Tue, Jun 23, 2020 3:00 PM - 4:00 PM CEST CPP data ecosystem gives cross-sectorial industries access to a huge amount of sensor data coming from high volume products such as vehicles or smart buildings. The new information sources create new value, improving existing services, and fostering the creation of new data-driven services. The project overcomes data monetization and exchange barriers by defining a unique ecosystem integrating data streams coming from various cyber-physical systems, especially in the automotive and smart building sectors. It pays particular attention to cross-sectorial data and services. The objective of this session is to perform a Live Demo of the integrated Cross-CPP data marketplace to understand the benefits and impact of this kind of solution for your data-driven business. Cross-CPP Ecosystem and data-monetization opportunities Cross-CPP data marketplace live-demo including Integrated Analytics Tool Box, Context Services, and Security and Privacy Policies Promotion of Cross-CPP Beta Testing Campaign published in ReachOut Presenters: Christian Wolff (ATB), Víctor Corral (ATOS), Ernestisna Mensalvas (UPM).

1. Horizon 2020
European Union Funding
for Research & Innovation
Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
* This project has received funding from the European Union’s Horizon 2020 research and innovation programm under grant agreement No. 780167.
*

2. Horizon 2020
European Union Funding
for Research & Innovation
Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
BDVe Webinar:
How to monetize your data in an open data
marketplace

3. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 3
What is Cross-CPP about
Giving Access to CPP Data
The puzzle of observations from CPP creates a digital model of “the world” in the cloud.
This is a NEW prime data resource for new business opportunities.

4. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 4
CPP Data Ecosystem
History -> Chain of data platform projects
• Giving data customers access to personal and industrial data streams to
build sectorial and cross-sectorial services
• Empower data owners to exploit their most valuable asset (IoT data)
Data Diversity & Volume
SystemComplexity
• Brand independent vehicle
data MP
• Agreed data model (CVIM)
• CPP data from divers sectors
• Analytic toolbox
Further projects: smashHit …

5. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 5
CPP Data Ecosystem
Driven by the needs of its key stakeholders
• Data Owner: control over data (trustful, secure,
traceable), fair compensations
• Data Customer/Consumer: Brand independent data
market, standardized interface data access point, easy
manageable solution with just one interface, data
quality/integrity
Make Data Markets more attractive for
its key stakeholders:

6. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Contract
Data
Discovery
Offer
The Marketplace enables digital trade with CPP data between interested parties and data providers.
It covers data discovery and provisioning, accounting and billing, offer and contract negotiation,
SDKs and development support.
Provisioning
Transaction
CPP Data Ecosystem
Marketplace for CPP data
Is this really so easy?
Needed by Data Customers:
 Brand independent concept
 Single CPP data access
point with just one interface
 Controlled access to data
streams of diverse CPP
 Win-Win value chain for all
ecosystem partners
Current Situation:
 No or limited access to CPP
data
 Limited possibilities to use
cross-sectorial CPP big data
streams
 Missing preconditions to
establish such cross-sectorial
data market
 Non-economical brand-specific
service platform solutions
 Wasted Innovation Potentials
6

7. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
CPP Data Ecosystem
Brand independent Ecosystem open for integration of any CPP Data
7
 Standardized Cross Industrial
Data Model
Flexible to incorporate CPP data
coming from various industrial
sectors.
 CPP Big Data Marketplace with
Analytics Toolbox
“One-Stop-Shop” will provide
Service Providers a single point of
access to data streams from multiple
mass products.
 Cross Industrial Services
The consortium partners have
developed several innovative cross-
sectorial services.

8. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Success factors
• Ecosystem
 Driven by the needs of Data Owners, Data Providers and Data Customers
 Brand independent, Open platform with standardized interface -> High attractiveness
for SP
 Linking CPP data from different sectors enables higher quality content and NEW
services world
 Economical solution for all value chain partners, due to a greater amount of data
customers
 Data Providers can profit from Innovation Potentials by thousands of external experts
• User Engagement
 Increased willing to provide IoT data by data providers and data owners
 The owner can fully control which data he provides to which Service Provider
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9. Horizon 2020
European Union Funding
for Research & Innovation
Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Cross-CPP data Marketplace Live Demo
AGORA MVP

10. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
The story behind Cross-CPP...
10
2015 2016 2017 2018
AutoMat Kickoff
H2020 aims to develop an
Open Big Data Marketplace
from 3 leading EU OEMs
AutoMat Early
Prototype
Initial steps on the first Early
Prototype of the solution
AutoMat Final Prototype
Industry validation by VW, Renault
and Fiat. 4M data-packages
indexed. 3 BCs supported
Cross-CPP
New EU project aiming to
extend marketplace to
cross-sectorial sectors.
2020 2019
Cross-CPP and AGORA MVP go-to-market
Define the strategy to land into data-exchange markets.
Approach to real customers
Cross-CPP Full Prototype
From R&D to MVP. Officially launch of the
data-marketplace Atos solution

11. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
What we offer?
11
Brand-independent data Marketplace to
trade-off and monetize your Data Lakes
New products
and services
Offer Contract ExchangeCatalogue
API-based: unlock new data-driven
services based on harmonized
industrial datasets

12. Horizon 2020
European Union Funding
for Research & Innovation
Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Type of Sources and Data;
The Common Industrial Data Model (CIDM)

13. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Data Sources and Type of Data
13
Connected Vehicles
Smart Buildings
• Datapackage: Set of measurements
• TimeSeries
• Histograms
• Geo-Histograms
• Basic-Information
• Event-based
• Format: JSON
• How to collect?:
• Demand
• Subscription

14. Horizon 2020
European Union Funding
for Research & Innovation
Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
How to Monetize your data:
B2B and B2C Monetization process

15. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Key Concepts
23
Data Consumers
- Create Request-
Data Owners
- Accept / Terminate
Offers-
Monetization
active between
Data Owner and
Consumer through
Contracts
• AGORA is governed by a suscription-based
mechanism;
• Data Request and Offers
• Every interested Data Consumer creates a -
Data Request (s)- which includes all the
parameters, filters and configuration within the
Data Discovery process. It defines the needed
conditions to receive concrete data.
• Once the Data Request is published by Data
Consumers in the marketplace, Data Owners
can accept Offer (s) and get the consent to
deliver their data through that request and this
specific Data Consumer (s). This acceptance
process is formalized in an Contract.

16. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Steps flow
24

17. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Horizon 2020
European Union Funding
for Research & Innovation
Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Data Analytics Toolbox

18. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 26
Data analytical model
Data

19. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 27
Data Analytics Toolbox

20. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 28
Data Analytics Toolbox

21. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Streaming: Time series library
Prediction Drift Detection
• Core functionalities:
1. Prediction: forecasting of the future behavior of a given signal.
2. Drift Detection: metric representing the severity of a signal’s fluctuation.
3. Correlation metrics between two or more signals.

22. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 30
Use Cases – Time series’ module
• Identify malfunctioning sensors
• Drift estimation functions to measure a signal’s fluctuations.
• Can also help the detection of actual drift on a car’s
maneuvers.
Drift metric
• Any subsequent analysis (e.g. prediction, correlation)
benefits from having outliers detected and filtered out.

23. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 31
Data Analytics Toolbox

24. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 32
Batch: Trajectory library
• There are 4 main functionalities available in the module:
1. Interpolation: It refers to the method to estimate new data within the range of known data.
2. Statistics: Provides the average velocity, the duration and distance of a trajectory.
3. Clustering: Enables to group trajectories based on their similarities.
4. Anomalies detection: It allows to detect uncommon patterns in the data.
Statistics ClusteringInterpolation
Anomalies
detection

25. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 33
Use Cases – Trajectory Library
• Focus on specific routes
• Similar trajectories are grouped together.
• Aids further inspection of each group (e.g.
sensors’ behaviour).

26. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 34
Marketplace integration – Trajectory Library

27. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 35
Use Cases – Trajectories’ module
• Remove anomalous coordinates
• Atypical positions can be better identified when
a centroid trajectory is defined.
• Linear interpolation can then be used to obtain
an estimation of how they should look in
reality.

28. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 36
Marketplace integration – Trajectory Library

29. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 37
Data Analytics Toolbox

30. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 38
Batch: Networks library
• The functionalities available in the module are:
1. Create a network: Create a network from nodes and links.
2. Update the networks: Enables to represent time or other evolutions in the system.
– The networks could be live updated.
3. Compute basic metrics of the networks.
Network
Creation
Update
Networks
Metrics
Networks

31. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 39
Use Cases – Networks’ module
• Weather’s influence on sensors
• Signals with similar patterns are neighbors in a
network.
• Separated groups can be related to distinct
behaviors of a sensor.
• Aids inspection of the correlations and causality of
each different group.

32. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 40
Use Cases – Networks’ module
• Investigate outliers
• Non-neighboring or significantly distance groups
may be worth inspecting.
• Helps discover weird occurrences of a signal.

33. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 41
Introduction to the platform
1 Obtaining access to the data:
1- Selecting the type of data ( vehicles/buildings, temperature o GPS…)

34. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 42
Introduction to the platform
• In the Data Discovery the user can
add channels to have access to its
data.
• It is possible to set geographical an
time filters inside a channel.
1 Obtaining access to the data:
2- Request the data:

35. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 43
Introduction to the platform
• Once the Data provider has
accepted the user request, it is
possible to carry out analytics.
• In the Toolbox the user may create
analytics.
• Also it displays every analytic
performed in the past in each library.
(Time Series, Trajectories, Networks
and Machine Learning)
2 Perform Analytics:
1- Carrying out a model:

36. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 44
Introduction to the platform
• In the menu of a new analytic the
user shall choose among the type of
analysis that suit the best its
purpose:
By instance, “Permutation Entropy” is a good
feature for detecting Malfunctioning sensors.
• A brief description of each model is
included to assist in the model
decision making.
• Follow the steps to complete the
analytic.
2 Perform Analytics:
1- Carrying out a model:

37. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 45
Introduction to the platform
• The new analytic appears in the
Analytics view.
2 Perform Analytics:
1- Carrying out a model:

38. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources 46
Introduction to the platform
• The new analytic appears in the
Analytics view.
• For streaming data, the analytic
output consist in an Output AEON
subscription URL to receive the
results in streaming.
2 Perform Analytics:
2- Inspecting the new analytic:

39. Ecosystem for Services based on integrated Cross-sectorial Data Streams
from multiple Cyber Physical Products and Open Data Sources
Thank you for your attention !
Horizon 2020
European Union Funding
for Research & Innovation
47