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euBusinessGraph SIGNED

Enabling the European Business Graph for Innovative Data Products and Services

Total Cost €

0

EC-Contrib. €

0

Partnership

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 euBusinessGraph project word cloud

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

linking    contributes    demonstrating    provisioning    mentions    countries    plays    languages    name    expensive    disrupt    border    communities    error    feasible    cross    directors    geo    press    public    official    entity    authoritative    tedious    mostly    entities    shareholders    input    chains    firmographics    silo    sales    business    interactions    eubusinessgraph    aggregation    collection    outside    operation    interoperability    contextual    transfer    models    accessibility    sectors    accountability    cadastral    borders    enterprises    foundations    originating    limited    country    instrumental    fragmented    tenders    registered    time    incorporation    ed    combination    foundation    innovation    smes    company    reconciliation    providers    analytics    simplify    sources    renders    ratings    consuming    financials    graph    collecting    ownership    ones    data    prone    sheets    balance    aggregating    lingual    sectorial    quality    open    scope    transparency    size    companies    private    basic    corporate    marketing   

Project "euBusinessGraph" data sheet

The following table provides information about the project.

Coordinator
SINTEF AS 

Organization address
address: STRINDVEGEN 4
city: TRONDHEIM
postcode: 7034
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.

 Coordinator Country Norway [NO]
 Project website http://eubusinessgraph.eu/
 Total cost 3˙601˙500 €
 EC max contribution 3˙099˙900 € (86%)
 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 2017
 Duration (year-month-day) from 2017-01-01   to  2019-06-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    SINTEF AS NO (TRONDHEIM) coordinator 611˙090.00
2    EVRY NORGE AS NO (FORNEBU) participant 454˙300.00
3    STIFTELSEN SINTEF NO (TRONDHEIM) participant 358˙235.00
4    DEUTSCHE WELLE DE (BONN) participant 334˙750.00
5    OPENCORPORATES LTD UK (LONDON) participant 266˙175.00
6    INSTITUT JOZEF STEFAN SI (LJUBLJANA) participant 235˙625.00
7    UNIVERSITA' DEGLI STUDI DI MILANO-BICOCCA IT (MILANO) participant 204˙125.00
8    SPAZIODATI SRL IT (TRENTO) participant 190˙312.00
9    REGISTERENHETEN I BRONNOYSUND NO (BRONNOYSUND) participant 185˙675.00
10    ONTOTEXT AD BG (SOFIA) participant 130˙183.00
11    CERVED GROUP SPA IT (SAN DONATO MILANESE) participant 126˙000.00
12    SIRMA AI EAD BG (SOFIA) participant 3˙428.00
13    CERVED GROUP SPA IT (MILANO) participant 0.00

Map

 Project objective

Corporate information, including basic company firmographics (e.g., name(s), incorporation data, registered addresses, ownership and related entities), financials (e.g., balance sheets, ratings) as well as contextual data (e.g., cadastral data on corporate properties, geo data, data about directors and shareholders, public tenders data, press mentions) are the foundation that many data value chains are built on. Furthermore, this type of information contributes to the transparency and accountability of enterprises, is instrumental input to the process of marketing and sales, and plays a key role in many business interactions. Existing initiatives to increase the interoperability and access of corporate data are mostly fragmented (across borders), limited in scope and size, and silo-ed within specific business communities with limited accessibility from outside their originating sectors and countries. As a result, collecting and aggregating data about a business entity from several public sources (be it private/public, official or non-official ones), and especially across country borders and languages is a tedious, time consuming, error prone, and very expensive operation which renders many potential business models non-feasible. euBusinessGraph represents a key initiative to simplify and disrupt the cross-border and cross-lingual collection, reconciliation, aggregation, and provisioning and analytics of company-related data from authoritative and non-authoritative public or private sector sources, with the aim of enabling cross-sectorial innovation. By a combination of large companies, SMEs, public organizations, and technology transfer providers euBusinessGraph sets the foundations of a European cross-border and cross-lingual “business graph”, aggregating, linking, and provisioning (open and non-open) high-quality company-related data, demonstrating innovation across sectors where company-related data value chains are relevant.

