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EXtreme-scale Analytics via Multimodal Ontology Discovery & Enhancement

Objective

Exascale volumes of diverse data from distributed sources are continuously produced. Healthcare data stand out in the size produced (production 2020 >2000 exabytes), heterogeneity (many media, acquisition methods), included knowledge (e.g. diagnostic reports) and commercial value. The supervised nature of deep learning models requires large labeled, annotated data, which precludes models to extract knowledge and value. EXA MODE solves this by allowing easy & fast, weakly supervised knowledge discovery of exascale heterogeneous data provided by the partners, limiting human interaction. Its objectives include the development and release of extreme analytic methods and tools, that are adopted in decision making by industry and hospitals. Deep learning naturally allows to build semantic representations of entities and relations in multimodal data. Knowledge discovery is performed via document-level semantic networks in text and the extraction of homogeneous features in heterogeneous images. The results are fused, aligned to medical ontologies, visualized and refined. Knowledge is then applied using a semantic middleware to compress, segment and classify images and it is exploited in decision support and semantic knowledge management prototypes. EXA MODE is relevant to ICT12 in several aspects: 1) Challenge: it extracts knowledge and value from heterogeneous quickly increasing data volumes. 2) Scope: the consortium develops and releases new methods and concepts for extreme scale analytics to accelerate deep analysis also via data compression, for precise predictions, support decision making and visualize multi-modal knowledge. 3) Impact: the multi-modal/media semantic middleware makes heterogeneous data management & analysis easier & faster, it improves architectures for complex distributed systems with better tools increasing speed of data throughput and access, as resulting from tests in extreme analysis by industry and in hospitals.

Field of science

  • /humanities/philosophy, ethics and religion/philosophy/metaphysics/ontology
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning/deep learning

Call for proposal

H2020-ICT-2018-2
See other projects for this call

Funding Scheme

RIA - Research and Innovation action

Coordinator

HAUTE ECOLE SPECIALISEE DE SUISSE OCCIDENTALE
Address
Route De Moutier 14
2800 Delemont
Switzerland
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 851 875

Participants (7)

UNIVERSITA DEGLI STUDI DI PADOVA
Italy
EU contribution
€ 516 250
Address
Via 8 Febbraio 2
35122 Padova
Activity type
Higher or Secondary Education Establishments
ONTOTEXT AD

Participation ended

Bulgaria
EU contribution
€ 3 000
Address
Tsarigradsko Shose 135
1784 Sofia
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
STICHTING KATHOLIEKE UNIVERSITEIT
Netherlands
EU contribution
€ 675 156
Address
Geert Grooteplein Noord 9
6525 EZ Nijmegen
Activity type
Higher or Secondary Education Establishments
MICROSCOPEIT SP ZOO
Poland
EU contribution
€ 604 000
Address
Ul. Al. Kasztanowa 3A-5
53 125 Wroclaw
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
AZIENDA OSPEDALIERA PER L EMERGENZA CANNIZZARO
Italy
EU contribution
€ 502 500
Address
Via Messina 829
95126 Catania
Activity type
Public bodies (excluding Research Organisations and Secondary or Higher Education Establishments)
SURFSARA BV
Netherlands
EU contribution
€ 562 250
Address
Science Park 140
1098XG Amsterdam
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
SIRMA AI EAD
Bulgaria
EU contribution
€ 618 250
Address
135 Tsarigradsko Shose Blvd
1784 Sofia
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)