Linked Data: some social challenges

L ink ed Da ta social challengessom e tech & michele barbera <barbera@netseven.it> @barbz79it

CHALLENGES2

SOCIAL

CHALLENGES3

LINKED

ECONOMY

smart data now! Unità Web of Data <spaziodati.eu> <netseven.it> <fbk.eu>

Semantic

provocative

failed*.*

produced

research

papers

years,

ontology?!

really

failed...

we’re

working

engineering

little

semantics

way... Semantic

Web Linked

Semantic

Web Linked

Data Web

it’s

technology

it’s

definetely

it’s

linking

things

together

your web site DATA IS LESS VALUABLE WHEN SILOED

because

context

content

xcontent

linking

t e chs o m e es i s s u

SCALABILITY

size? Flexibility,

dinamicity,

scalability by Giovanni Tummarello

dataspaces by Giovanni Tummarello

summaries 12M

relationshipsClass Level http://test01.sindice.net/szydan/dataset-view/dataset/default/www.bbc.co.uk by Giovanni Tummarello

summaries 12M

relationshipsClass Level 10B

relationships http://test01.sindice.net/szydan/dataset-view/dataset/default/www.bbc.co.uk by Giovanni Tummarello

streaming

linked

versioning moved deleted SPOT

DIFFERENCE

<self_promotion>

SIREn Data Collection Settings 500M web data documents  Cluster of 4 nodes (RDF, RDFa, Microformat, etc.)  2 nodes for indexing 200K datasets  2 nodes for querying 50B triples  Replication Indexing Performance Services Full index construction takes  Keyword and structured queries approx 24 hours  Dataset search 436K triples / second  >> 99% uptime

SIREn Data Collection Settings 500M web data documents  Cluster of 4 nodes (RDF, RDFa, Microformat, etc.)  2 nodes for indexing 200K datasets  2 nodes for querying 50B triples  Replication spaziodati.3scale.net Indexing Performance Services Full index construction takes  Keyword and structured queries approx 24 hours  Dataset search 436K triples / second  >> 99% uptime

</self_promotion>

so ci al is su es

THINKING

thinking

tables

thinking

tables

thinking

tables

thinking

tables

thinking

tables

thinking

tables

thinking

tables

thinking

tables

thinking

tables

thinking

tables u_id f_id 1 2 1 3 3 4 4 3 id name age affiliation 1 Michele 33 net7 2 Mario 32 unipi 3 Silvia 28 unifi 4 Irene 27 unitn Institution City net7 pisa unipi pisa unifi firenze unitn trento

thinking

graphs? pisa Firenze place Trento e e plac plac unipi net7 unifi e plac ks ks unitn wor wor friend frien ks d michele

(33) wor silvia

(28) frien d irene

(27) fri end mario

e.g.soci al

gr ap hs Mario

342-2345672 ,

G Giovanni

333-231345 iuseeppe

Bologna,

UgoAnna

328-3422345,

Trento,

VerMamma

050-342212 di

PisaAntonio

051-34245 6,

Bologna

A.A.A.**

“you

don’t

you’re

talking

about”

AAA library wikidb scholarly

community

tbl“The

inviting

sharing

losing

control.

Indeed,

“Net,

control

greater

benefits” “ It

getting

excited

“ connections,

rather

nervous”

3)info

non-info

http-range-14 http://example.com/resource/CNR http://example.com/page/CNR 303

redirection? http://example.com/data/CNR http://www.cnr.it/homepage#CNR http://www.cnr.it/homepage hash

caution! http://universities.org/italy#cnr ns:president <a_person> ns:department <some_department> ns:department <some_department> owl:sameAs http://www.example.com/cnr ns:creator <jonnhy

developer> ns:date 12

2011 ns:name “The

Website”

4)Open

Assumption

Kbase Seat

reserved Seat

reserved OWA CWA is

reserved?UNKNOWN NO

difficult

understand-

inconsistencies

anduniversal

systems-

We’re

familiar

reasoning-

existing

D a ta d i e my? k o n na

L o e c

datasets-

frequently

updated Linked

<h1 id="name"><span class="fn n"> <span class="given-name">Michele </span> <span class="family-name">Barbera</span> </span></h1>

www.rottentomatoes.com

Schema.orghttp://www.linkedopendata.it/schema-org-e-le-responsabilita-dei- monopolisti

knowledge

Freebase

Geonames

DBpedia

schema.org

search

statistics? opaque/hidden

identifiers

reusable

5 billion 40%global data mobile phones 30 billion pieces of content shared growth in projected generated per year vs 5% on facebook every month 235 terabytes 15 out of 17 data collected by US library of Congress 60% potential increas in retailers’ sectors in US have more data stored per company than the US Library in april 2011 operating margins possible with big data of Congress BIG DATA AND INFO OVERLOAD IN USE IN 2010: 250$ billion potential annual value 600$ billion 300$ to Europe’s public sector potential annual consumer surplus from using billion administration - more than GDP of Greece personal location data globallypotential annual value to US health care (more than double the total annual 60% 140.000-190.000 more deep analytical talent positions health care potential increase and 1,5 million more data-savvy managers spending in Spain) in retailers’ operating margins need to take full advantage of big data possible wiith big data with big dat only in United States

“ “ The

deleted

instead

added. Paul

Houle,

http://lists.w3.org/Archives/Public/public-lod/2012Jun/0038.html

digital

public

goods)

r e p r e s e n t s

u n p r e c e d e n t e d

opportunity

(local?

vertical?)

economy

preserve

cultural

diversity

“ The

matter

streams

public

private

sector

[...] Clearly,

research,

engineering,

policy

making

Economy

exploitation

unprecedented

wealth

“ data

become

Future

Europe.

WE CAN DO IT!!!

you.@barbz79it

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Linked Data: some social challenges

by Michele Barbera on Jun 19, 2012

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