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SmartDataLake SIGNED

Sustainable Data Lakes for Extreme-Scale Analytics

Total Cost €

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EC-Contrib. €

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Partnership

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 SmartDataLake project word cloud

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

portfolio    ranking    search    approximate    entity    efficient    coexist    pricing    hidden    incremental    recommendation    visual    automated    associations    provides    scalable    synopses    scenarios    representative    big    ad    spatial    network    innovation    algorithms    times    modelled    investment    sources    adaptive    relations    extraction    domain    resolution    visually    containing    sustainable    link    flexible    abstracting    scientist    prediction    functionalities    contents    intelligence    smes    query    entities    detection    business    placement    exploration    reduce    virtualization    empower    decision    diverse    interactive    hoc    visualizations    lake    world    similarity    tuning    queries    faster    heterogeneous    lakes    temporal    discovering    multiple    tiers    extreme    planning    service    exploring    unveiling    data    smartdatalake    ecosystems    types    offers    fast    storage    amounts    raw    loop    patterns    optimizing    update    capitalize    elastic    selecting    answering    space    clustering    analytics    self    retained    models   

Project "SmartDataLake" data sheet

The following table provides information about the project.

Coordinator
ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS TECHNOLOGIES TIS PLIROFORIAS, TON EPIKOINONION KAI TIS GNOSIS 

Organization address
address: ARTEMIDOS 6 KAI EPIDAVROU
city: MAROUSSI
postcode: 151 25
website: www.athena-innovation.gr

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 Greece [EL]
 Total cost 3˙945˙450 €
 EC max contribution 3˙945˙450 € (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-2018-2
 Funding Scheme RIA
 Starting year 2019
 Duration (year-month-day) from 2019-01-01   to  2021-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS TECHNOLOGIES TIS PLIROFORIAS, TON EPIKOINONION KAI TIS GNOSIS EL (MAROUSSI) coordinator 853˙125.00
2    ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE CH (LAUSANNE) participant 760˙000.00
3    TECHNISCHE UNIVERSITEIT EINDHOVEN NL (EINDHOVEN) participant 569˙637.00
4    UNIVERSITAT KONSTANZ DE (KONSTANZ) participant 425˙000.00
5    RAW LABS SA CH (LAUSANNE) participant 411˙750.00
6    SYNYO GmbH AT (WIEN) participant 322˙500.00
7    SPAZIODATI SRL IT (TRENTO) participant 302˙500.00
8    SPRING TECHNO GMBH & CO KG DE (BREMEN) participant 300˙937.00

Map

 Project objective

Data lakes are raw data ecosystems, where large amounts of diverse data are retained and coexist. They facilitate self-service analytics for flexible, fast, ad hoc decision making. SmartDataLake enables extreme-scale analytics over sustainable big data lakes. It provides an adaptive, scalable and elastic data lake management system that offers: (a) data virtualization for abstracting and optimizing access and queries over heterogeneous data, (b) data synopses for approximate query answering and analytics to enable interactive response times, and (c) automated placement of data in different storage tiers based on data characteristics and access patterns to reduce costs. The data lake’s contents are modelled and organised as a heterogeneous information network, containing multiple types of entities and relations. Efficient and scalable algorithms are provided for: (a) similarity search and exploration for discovering relevant information, (b) entity resolution and ranking for identifying and selecting important and representative entities across sources, (c) link prediction and clustering for unveiling hidden associations and patterns among entities, and (d) change detection and incremental update of analysis results to enable faster analysis of new data. Finally, interactive and scalable visual analytics are provided to include and empower the data scientist in the knowledge extraction loop. This includes functionalities for: (a) visually exploring and tuning the space of features, models and parameters, and (b) enabling large-scale visualizations of spatial, temporal and network data. The results of the project are evaluated in real-world use cases from the business intelligence domain, including scenarios for portfolio recommendation, production planning and pricing, and investment decision making. SmartDataLake will foster innovation and enable European SMEs to capitalize on the value of their own data lakes.

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

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