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BYTE:		
BYTE	Big	Data	Community	Workshop
Lorenzo	Bigagli,	National	Research	Council	of	Italy
Martí Cuquet,	University	of	Innsbruck
1	December	2016,	Valencia,	Spain
Big data roadmap and cross-disciplinary community for
addressing societal Externalities
@BYTE_EU www.byte-project.eu
Workshop	agenda
11:00	– 12:15 STRENGTHENING	THE	BYTE	BIG	DATA	COMMUNITY
Presentation	of	the	BBDC
Group	work	on	its	future
12:15	– 13:30 CONTRIBUTING	TO	THE	BDVA
Presentations	on	the	BBDC	focus	areas	for	2016:
• Smart	cities	(Anna	Melchor,	InnDEA,	València)
• Health	(Aggelos Liapis,	Athens	University,	BYTE	AB)
• Environment	(Giovanni	Rum	and	Wenbo Chu,	GEO	Secretariat)
Small groups	discussion	to	integrate	BYTE	findings
13:30	– 13:45 CLOSING	REMARKS
@BYTE_EU www.byte-project.eu
Vision	and	mission
Civil society	as important as industry,	academia and	policy	makers
in	the	EU	strategy for	big	data
@BYTE_EU www.byte-project.eu
Big	Data	Value
cPPP
CSOs
NGOs
NPOs
EU	Big	Data	Strategy:	filling	the	gap
BDVA
TF9	
Societal
TF5	Legal
TF3	
Community
Big	Data	Community
@BYTE_EU www.byte-project.eu
Objectives
◦ Engage	NGOs,	NPOs,	CSOs,	third	sector,	local	
governments,	tech-transfer	organizations
◦ Continue	BYTE	research	on	societal	externalities	of	big	
data,	and	how	to	make	the	best	of	them
◦ Input	and	feedback	to	BDVA,	membership	and	related	
networks
@BYTE_EU www.byte-project.eu
Activities
◦ Research/consultation	to	identify	sector-specific	
and	general	guidelines	about	current	big	data	
issues,	good	practice	and	touch	points	with	
standards	and	methodologies
◦ 3	focus	areas	per	year
◦ Input	and	validation
◦ SRIA	societal	implications
◦ EC	work	programme
@BYTE_EU www.byte-project.eu
BDVA	SRIA
@BYTE_EU www.byte-project.eu
Big	Data	PPP	in	H2020
ICT-14-2016-2017:	Big	Data	PPP:	cross-sectorial	and	cross-lingual	
data	integration	and	experimentation
ICT-15-2016-2017:	Big	Data	PPP:	Large	Scale	Pilot	actions	in	sectors	
best	benefitting	from	data-driven	innovation
ICT-16-2017:	Big	data	PPP:	research	addressing	main	technology	
challenges	of	the	data	economy
ICT-17-2016-2017:	Big	data	PPP:	Support,	industrial	skills,	
benchmarking	and	evaluation	
ICT-18-2016:	Big	data	PPP:	privacy-preserving	big	data	technologies
@BYTE_EU www.byte-project.eu
Membership
◦ Open	to	individuals	and	
organisations
◦ 4 envisioned	membership	
categories
◦ interested	party
◦ associate	member
◦ full	member
◦ ambassador
@BYTE_EU www.byte-project.eu
Interested	party
Description
••Contact	list
••Identify	key	issues
••Identify	sectors	of	
interest
••Participate	in	
discussions	with	peers
Opportunities
••Stay	informed	and	
interact
••Participate	in	
consultations
Engagement
••Low-level	– reactive
••Occasional	
teleconference/meeting
@BYTE_EU www.byte-project.eu
Associate	member
Description
••Contact	list
••Identify	key	issues
••Identify	sectors	of	
interest
••Participate	in	
discussions	with	peers
••Regularly	contribute	to	
focus	areas
••Review	BBDC	outcomes
Opportunities
••Stay	informed	and	
interact
••Participate	in	
consultations
••Participate	in	research	
and	innovation	projects
Engagement
••Regular	teleconferences
••Occasional	meeting	or	
annual	workshop
@BYTE_EU www.byte-project.eu
Full	member
Description
••Contact	list
••Identify	key	issues
••Identify	sectors	of	interest
••Participate	in	discussions	
with	peers
••Regularly	contribute	to	
focus	areas
••Review	BBDC	outcomes
••Commit	resources	to	
BBDC	activities
Opportunities
••Stay	informed	and	
interact
••Participate	in	
consultations
••Participate	with	priority	or	
lead research	and	
innovation	projects
••Support	or	take	part	in	
BBDC	management
Engagement
••Regular	teleconferences
••Occasional	meeting	or	
annual	workshop
••Letter	of	intent	
(120h/year	– 0.75PM)
••Participation	in	annual	
relevant	meeting
••Potential	BDVA	
membership
@BYTE_EU www.byte-project.eu
Ambassadors
Local	contacts,	partners	and	institutions
Contact	with	local	initiatives
Obtain	local	input	for	the	community
Disseminate	results	and	represent	the	community	locally
Organise	joint	co-branded	events
@BYTE_EU www.byte-project.eu
Group	work
Roam and	brainstorm around 3	focus	points
◦ Strategy and	sustainability
◦ Mission,	objectives,	activities
◦ Advertising	and	expanding the	community
◦ Venues,	contacts,	related networks
◦ You name it!
