The document details the follow-up of the Big Data Europe workshop focused on smart, green, and integrated transport, discussing the transport data and technology needs across three dimensions: infrastructure, vehicle, and users. It identifies challenges in understanding data types, interoperability, and privacy issues, while emphasizing the need for expertise and better communication within and between domains. Key conclusions highlight the diversity of big data technologies in transport and the importance of addressing data quality and silos for effective solutions.

1. BIG DATA EUROPE FOR
SMART, GREEN AND
INTEGRATED TRANSPORT
1ST
WORKSHOP FOLLOW-
UP
DATA AND TECHNOLOGY
Seán Gaines, Vicomtech-IK4 - 20151211

2. Background and Objectives
 Background
o BDE aims to create a foundational work for
Euroepan companies to build innovative Big Data
Solutiosn
o The BDE includes objectives focused on the
Transport Societal Challenge
 Objectives
o Provide input to the BDE platform design
o Present a high level and consistent view of the
Transport Data and Technology needs and
potential

3. Summary of Workshop
Session
 Three Transport dimensions discussed:
o Infrastructure
o Vehicle
o Users
 Types of data within each dimension were
discussed
 An analysis of the Volume, Velocity and
Variety of each type was done

4. Infrastructure
Data Types/Function Volume Velocity Variety
Dynamic Maps/Attributes + - +
Maintenance - - +
Operational + + +
Foresight ? ? ?

5. Vehicle
Data Types/Function Volume Velocity Variety
Location + - +
Driver Monitoring 0 0 +
Performance + + +
Telemetry + + -

6. Private Users
Data Types/Function Volume Velocity Variety
Events ? + +
State - - +
Behaviours - + +
Personal Activity - + +

7. Conclusions
 Commonalities between data types and their
3V characterisitics do exists but need to be
better understood between domain experts
 High diversity in application of Big Data
technologies in transport
 A more complete understanding of data
challenges is hindering the identification of
real solutions

8. Open Issues and Challenges
 Building Big Data expertise in the domain
 Privacy is and will remain a significant issue
 Control and measurement of the quality of
data and therefore the knowledge derived
form it
 Lack of understanding between domains could
lead to rifts between domains
 Rifts would further compound the problem of
data silos and hinder interoperability between
big data solutions

9. Open Issues and Challenges
 Lack of Data Formats and Interoperability are
a barrier
 Data Loss from infrastructure, vehicles and
users that will grow in an IoT world
 Linking data across the domains
 Driving value from Transport data sources
 Simple, in situ and economical processing of
data

10. Questions?