#	Pagina
attuale pagina	/open-h2020/projects/199839/index.html

Opendata, web and dolomites

PROTEUS SIGNED

Scalable online machine learning for predictive analytics and real-time interactive visualization

Total Cost €

EC-Contrib. €

Partnership

Views

Outcomes and
results

PROTEUS project word cloud

Explore the words cloud of the PROTEUS project. It provides you a very rough idea of what is the project "PROTEUS" about.

gap steelmaking applicable time deal interactive scalable online validating manifold industrial visualization enrichment proteus big apache outcome ready reducing architectures library original economic strategies validation streams version extremely form velocity scalability data platform scientific massive enhanced machine algorithms flink visualisation considering dependency predictive portable mission domains stream job analytic hybrid batch enhancement skills learning contributions visual responsiveness techniques setting computation analytics strategic world industry streaming area flexible fundamental empowering positions

Project "PROTEUS" data sheet

The following table provides information about the project.

Coordinator	BOURNEMOUTH UNIVERSITY Organization address address: FERN BARROW BOURNEMOUTH UNIVERSITY city: POOLE postcode: BH12 5BB website: www.bournemouth.ac.uk 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	http://www.proteus-bigdata.com
Total cost	3˙156˙525 €
EC max contribution	3˙156˙525 € (100%)
Programme	1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
Code Call	H2020-ICT-2015
Funding Scheme	RIA
Starting year	2015
Duration (year-month-day)	from 2015-12-01 to 2018-11-30

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	BOURNEMOUTH UNIVERSITY BOURNEMOUTH UNIVERSITY Organization address address: FERN BARROW BOURNEMOUTH UNIVERSITY city: POOLE postcode: BH12 5BB website: www.bournemouth.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (POOLE)	coordinator	627˙774.00
2	DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH Organization address address: TRIPPSTADTER STRASSE 122 city: KAISERSLAUTERN postcode: 67663 website: www.dfki.de contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	DE (KAISERSLAUTERN)	participant	1˙035˙750.00
3	TREELOGIC TELEMATICA Y LOGICA RACIONAL PARA LA EMPRESA EUROPEA SL TREELOGIC TELEMATICA Y LOGICA RACIONAL PARA LA EMPRESA EUROPEA SL Organization address address: PARQUE TECNOLOGICO DE ASTURIAS city: LLANERA ASTURIAS postcode: 33428 website: www.treelogic.com contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	ES (LLANERA ASTURIAS)	participant	700˙294.00
4	TRILATERAL RESEARCH LTD TRILATERAL RESEARCH LTD Organization address address: ONE KNIGHTSBRIDGE GREEN OFFICE 5.12, 5TH FLOOR city: LONDON postcode: SW1X 7QA website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (LONDON)	participant	333˙750.00
5	Lambdoop Solutions S.L. Lambdoop Solutions S.L. Organization address address: AVENIDA DE MANOTERAS 38 city: MADRID postcode: 28050 website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	ES (MADRID)	participant	243˙330.00
6	ARCELORMITTAL INNOVACION INVESTIGACION E INVERSION SL ARCELORMITTAL INNOVACION INVESTIGACION E INVERSION SL Organization address address: LUGAR RESIDENCIA LA GRANDA SN city: GOZON postcode: 33418 website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	ES (GOZON)	participant	215˙625.00
7	TRILATERAL RESEARCH & CONSULTING LLP TRILATERAL RESEARCH & CONSULTING LLP Organization address address: HAMMERSMITH ROAD 72 CROWN HOUSE city: LONDON postcode: W14 8TH website: http://www.trilateralresearch.com/ contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (LONDON)	participant	0.00