 Deliverables

List of deliverables.
Requirements Analysis, Architecture and API Specification for the euBusinessGraph Marketplace – v1 Documents, reports 2019-10-15 12:06:40
Data Gathering, Quality Assessment and Management Plan Documents, reports 2019-10-15 12:06:40
Exploitation and Dissemination Strategy Documents, reports 2019-10-15 12:06:40
System of Identifiers, Ontologies and Vocabularies Documents, reports 2019-10-15 12:06:40
Website Other 2019-10-15 12:06:40

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

 Publications

year authors and title journal last update
List of publications.
2018 M. B. Massri, I. Novalija, M.Grobelnik
Relation Extraction from News.
published pages: , ISSN: , DOI:
2019-12-16
2019 Dumitru Roman, Tatiana Tarasova, and Javier Paniagua
MethOSM: A Methodology for Computing Composite Indicators Derived from OpenStreetMap Data
published pages: , ISSN: 1948-660X, DOI: 10.5311/josis.2019.19.491
Journal of Spatial Information Science JOSIS, 2019 2019-12-16
2019 Valerio Di Carlo, Federico Bianchi, Matteo Palmonari
Training Temporal Word Embeddings with a Compass
published pages: 6326-6334, ISSN: 2374-3468, DOI: 10.1609/aaai.v33i01.33016326
Proceedings of the AAAI Conference on Artificial Intelligence 33 2019-12-16
2019 Jan Chołoniewski, Julian Sienkiewicz, Gregor Leban, Janusz A. Hołyst
Modeling of temporal fluctuation scaling in online news network with independent cascade model
published pages: 129-144, ISSN: 0378-4371, DOI: 10.1016/j.physa.2019.02.035
Physica A: Statistical Mechanics and its Applications 523 2019-12-16
2020 Saliha Sajid, Bjørn Marius von Zernichow, Ahmet Soylu and Dumitru Roman
Predictive Data Transformation Suggestions in Grafterizer using Machine Learning
published pages: , ISSN: , DOI:
2019-12-16
2018 Ahmet Soylu, Oscar Corcho, Elena Simperl, Dumitru Roman, Francisco Yedro Martínez, Chris Taggart, Ian Makgill, Brian Elvesæter, Ben Symonds, Helen McNally, George Konstantinidis, Yuchen Zhao, Till C. Lech
Towards Integrating Public Procurement Data into a Semantic Knowledge Graph 1-4
published pages: , ISSN: 1613-0073, DOI:
Proceedings of the EKAW 2018 Posters and Demonstrations Session co-located with 21st International Conference on Knowledge Engineering and Knowledge Management (EKAW 2018) 2019-12-16
2019 Chris Taggart, Mollie Hanley, Alex Skene
Creating the German open company data: how we did it
published pages: , ISSN: , DOI:
2019-12-16
2018 Mollie Hanley
Patisserie Valerie shows why we need Corporate Events data
published pages: , ISSN: , DOI:
2019-12-16
2018 Evgenia Belyaeva, Aljaž Košmerlj, Dunja Mladenić, Gregor Leban
Automatic Estimation of News Values Reflecting Importance and Closeness of News Events
published pages: , ISSN: 0350-5596, DOI: 10.31449/inf.v42i4.1132
Informatica 42/4 2019-12-16
2017 Nivethika Mahasivam, Nikolay Nikolov, Dina Sukhobok, Dumitru Roman
Data preparation as a service based on Apache Spark
published pages: 125-139, ISSN: , DOI: 10.1007/978-3-319-67262-5_10
Proceedings of The European Conference on Service-Oriented and Cloud Computing (ESOCC) 2017 2019-10-15
2017 Dina Sukhobok, Nikolay Nikolov, Dumitru Roman
Tabular Data Anomaly Patterns
published pages: , ISSN: , DOI:
In the proceedings of The 3rd International Conference on Big Data Innovations and Applications 2019-10-15
2017 Dumitru Roman, Mike Kobernus, Rune Ødegård, Nikolay Nikolov, Dinaa Sukhobok, Bjoern Marius von Zernichow, Till Christopher Lech
ALaDIn: Shining a Light on Air Quality through Data Integration and Machine Learning
published pages: , ISSN: , DOI:
Proceedings of the Environmental Informatics – From Science to Society: The Bridge provided by Environmental Informatics 2017 2019-10-15
2017 Bjoern Marius von Zernichow and Dumitru Roman
A Visual Data Profiling Tool for Data Preparation
published pages: , ISSN: , DOI:
the proceedings of the Sixth International Conference on Data Analytics DATA ANALYTICS 2017 2019-10-15
2017 Bjørn Marius von Zernichow, Dumitru Roman
Usability of Visual Data Profiling in Data Cleaning and Transformation
published pages: 480-496, ISSN: , DOI: 10.1007/978-3-319-69459-7_32
The 16th International Conference on Ontologies, DataBases, and Applications of Semantics, 2017 2019-10-15
2017 Chris Taggart, Mollie Hanley
\"\"\"Introducing corporate events: timeline data for companies\"\"\"
published pages: , ISSN: , DOI:
2019-10-15
2017 Dina Sukhobok, Nikolay Nikolov, Dumitru Roman
Tabular Data Anomaly Patterns
published pages: , ISSN: , DOI:
Proceedings of International Conference on Big Data Innovations and Applications (Innovate-Data 2017), 21-23 August 2017, Prague, Czech Republic, IEEE 2019-10-15

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

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