◦ Community	name and	identity after the	end	of	BYTE
@BYTE_EU www.byte-project.eu
Funding opportunities
Cooperation agreement with	another community	(e.g.	BDVA)
Corporate/Government sponsorship
EU	funding (e.g.	H2020)
Funding from	Member States
Annual membership fee and	member contributions
Crowdfunding
Conference	fees
Standardization Bodies
Business	Areas (e.g.	Joint	Industry Programs	for	Big	Data	in	Automotive,	Defense,	Oil &	Gas,	Energy,	
Transport and	other sectors)
Service	fees
BYTE Big Data Community Workshop
@BYTE_EU www.byte-project.eu
You name it!
Big	Data	Social	Club
Big	Data	for	[social]	good
Big	Data	Crew
Big	Data	Fellowship
EU	Big	Data	ClearingHouse (EU	BiDCH)	– Neutral 3rd	party
EU	Big	Data	Trust	(EU	BiDT)
EU	Big	Data	Advisory (EU	BDA)
EU	Big	Data	Society
EU	Big	Data	Agency
@BYTE_EU www.byte-project.eu
Contributing	to	the	BDVA
◦ Focus	areas	for	2016
◦ Smart	cities	(Anna	Melchor,	Smart	City	Valencia)
◦ Health	(Aggelos Liapis,	Athens	University,	BYTE	AB)
◦ Environment	(Wenbo Chu	and	Giovanni	Rum,	GEO	
Secretariat)
◦ Small	groups	discussion	to	integrate	BYTE	findings
Smart	cities
This	case	study	has	focused	on	the	creation	of	value	from	potentially	massive	amounts	of	urban	data	that	emerges	through	the	
digitalised	interaction	of	a	city’s	users,	i.e.	of	citizens	and	businesses,	with	the	urban	infrastructure.	The	economies	of	digital,	
especially	big	data,	favour	monopolistic	structures,	which	may	pose	a	threat	to	the	many	SMEs	in	cities.	However,	open	source	
and	open	platforms,	open	data,	and	even	open	algorithms	crystallise	as	a	shortcut	and	“technology-driven	form	of	
liberalisation”	accompanying	the	big	data	movement	in	cities,	which	has	the	potential	to	level	the	playing	field	and	even	spur	
more	creativity	and	innovation.	Nonetheless,	monetisation	of	big	data	remains	a	moving	target.	Investments	by	the	private	
sector	need	to	be	secured	by	reduction	or	compensation	of	future	uncertainties,	otherwise	the	current	state	of	lack	of	
investments	will	remain.	Similarly,	with	the	increasing	potential	of	machines	that	learn,	old	jobs	consisting	of	simple	tasks are	
also	at	risk.	New	skills	are	required	and	will	create	new	jobs,	but	numbers	are	most	likely	not	equal.
As	for	the	social	and	ethical	externalities,	the	potential	of	big	data	to	be	used	for	social	good	is	immense,	especially	in	the	
digitalising	city.	However,	the	reliance	on	data-driven	services	needs	a	debate	on	how	we	can	assure	enough	equality	when	
there	are	so	many	different	reasons	why	not	all	citizens	will	reap	value	from	data	in	equal	amounts.	This	may	be	due	to	the	
digital	divide	we	have	been	aware	of	for	a	while	now,	or	to	entirely	new	challenges	through	recent	technological	
breakthroughs	such	as	deep	learning,	which	enable	machines	to	learn	and	take	over	simple	tasks,	such	as	counting	cars	or	
recognising	letters.	Moreover,	trust	in	computing	methods	for	big	data	may	be	harder	to	establish	if	their	rationale	cannot	be	
easily	explained.	Furthermore,	businesses,	critical	infrastructures,	and	lives	may	rely	on	big	data	algorithms.
