This document summarizes a session from the European Big Data Value Forum 2020. It discusses the DataBench Toolbox, which aims to be a one-stop-shop for big data and AI benchmarking. The toolbox connects benchmarking results and showcases knowledge. It was demonstrated including an AI Benchmark Observatory for tracking topic popularity over time using various data sources. Finally, the needs of digital innovation hubs for fostering adoption of benchmarking results were discussed, including providing local services and connecting to resources across Europe.

1. EUROPEAN BIG DATA VALUE FORUM 2020
EUROPEAN BIG DATA VALUE FORUM 2020
Session 4.
A practical journey on how to
use the DataBench Toolbox

2. EUROPEAN BIG DATA VALUE FORUM 2020
EUROPEAN BIG DATA VALUE FORUM 2020
Panelists
Marko Grobelnik
Artificial Intelligence Lab,
Jozef Stefan Institute
Daniel Sáez Domingo
Strategic Intelligence &
Technology Transfer
Director, ITI. Coordinator of
the Data Cycle Hub (DCH)
and EuHubs4Data
Tomás Pariente
Associate Head of AI, Data &
Robotics Unit, Atos Research
and Innovation

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EUROPEAN BIG DATA VALUE FORUM 2020
Demo of the DataBench Toolbox

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The DataBench Toolbox aims to be a one-stop-shop
for Big Data / AI Benchmarking offering multiple
benefits for different kind of users and businesses
Connecting the
Toolbox with all
DataBench
results
DataBench Toolbox

5. EUROPEAN BIG DATA VALUE FORUM 2020
Toolbox
Showcasing knowledge about benchmarking
Who are our
stakeholders?
Benchmark providers /
communities
BDV PPP Projects /
Researchers
Technical users
Business Users /
CTOs…
What can we do for
them?
Visibility, integration
Benchmarking
Alignment with BDV RM /
Blueprints
Catalogues / Search
Deployment / Execution
Pipelines / Blueprints
Knowledge,
Use cases / Industries,
Correlation Tech / KPIs
How?
Operationalize work
done in DataBench
Catalogue of benchmarks vs
BDV Reference model and
data pipelines
Reports, methods,
indicators, self-assessment,
surveys
Relation to use cases &
industries, examples,
Handbook
AI Observatory, blueprints,
admin…

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DEMO

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EUROPEAN BIG DATA VALUE FORUM 2020
AIBench Observatory

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AIBench Observatory
AIBench Observatory is a tool to observe the popularity,
importance and visibility of topic terms related to the
Artificial Intelligence and Big Data along several dimensions
on a monthly basis.
DataBench Popularity Index is a measure to rank topic
terms in the area of Artificial Intelligence and Big Data
(with specific accent on tools and technologies related to
Benchmarking).
EMERGING
TRENDS
COMBINED
MEASURE
COMPONENTS
SELECTION
SEMANTIC
ANNOTATION
RANKING FROM
MULTIPLE SOURCES
UNIFICATION AND
NORMALIZATION
aibench.ijs.si

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Data Sources to assess Popularity Index
Microsoft Academic Graph
[Academia & Patents]
Media News from Event Registry
[News and Social media]
GitHub projects
[Development]
Horizon2020 projects
[Research projects]
Job ads from Adzuna
[Job market & skills]
Search volume from Google Trends
[Global popularity]
Investments from Prequin
[Investment trends]
Global and & Dynamic data sources

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Visual.ly
Microsoft Power BI
Apache OPEN NLP
Google Cloud Platform
Natural Language
Wolfram Alpha
…
3
21
Is-a
Microsoft Academic Graph (MAG) taxonomy has
been expanded with DataBench terms – over 1,700
tools and technologies related to Benchmarking, Big
Data, Artificial Intelligence.
New concepts have been aligned with MAG topic,
MAG keyword, Wikipedia (for analysis in wikification)
and Event Registry concepts.
Ontology of AI & Big Data
Data visualization tools and
technologies
NLP tools and
technologies
Other groups of tools
and technologies
AI, Big Data
Benchmarking topics
(including tools,
technologies)
Example
Term: Apache OPEN NLP
Parent: [databench.ijs.si/nlp]
URI: databench.ijs.si/apache_open_nlp
Wiki concept: https://en.wikipedia.org/wiki/Apache_OpenNLP
ER concept: “Apache OPEN NLP”

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Time series for Tools and Technologies
Time Series – popularity over time

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Moving Indicators

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Live News – media coverage

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EUROPEAN BIG DATA VALUE FORUM 2020
Fostering adoption of
DataBench results.
Needs from the point of view of
Digital Innovation Hubs
Daniel Sáez Domingo
Strategic Intelligence &
Technology Transfer Director, ITI.
Coordinator of the Data Cycle
Hub (DCH) and EuHubs4Data

15. EUROPEAN BIG DATA VALUE FORUM 2020
Data Driven Innovation Hubs are key instruments to foster DDI
BDVA SRIA -
http://bdva.eu/sites/default/files/BD
VA_SRIA_v4_Ed1.1.pdf
Environments for data driven innovation and experimentation, where
research on BDV technologies and novel BDV applications can be
quickly tested, piloted and exploited
Technical and non-technical
activities, bringing data,
technology, application
developments together, and
fostering skills, competences
and best practices
Rely on existing national and
European initiatives, federate,
complement and leverage
activities of similar national
incubators / environments and
existing PPPs
Needs of large and small
companies, to ensure access to
economic opportunities offered
by BDV, testing the viability of
actual business deployments
Services to accelerate data driven innovation

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Local Offer …
• One-Stop-Shop in the region
• Support Digitalization of SMEs and
Public Admin.
• Neutral infrastructures and
information about Data driven
technologies and Data Sharing options
• Personalized assessment to companies
in order to take decisions about technology
investments or business models in the
digital economy.
• Deploy pilot projects and technology
tests in lab environments as a previous
phase to the investment in a technology or
the launch of a product to market.

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… but Connected to Europe
• The Services
• Technology Selection
• Data maturity & Digital assessment
• Access to Data & infrastructures
• Strategic approach around Data
• Support to experiments
• R&D and PoC
• Prototyping and concept validation
• Ecosystem Building
• New Business Models
• Funding
• Data & AI Technology Watch
• Ethics and legal on Data
• Skills/Training
• Brokering/Consortium Building/Innovation
Scouting
• Data governance services
• The Needs
• Use Cases
• Metrics
• Projects
• Networks
• Maturity models
• Demonstrators
• Orchestrators
• Data Sharing Schemes
• Safe-mode tests

18. This project has received funding from the European Horizon 2020 Programme for research,
technological development and demonstration under grant agreement n° 780966
Contacts
info@databench.eu
@DataBench_eu
DataBench
www.databench.eu
DataBench Project
DataBench
DataBench Project