Map

Project objective

PROTEUS mission is to investigate and develop ready-to-use scalable online machine learning algorithms and interactive visualization techniques for real-time predictive analytics to deal with extremely large data sets and data streams. The developed algorithms and techniques will form a library to be integrated into an enhanced version of Apache Flink, the EU Big Data platform. PROTEUS will contribute to the EU Big Data area by addressing fundamental challenges related to the scalability and responsiveness of analytics capabilities. The requirements are defined by a steelmaking industrial use case. The techniques developed in PROTEUS are however, general, flexible and portable to all data stream-based domains. In particular, the project will go beyond the current state-of-art technology by making the following specific original contributions: i) Real-time scalable machine learning for massive, high-velocity and complex data streams analytics; ii) Real-time hybrid computation, batch data and data streams; iii) Real-time interactive visual analytics for Big Data; iv) Enhancement of Apache Flink, the EU Big Data platform; and v) Real-world industrial validation of the technology developed The PROTEUS impact is manifold: i) strategic, by reducing the gap and dependency from the US technology, empowering the EU Big Data industry through the enrichment of the EU platform Apache Flink; ii) economic, by fostering the development of new skills and new job positions and opportunities towards economic growth; iii) industrial, by considering real-world requirements from industry and by validating the outcome on an operational setting, and iv) scientific, by developing original hybrid and streaming analytic architectures that enable scalable online machine learning strategies and advanced interactive visualisation techniques that are applicable for general data streams in other domains.

Deliverables

List of deliverables.
Report on scientific dissemination activities â€“ V2 [	Documents, reports	2020-02-20 17:17:37
PROTEUS factsheet leaflet	Websites, patent fillings, videos etc.	2020-02-20 17:17:34
Catalogue of scientific and technical requirements	Documents, reports	2020-02-20 17:17:35
Updateable-state management prototype implementation	Demonstrators, pilots, prototypes	2020-02-20 17:17:34
Investigative overview of targeted techniques and algorithms	Documents, reports	2020-02-20 17:17:34
Report on community engagement and technology transfer activities â€“ V1	Documents, reports	2020-02-20 17:17:34
Guidelines for interacting and visualization information in Big Data environments	Documents, reports	2020-02-20 17:17:34
Report on project communication and engagement activities â€“ V1	Documents, reports	2020-02-20 17:17:34
Declarative language syntax definition	Documents, reports	2020-02-20 17:17:35
Basic scalable streaming algorithms	Demonstrators, pilots, prototypes	2020-02-20 17:17:35
Declarative language prototype implementation	Demonstrators, pilots, prototypes	2020-02-20 17:17:34
Report on scientific dissemination activities â€“ V1	Documents, reports	2020-02-20 17:17:34
Hybrid computation prototype implementation	Demonstrators, pilots, prototypes	2020-02-20 17:17:34
Hybrid computation tested system	Demonstrators, pilots, prototypes	2020-02-20 17:17:35
Visualization requirements for massive online machine learning strategies	Documents, reports	2020-02-20 17:17:35
First prototype (V1)	Demonstrators, pilots, prototypes	2020-02-20 17:17:34
PROTEUS project website	Websites, patent fillings, videos etc.	2020-02-20 17:17:35
Scenario details and objectives description	Documents, reports	2020-02-20 17:17:34
Scenario development and KPI definition for the PROTEUS solution	Documents, reports	2020-02-20 17:17:35
Scalable Online algorithms in Flink	Demonstrators, pilots, prototypes	2020-02-20 17:17:34
Optimizer finished implementation	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Architecture design for supporting incremental visual methods	Documents, reports	2020-02-20 17:17:34
Report on community engagement and technology transfer activities â€“ V2	Documents, reports	2020-02-20 17:17:34
Scalable drift and anomaly detection	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Third prototype (V3)	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
PROTEUS evaluation and impact assessment	Documents, reports	2020-02-20 17:17:34
Declarative language finished implementation	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Declarative language tested implementation	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Final demonstrator	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Optimizer Prototype	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Second prototype (V2)	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Software implementation and integration with Apache Flink	Demonstrators, pilots, prototypes	2020-02-20 17:17:34
Scalable online machine learning algorithms for streaming	Demonstrators, pilots, prototypes	2020-02-20 17:17:33
Report on project communication and engagement activities â€“ V2	Documents, reports	2020-02-20 17:17:37

