This document discusses the BYTE project which aims to address societal externalities associated with big data use. The project will produce a research roadmap and recommendations, involve relevant stakeholders to identify challenges through case studies, and disseminate findings. Case studies will explore externalities in various domains including environmental, energy, and health data. Both positive externalities like efficiencies and innovation, and negative externalities like privacy concerns and outdated legislation are discussed. Health case studies found improvements in diagnosis and treatment but also reluctance to share data due to legal and ethical constraints.

1. BYTE:
Big Data Externali2es – the BYTE Case Studies
Rachel Finn
Trilateral Research & Consul2ng, LLP
Big data roadmap and cross-disciplinarY
community for addressing socieTal
Externalities
European Data Economy Workshop
15 September 2015

2. @BYTE_EU www.byte-project.eu
Project details: BYTE
• Big
data
roadmap
and
cross-­‐disciplinarY
community
for
addressing
socieTal
Externali9es
(BYTE)
project
• March
2014
–
Feb
2017;
36
months
•
Funded
by
DG-­‐CNCT:
€2.25
million
(Grant
agreement
no:
619551)
•
11
Partners
•
10
Countries

3. @BYTE_EU www.byte-project.eu
Objec2ves
The
BYTE
project
has
three
main
objec9ves:
1.
To
produce
a
research
and
policy
roadmap
and
recommenda0ons
to
support
European
stakeholders
in
increasing
their
share
of
the
big
data
market
by
2020
and
in
capturing
and
addressing
the
posi9ve
and
nega9ve
societal
externali9es
associated
with
use
of
big
data.
2.
To
involve
all
of
the
European
actors
relevant
to
big
data
in
order
to
iden9fy
concrete
current
and
emerging
problems
to
be
addressed
in
the
BYTE
roadmap.
The
stakeholder
engagement
ac9vi9es
will
lead
to
the
crea9on
of
the
Big
Data
Community,
a
sustainable
plaXorm
from
which
to
measure
progress
in
mee9ng
the
challenges
posed
by
societal
externali9es
and
iden9fy
new
and
emerging
challenges.
3.
To
disseminate
the
BYTE
findings,
recommenda0ons
and
the
existence
of
the
BYTE
Big
Data
Community
to
a
larger
popula9on
of
stakeholders
in
order
to
encourage
them
to
implement
the
BYTE
guidelines
and
par9cipate
in
the
Big
Data
Community.

4. @BYTE_EU www.byte-project.eu
Case studies: big data prac22oners assist
to iden2fy externali2es
Environmental
data
Energy
U9li9es
/
Smart
Ci9es
Cultural
Data
Health
Crisis
informa9cs
Transport

5. @BYTE_EU www.byte-project.eu
Understanding ‘externali2es’
§ In
BYTE
we
consider
the
externali0es
or
impacts
of
big
data
§ Posi0ve
effects
or
benefits
realised
by
a
third
party
§ Nega0ve
costs
(or
harm)
that
affects
a
third
party
§ Externali9es
relate
to
social
processes
linked
to
big
data,
as
well
as
the
opportuni9es
&
risks
that
may
arise
as
a
result
of
the
existence
of
the
data.
§ Some
effects
may
be
unexpected
or
uninten0onal
IMPACT
ECONOMIC
SOCIAL
LEGAL
ETHICAL
POLITICAL

6. @BYTE_EU www.byte-project.eu
Big data concerns: externali2es
Economic
• Boost
to
the
economy
• Innova9on
• Increase
efficiency
• Smaller
actors
lef
behind
• Shrink
economies
Legal
• Privacy
• Data
protec9on
• Data
ownership
• Copyright
• Risks
associated
with
inclusion
&
exclusion
Social
&
Ethical
• Transparency
• Discrimina9on
• Methodological
difficul9es
• Spurious
rela9onships
• Consumer
manipula9on
Poli9cal
• Reliance
on
US
services
• Services
have
become
u9li9es
• Legal
issues
become
trade
issues
Economic
• Boost
to
the
economy
• Innova0on
✔
• Increase
efficiency
✔
• Smaller
actors
lef
behind
• Shrink
economies
Legal
• Privacy
✔
• Data
protec0on
✔
• Data
ownership
✔
• Copyright
• Risks
associated
with
inclusion
&
exclusion
Social
&
Ethical
• Transparency
✔
• Discrimina9on
• Methodological
difficul9es
• Spurious
rela9onships
• Consumer
manipula9on
• Improved
services
✔
Poli9cal
• Reliance
on
US
services
✔
• Services
have
become
u0li0es
✔
• Legal
issues
become
trade
issues
• Dependent
on
public
funding
✔

