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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.

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

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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