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

Publications

List of publications.
year	authors and title	journal	last update
2018	Daniela Pohl, Abdelhamid Bouchachia, Hermann Hellwagner Batch-based active learning: Application to social media data for crisis management published pages: 232-244, ISSN: 0957-4174, DOI: 10.1016/j.eswa.2017.10.026	Expert Systems with Applications 93	2020-02-20
2015	Paris Carbone, Stephan Ewen, Seif Haridi, Asterios Katsifodimos, Volker Markl, Kostas Tzoumas Apache Flink: Stream and Batch Processing in a Single Engine published pages: 28-38, ISSN: , DOI:	Bulletin of the IEEE Computer Society Technical Committee on Data Engineering December 2015 Vol. 38 No. 4, Is	2020-02-20
2017	Bonaventura Del Monte Efficient Migration of Very Large Distributed State for Scalable Streaming Processing published pages: , ISSN: , DOI:	Proceedings of the VLDB 2017 PhD Workshop 28 August 2017	2020-02-20
2016	Saad Mohamad, Moamar Sayed-Mouchaweh and Abdelhamid Bouchachia Active Learning for Data Streams under Concept Drift and concept evolution published pages: 51-68, ISSN: , DOI:	ECML/PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments STREAMEVOLV-2016, 23 September	2020-02-20
2016	DÃaz Morales, R. , & Navia VÃ¡zquez, Ã Improving the efficiency of IRWLS SVMs using parallel Cholesky factorization published pages: 91-98, ISSN: 0167-8655, DOI: 10.1016/j.patrec.2016.08.015	Pattern Recognition Letters Volume 84, 1 December 2016	2020-02-20
2017	Roberto DÃaz-Morales, Ãngel Navia-VÃ¡zquez LIBIRWLS: A parallel IRWLS library for full and budgeted SVMs published pages: 183-186, ISSN: 0950-7051, DOI: 10.1016/j.knosys.2017.09.007	Knowledge-Based Systems 136	2020-02-20
2016	Bouchachia, Abdelhamid; Kalnishkan, Y; Jamil, W. Aggregation Algorithm Vs. Average for Time Series Prediction published pages: 69-82, ISSN: , DOI:	ECML/PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV-2016) 1	2020-02-20
2016	Mohamad, S., Bouchachia, A. and Sayed-Mouchaweh, M. A Bi-Criteria Active Learning Algorithm for Dynamic Data Streams published pages: 1-13, ISSN: 2162-2388, DOI: 10.1109/TNNLS.2016.2614393	IEEE Transactions on Neural Networks and Learning Systems N/A (early access)	2020-02-20
2018	Saad Mohamad, Moamar Sayed-Mouchaweh, Abdelhamid Bouchachia Active learning for classifying data streams with unknown number of classes published pages: 1-15, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2017.10.004	Neural Networks 98	2020-02-20
2017	JosÃ© de JesÃºs Rubio, Abdelhamid Bouchachia MSAFIS: an evolving fuzzy inference system published pages: 2357-2366, ISSN: 1432-7643, DOI: 10.1007/s00500-015-1946-4	Soft Computing 21/9	2020-02-20
2017	Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Tilmann Rabl, Volker Markl Blockjoin published pages: 2061-2072, ISSN: 2150-8097, DOI: 10.14778/3151106.3151110	Proceedings of the VLDB Endowment 10/13	2020-02-20
2017	M.S. Mouchaweh, A. Bifet, A. Bouchachia, J. Gama, R. Ribeiro ECML/PKDD 2017 Workshop on IoT Large Scale Learning from Data Streams published pages: , ISSN: , DOI:		2020-02-20

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "PROTEUS" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "PROTEUS" are provided by the European Opendata Portal: CORDIS opendata.