7. @BYTE_EU www.byte-project.eu
Select horizontal findings
Posi9ve
externali9es
• Efficiencies
• Product
and
service
innova9on
• New
business
models
• Societal
benefits
(improved
decision-­‐
making
in
healthcare,
crisis
management,
commercial
organisa9ons;
personalised
services)
Nega9ve
externali9es
• Dependence
on
public
funding
to
create
the
environment
in
which
big
data
business
models
can
flourish
• Privacy
concerns
• Fear
of
losing
proprietary
informa9on
• Outdated
legisla9on
• Difficulty
in
adap9ng
business
models

8. @BYTE_EU www.byte-project.eu
Case study-­‐specific findings: health
• Big
data
in
healthcare
is
quite
well
developed
and
widespread
across
a
number
of
health
areas.
• Gene0c
data
use
is
maturing
and
focused
on
high-­‐grade
analy9cs
and
the
discovery
of
rare
genes
and
gene9c
disorders.
• The
key
improvements
include
9mely
and
more
accurate
diagnosis,
the
development
of
personalised
medicines,
and
drug
and
other
treatments/
therapy
development,
which
can
save
lives.
• Key
innova9ons
include
the
development
of
privacy
protec9ng
and
secure
databases
for
gene9c
data
samples.
• However,
there
tends
to
be
a
reluctance
by
public
sector
ini0a0ves
to
share
data
due
to
legal
and
ethical
constraints.
“So
in
our
own
consent
we
never
say
that
data
will
be
fully
anonymous.
We
do
everything
in
our
power
so
that
it
is
deposited
in
a
anonymous
fashion
and
[…]
when
we
consent
we
are
very
careful
in
saying
look
it’s
very
unlikely
that
anyone
is
going
to
ac9vely
iden9fy
informa9on
about
you”
(Program
head,
Clinical
gene9cist
)

9. @BYTE_EU www.byte-project.eu
Case study-­‐specific findings: crisis
informa2cs
• Crisis
informa9cs
is
in
the
early
stages
of
integra9ng
big
data.
• Currently,
its
primary
focus
is
on
integra9ng
social
media
and
geographical
data.
• The
key
improvement
is
that
the
analysis
of
this
data
improves
situa0onal
awareness
more
quickly
afer
an
event
has
occurred.
• A
key
innova9on
is
the
combina0on
of
human
compu0ng
and
machine
compu0ng,
primarily
through
digital
volunteers,
to
validate
the
data
collected
and
determine
how
trustworthy
it
is.
• Stakeholders
in
this
area
are
making
progress
in
addressing
privacy
and
data
protec0on
issues.
• There
is
evidence
of
a
reliance
on
US
cloud
and
compu9ng
services.
“And
I
have
seen
this
on
mul9ply
occasions
from
[…]
big
private
companies
in
this,
they’ll
deal
with
their
own
huge
amount
of
data
and
response
to
crisis
and
so
on.
But
[then]
become
very
unpredictable
unsustainable
outside
of
an
emergency,
do
a
good
job
of
talking
about
what
they
do
during
a
crisis
but
then
sort
of
disappear
in-­‐between.”
(Programme
manager,
Interna9onal
Governmental
Organisa9on)

10. @BYTE_EU www.byte-project.eu
BYTE project key outputs
•
Define
research
efforts
and
policy
measures
necessary
for
responsible
par9cipa9on
in
the
big
data
economy
•
Vision
for
Big
Data
for
Europe
for
2020,
incorpora9ng
externali9es
• Amplify
posi9ve
externali9es
• Diminish
nega9ve
ones
•
Roadmap
• Research
Roadmap
• Policy
Roadmap
•
Forma9on
of
a
Big
Data
community
• Implement
the
roadmap
• Sustainability
plan

11. @BYTE_EU www.byte-project.eu
Next event
Valida0ng
case
study
externali0es
Dublin
14th
October
2015,
9am-­‐5pm
Presenta9ons
by:
Sonja
Zillner,
SIEMENS
Big
Data
in
a
Digital
City
Knut
Sebas9an
Tungland,
Statoil
Big
data
in
the
energy
sector

12. @BYTE_EU www.byte-project.eu
THANK YOU
Any
ques0ons?
Key
contacts:
◦ Rachel
Finn
–
rachel.finn@trilateralresearch.com
◦ Kush
Wadhwa
–
kush.wadhwa@trilateralresearch.com