Since	new	sources	of	data	create	new	ways	that	data	can	be	misused	(including	sensitive	personal	data),	this	case	study	
questions	the	suitability	of	the	current	legal	framework	based	on	data	ownership.	Indeed,	the	shift	towards	big	data	may	imply	
that	data	as	well	as	algorithms	to	mine	the	data	are	required	commodities	to	create	value	through	user	experience	and	
services.
Finally,	political	externalities	include	losing	control	to	big	data	actors	outside	Europe.	Indeed,	big	data	businesses	can	improve	
the	European	economy,	but	require	a	unified	European	data	economy	with	accordingly	unified	policies.
Health
This	case	study	has	focused	on	the	use	of	genetic	data	by	a	public	health	data	driven	research	organisation.	Overall,	this	case	study	highlights	a	number	of	
positive	societal	externalities	that	flow	from	genetic	research	and	rare	gene	identification,	which	is	facilitated	through	the	utilisation	of	big	health	data.	
Concerning	economical	externalities,	one	important	result	is	cost	saving	for	healthcare	organisations	that	are	gained	through more	accurate	and	timely	
diagnoses	and	efficient	treatments.	This	is	particularly	important	when	dealing	with	rare	genetic	disorders	that	may	not	otherwise	attract	the	attention	that	
disorders	and	health	issues	affecting	the	wider	population	do.	In	addition,	the	utilisation	of	big	data	in	healthcare	produces	another	economic	externality	in	
that	it	potentially	generates	revenue	especially	through	the	development	of	marketable	treatments	and	therapies,	and	the	innovation	of	health	data	
technologies	and	tools.	Nevertheless,	research	initiatives,	such	as	the	institute	of	the	case	study,	are	naturally	subject	to financial	restrictions	and	cost	savings	
measures	implemented	by	governments.
On	the	societal	and	ethical	side,	the	identification	of	rare	genetic	disorders	provides	treatment	opportunities	for	the	patient, as well	as	more	effective	
diagnostic	testing	for	future	patients	and	a	greater	understanding	of	rare	genetic	disorders	generally.	In	addition,	analyses of genetic	data	enables	treating	
clinicians	to	provide	a	range	of	other	healthcare	services	for	family	members,	including	genetic	counselling.	Beyond	the	initial purpose	for	the	data	collection,	
there	is	limited	or	no	reuse	of	genetic	data	due	to	legal	and	ethical	issues.	However,	data	reuse	may	become	a	stronger	focus in the	future	for	the	purpose	of	
producing	additional	benefits	for	patients	and	society.	There	will	likely	be	an	increase	in	focus	on	research	for	the	purpose of developing	personalised	
medicine	treatments,	which	focuses	on	improved	treatment	based	on	patient	drug	metabolism.	Whilst	the	positive	social	impacts of reusing	genetic	data	are	
obvious,	ethical	considerations	will	remain	at	the	forefront	of	any	policies	supporting	the	repurposing	of	genetic	data,	especially	as	it	is	sensitive	personal	
data.	There	are	potential	negative	impacts	linked	to	the	utilisation	of	big	data	in	healthcare	such	as	over-medicalisation	of	an otherwise	healthy	population;	
discrimination	based	on	the	stratification	on	genotype	or	in	relation	to	health	insurance	policies;	and	incidental	findings	discovered	when	data	is	analysed.	
For	example,	cancer	genes	may	be	discovered	alongside	the	identification	of	rare	genes	or	other	genetic	mutations.	
Since	health	data	is	by	its	very	nature	sensitive	data,	this	case	study	highlights	legal	risks	associated	with	data	protection	and	data	security.	In	particular,	
anonymisation is	a	legal	requirement	that	is	challenging	to	achieve	with	genetic	data.	The	issue	of	data	protection	and	information	privacy calls	for	the	
development	of	adequate	protections	that	balance	the	right	to	personal	data	protection	whilst	fostering	innovation	in	the	digital	economy.	Although	data	
security	preservation	measures	ensure	compliance	with	standard	data	protection	requirements,	they	can	also	hinder	further	research,	which	in	turn,	could	
lead	to	new	developments	and	treatments.	Lastly,	threats	to	intellectual	property	rights	can	arise	in	relation	to	subsequent	uses	of	big	health	data,	such	as	in	
relation	gene	patenting	(and	licensing)	of	new	drug	therapies,	or	if	it	were	to	be	included	in	works	protected	by	copyright.
Concerning	political	externalities,	the	availability	of	big	amounts	of	data	will	enable	politicians	to	have	more	information	about	different	situations	in	the	
health	sector	and	thus	a	better	understanding	that	may	lead	to	improve	their	decision-making	and	increases	the	investments	in	healthcare.
