitoring tools Other 2020-03-24 10:50:12
Hackathon Other 2020-03-24 10:49:56
Final TomTom pilot Documents, reports 2020-03-24 10:50:06
Dynamic data integration, storage and access Documents, reports 2020-03-24 10:49:50
Integrated processing of data-in-motion and data-at-rest Demonstrators, pilots, prototypes 2020-03-24 10:49:45
Methods for task and time management Documents, reports 2020-03-24 10:49:22
Road information services Demonstrators, pilots, prototypes 2020-03-24 10:50:15
Business plans Documents, reports 2020-03-24 10:50:13
Linked Data generation framework Demonstrators, pilots, prototypes 2020-03-24 10:49:48
Link discovery and data fusion algorithms Open Research Data Pilot 2020-03-24 10:49:48
Data acquisition framework Demonstrators, pilots, prototypes 2020-03-24 10:49:24
Final Trento pilot Documents, reports 2020-03-24 10:50:28
iLog Demonstrators, pilots, prototypes 2020-03-24 10:50:12
Crowdsourcing vocabulary and licensing Open Research Data Pilot 2020-03-24 10:48:58
Spatio-temporal analytics Demonstrators, pilots, prototypes 2020-03-24 10:49:48
QROWD platform Demonstrators, pilots, prototypes 2020-03-24 10:49:49
Outreach report v2 Documents, reports 2020-03-24 10:50:20
Public endpoints and deployment Open Research Data Pilot 2020-03-24 10:49:24
Crowdsourced multilingual data harvesting and extraction framework Demonstrators, pilots, prototypes 2020-03-24 10:49:22
Ideas competition Other 2020-02-13 13:44:42
Data catalog Other 2020-02-13 13:44:41
Participatory framework Documents, reports 2020-02-13 13:44:40
Data management plan Open Research Data Pilot 2020-02-13 13:44:42
Data storage and access component Demonstrators, pilots, prototypes 2019-11-06 11:38:08
Urban mobility dashboard Demonstrators, pilots, prototypes 2019-11-06 11:38:08
Outreach report v1 Documents, reports 2019-11-06 11:38:08
Business case requirements and design Documents, reports 2019-11-06 11:38:08
Datasets Other 2019-11-06 11:38:08
Data quality assessment services Open Research Data Pilot 2019-11-06 11:38:08
Real-time inductive analysis Demonstrators, pilots, prototypes 2019-11-06 11:38:08
Requirements and architecture Documents, reports 2019-11-06 11:38:08
Online presence and brand guidelines Websites, patent fillings, videos etc. 2019-11-06 11:38:08
Exploitation strategy Documents, reports 2019-11-06 11:38:08
Crowdsourcing services Demonstrators, pilots, prototypes 2019-11-06 11:38:08

Take a look to the deliverables list in detail:  detailed list of QROWD deliverables.


year authors and title journal last update
List of publications.
2018 Maddalena, Eddy; Ibáñez, Luis-Daniel; Simperl, Elena; Zeni, Mattia; Bignotti, Enrico; Giunchiglia, Fausto; Stadler, Claus; Westphal, Patrick; Garcia, Luis P.F.; Lehmann, Jens
QROWD: Because Big Data Integration is Humanly Possible
published pages: , ISSN: , DOI: 10.5281/zenodo.3568169
2018 Westphal, Patrick; Fernández, Javier D.; Kirrane, Sabrina; Lehmann, Jens
SPIRIT: A Semantic Transparency and Compliance Stack
published pages: , ISSN: , DOI: 10.5281/zenodo.3567866
2018 Vougiouklis, Pavlos; Maddalena, Eddy; Hare, Jonathon; Simperl, Elena
How Biased Is Your NLG Evaluation?
published pages: , ISSN: , DOI: 10.5281/zenodo.3568173
Joint Proceedings SAD 2018 and CrowdBias 2018 2020-01-28
2018 Maddalena, Eddy; Ibáñez, Luis-Daniel; Simperl, Elena
On the mapping of Points of Interest through StreetView Imagery and paid crowdsourcing
published pages: , ISSN: , DOI: 10.5281/zenodo.3568200
2019 Patrick Westphal, Lorenz Bühmann, Simon Bin, Hajira Jabeen, Jens Lehmann
SML-Bench – A benchmarking framework for structured machine learning
published pages: 231-245, ISSN: 1570-0844, DOI: 10.3233/sw-180308
Semantic Web 10/2 2020-01-28
2019 Oluwaseyi Feyisetan, Elena Simperl
Beyond Monetary Incentives
published pages: 1-31, ISSN: 2469-7818, DOI: 10.1145/3321700
ACM Transactions on Social Computing 2/2 2020-01-28
2019 Stadler, Claus; Sejdiu, Gezim; Graux, Damian; Lehmann, Jens
Querying Large-scale RDF Datasets Using the SANSA Framework
published pages: , ISSN: , DOI: 10.5281/zenodo.3567886
Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) 2020-01-28
2018 F. Giunchiglia, E. Bignotti, and M. Zeni
Combining Crowdsourcing and Crowdsensing to Infer the Spatial Context
published pages: , ISSN: , DOI:
International Workshop on Context-Awareness for Multi-Device Pervasive and Mobile Computing 2019-11-06
2018 F. Giunchiglia, M. Zeni, E. Bignotti
Personal Context Recognition via Reliable Human-Machine Collaboration
published pages: , ISSN: , DOI:
Workshop on Information Quality and Quality of Service for Pervasive Computing 2019-11-06
2018 Fausto Giunchiglia, Enrico Bignotti, Mattia Zeni
Human-Like Context Sensing for Robot Surveillance
published pages: 129-148, ISSN: 1793-7108, DOI: 10.1142/s1793351x1840007x
International Journal of Semantic Computing 12/01 2019-11-06
2018 F. Giunchiglia, E. Bignotti, M. Zeni, and Wanyi Zhang
Assessing Consistency of in the wild Annotations
published pages: , ISSN: , DOI:
2nd International Workshop on Annotation of useR Data for UbiquitOUs Systems 2019-11-06
2018 Patrick Westphal Lorenz Bühmann Simon Bin Hajira Jabeen Jens Lehmann
SML-Bench -- A Benchmarking Framework for Structured Machine Learning
published pages: , ISSN: 1570-0844, DOI:
Semantic Web – Interoperability, Usability, Applicability 2019-11-06
2017 Fausto Giunchiglia, Mattia Zeni, Elisa Gobbi, Enrico Bignotti, Ivano Bison
Mobile Social Media and Academic Performance
published pages: 3-13, ISSN: , DOI: 10.1007/978-3-319-67256-4_1
2018 Claus Stadler, Muhammad Saleem, Axel-Cyrille Ngonga Ngomo, Jens Lehmann
Efficiently Pinpointing SPARQL Query Containments
published pages: 210-224, ISSN: , DOI: 10.1007/978-3-319-91662-0_16

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