Environment
This	case	study	has	been	conducted	in	the	context	of	an	earth	observation	data	portal	(GEOSS),	a	global-scale	initiative	for	better	
understanding	and	controlling	the	environment,	to	benefit	Society	through	better-informed	decision-making.	On	the	positive	side,
the	use	of	big	data	is	credited	with	having	strong	implications	on	the	economic	growth,	e.g.	sea	data	for	fishing	nations	and
weather	data	for	tourism,	for	the	mere	direct	effects	on	the	IT	sector	such	as	opportunities	for	infrastructure/hardware/data
centres,	and	rent-sharing	possibilities	for	computing.	However,	big	data	could	as	well	be	seen	as	a	threat	by	traditional	services,	
for	example	in	the	weather	forecasting	sector.
Our	analysis	of	social	and	ethical	externalities	shows	the	effectiveness	of	data-intensive	approaches	in	improving	the	governance	
of	environmental	challenges,	supporting	safe	and	environment-friendly	operations.	This	has	implications	on	the	robustness	of	the
environment	to	recover	after	stressing	events	(resilience),	especially	in	urban	context,	as	well	as	on	the	actual	quality	of	life	and	
human	health.	On	the	other	hand,	big-brother-effect	and	manipulation,	real	or	perceived,	can	be	problematic.	In	fact,	as	human	
society	is	an	integral	part	of	the	environment,	especially	in	urban	context,	the	fear	of	data	abuse,	privacy	violation	and	the	like,	
may	hamper	participation	and	engagement.	More	subtly,	also	excessive	trust	in	data-intensive	applications	has	been	highlighted	
as	a	possible	negative	implication,	in	that	it	would	encourage	the	false	believe	that	the	dynamics	of	the	environment	can	be	
captured	quantitatively,	overlooking	qualitative	aspects	that,	instead,	remain	fundamental	to	comprehend	it.
With	respect	to	legal	externalities,	the	growing	reliance	on	data	in	the	environment	sector	is	certainly	highlighting	many	
shortcomings	of	the	current	legal	frameworks,	e.g.	on	IPR,	privacy,	and	authorisation	to	use	the	data.	Potential	problems	are more	
prominent	when	considering	different	legislations	such	as	the	principle	of	full	and	open	exchange	of	data	that	is	simply	
inconsistent	with	some	of	the	current	national	policies.	Legal	support	for	citizens	in	data-related	issues	is	arguably	going	to	
become	a	public	service,	in	the	future.	Besides,	incompatibilities	in	the	legal	frameworks	in	different	countries	are	seen	as
inhibitors	that	need	to	be	adapted,	in	order	to	remove	legal	barriers.
Finally,	political	externalities	include	increased	transparency	and	accountability,	since	choices	will	have	to	be	based	on	measurable	
and	observable	indicators.	However,	there	is	a	risk	of	depending	on	external	sources,	particularly	provided	by	big	players.	In	this	
regard,	the	environment	community	is	concerned	about	the	imposition	of	commercial	products	as	de	facto	standards,	causing	an	
implicit	vendor	lock-in	for	their	maintenance	and	evolution.	The	use	of	GEOSS	map	data	is	a	potential	source	of	political	tensions,	
e.g.	with	regards	to	disputed	or	otherwise	sensitive	areas.	As	Europe	leads	the	innovation	in	the	spatial	sector,	the	shift	to	a	more	
intensive	use	of	data	in	the	environment	sector	may	put	Europe	in	a	primary	role	on	the	political	scene.
@BYTE_EU www.byte-project.eu
Stay	tuned
http://byte-project.eu/byte-community
@BYTE_EU www.byte-project.eu
BBDC	contacts
◦ Lorenzo	Bigagli (lorenzo.bigagli@cnr.it),	Jarl	Magnusson	(jarl.s.magnusson@dnvgl.com)
◦ Coordination	and	general	organisation
◦ Edward	Curry	(edward.curry@insight-centre.org),	Umair ulAssan (umair.ulhassan@insight-
centre.org)
◦ Impact	and	development
◦ Martí Cuquet (marti.cuquet@sti2.at),	Csilla Gödri (godri@niif.hu)
◦ Communication	and	outreach
◦ Rachel	Finn	(rachel.finn@trilateralresearch.com)
◦ Institutional	liaisons	(EC,	BDVA,	etc.)
@BYTE_EU www.byte-project.eu
See	you	soon…
◦ Parallel	session	on	Social	&	Legal	aspects
◦ 14:45,	this	same	room
◦ BYTE	Final	Conference
◦ 9	February	2017,	London	(TBD)
… and	thank you for	joining!

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