![Disrup)ve
Innova)on
A
disrup've
innova'on
is
an
innova)on
that
disrupts
an
exis)ng
market.
The
term
is
used
in
business
and
technology
literature
to
describe
innova)ons
that
improve
a
product
or
service
in
ways
that
the
market
does
not
expect,
typically
by
lowering
price
or
designing
for
a
different
set
of
consumers.
In
contrast
to
"disrup)ve"
innova)on,
a
"sustaining"
innova)on
does
not
have
an
effect
on
exis)ng
markets.
Sustaining
innova)ons
may
be
either
"discon)nuous"[1]
(i.e.
"transforma)onal")
or
"con)nuous"
(i.e.
"evolu)onary").
Transforma)onal
innova)ons
are
not
always
disrup)ve.
Although
the
automobile
was
a
transforma)onal
innova)on,
it
was
not
a
disrup)ve
innova)on,
because
early
automobiles
were
expensive
luxury
items
that
did
not
disrupt
the
market
for
horse-‐drawn
vehicles.
The
market
for
transporta)on
essen)ally
remained
intact
un)l
the
debut
of
the
lower
priced
Ford
Model
T
in
1908
by
making
higher
speed,
motorized
transporta)on
available
to
the
masses.[2]](https://image.slidesharecdn.com/cybermondayoverstockentire-101216055040-phpapp02/85/Semantic-Web-and-web-of-commerce-Disruptive-technology-3-320.jpg)
![Disrup)ve
innova)on
The
Theory
Christensen
defines
a
disrup)ve
innova)on
as
a
product
or
service
designed
for
a
new
set
of
customers.
Christensen
argues
that
disrup)ve
innova)ons
can
hurt
successful,
well
managed
companies
that
are
responsive
to
their
customers
and
have
excellent
research
and
development.
These
companies
tend
to
ignore
the
markets
most
suscep)ble
to
disrup)ve
innova)ons,
because
the
markets
have
very
)ght
profit
margins
and
are
too
small
to
represent
significant
growth.[5]](https://image.slidesharecdn.com/cybermondayoverstockentire-101216055040-phpapp02/85/Semantic-Web-and-web-of-commerce-Disruptive-technology-4-320.jpg)
![Wikipedia
Defini)on
of
an
Ontology
In computer science and information science, an ontology is a formal representation of the knowledge by a set of
concepts within a domain and the relationships between those concepts. It is used to reason about the properties of
that domain, and may be used to describe the domain."
In theory, an ontology is a "formal, explicit specification of a shared conceptualization".[1] An ontology provides a
shared vocabulary, which can be used to model a domain — that is, the type of objects and/or concepts that exist,
and their properties and relations.[2]"
Ontologies are used in artificial intelligence, the Semantic Web, systems engineering, software engineering,
biomedical informatics, library science, enterprise bookmarking, and information architecture as a form of knowledge
representation about the world or some part of it. The creation of domain ontologies is also fundamental to the
definition and use of an enterprise architecture framework."
Not
restricted
to
a
hierarchical
structure
as
with
a
taxonomy](https://image.slidesharecdn.com/cybermondayoverstockentire-101216055040-phpapp02/85/Semantic-Web-and-web-of-commerce-Disruptive-technology-11-320.jpg)
Semantic Web and web of commerce - Disruptive technology
- 1. The Seman)c Web and The Web Of Commerce The Seman)c web has the poten)al be completely disrup)ve or completely opportune to online commerce. Barbara Starr Email: bstarr@Ontologica.us Twitter: @BarbaraStarr
- 3. Disrup)ve Innova)on A disrup've innova'on is an innova)on that disrupts an exis)ng market. The term is used in business and technology literature to describe innova)ons that improve a product or service in ways that the market does not expect, typically by lowering price or designing for a different set of consumers. In contrast to "disrup)ve" innova)on, a "sustaining" innova)on does not have an effect on exis)ng markets. Sustaining innova)ons may be either "discon)nuous"[1] (i.e. "transforma)onal") or "con)nuous" (i.e. "evolu)onary"). Transforma)onal innova)ons are not always disrup)ve. Although the automobile was a transforma)onal innova)on, it was not a disrup)ve innova)on, because early automobiles were expensive luxury items that did not disrupt the market for horse-‐drawn vehicles. The market for transporta)on essen)ally remained intact un)l the debut of the lower priced Ford Model T in 1908 by making higher speed, motorized transporta)on available to the masses.[2]
- 4. Disrup)ve innova)on The Theory Christensen defines a disrup)ve innova)on as a product or service designed for a new set of customers. Christensen argues that disrup)ve innova)ons can hurt successful, well managed companies that are responsive to their customers and have excellent research and development. These companies tend to ignore the markets most suscep)ble to disrup)ve innova)ons, because the markets have very )ght profit margins and are too small to represent significant growth.[5]
- 5. What is the Seman)c Web Seman)c web synonymous with Web 3.0 ? Seman)c meaning PuXng structured informa)on into the web in some machine readable format Not about the rela)onships between links, but about rela)onship between things, and the proper)es of those things A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities By Tim Berners-Lee, James Hendler and Ora Lassila
- 6. What is the Seman)c Web (cont) “The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. It is a collaborative effort led by W3C with participation from a large number of researchers and industrial partners. It is based on the Resource Description Framework (RDF)” World Wide Web Consor)um hZp://www.w3.org/2001/sw/
- 7. RDF -‐ Triples • RDF (Resource Descrip)on Framework) A resource is anything you want to describe. An RDF triple contains a subject, predicate, and object. e.g Michael David subject knows object predicate Michael boy subject is-‐a object predicate
- 8. RDF -‐ Triples Michael David subject knows object predicate Michael boy subject is-‐a object predicate translates into (michael knows David) (michael is-‐a boy) and we can infer with the right ontology & inferencing mechanism (michael is-‐a person)
- 9. RDF -‐ Triples (michael knows David) (michael is-‐a boy) (michael is-‐a person) Triple store Or Web 3.0 database
- 11. Wikipedia Defini)on of an Ontology In computer science and information science, an ontology is a formal representation of the knowledge by a set of concepts within a domain and the relationships between those concepts. It is used to reason about the properties of that domain, and may be used to describe the domain." In theory, an ontology is a "formal, explicit specification of a shared conceptualization".[1] An ontology provides a shared vocabulary, which can be used to model a domain — that is, the type of objects and/or concepts that exist, and their properties and relations.[2]" Ontologies are used in artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture as a form of knowledge representation about the world or some part of it. The creation of domain ontologies is also fundamental to the definition and use of an enterprise architecture framework." Not restricted to a hierarchical structure as with a taxonomy
- 12. Ontologies • OWL – Web Ontology Language (OWL 2.0 released) • RDFS – RDF Schema • Some exis)ng standards ontologies: – FOAF -‐ Friend of a Friend -‐ for social networks – SIOC -‐ Seman)cally Interlinked Online Communi)es – Goodrela)ons for e-‐commerce – Geodata – Upper Level Ontology – FOAF -‐ Friend of a Friend -‐ for social networks – SIOC -‐ Seman)cally Interlinked Online Communi)es – Google Ontology – …..
- 13. 13
- 14. RDFa • RDFa is simply RDF in attributes. It adds a set of attribute level extensions to HTML, enabling rich metadata to be embedded within web pages. " • It not only enables triples to be embedded in web pages but also ultimately enables the extraction of triples" In short, this is the means by which we add structured markup to web pages
- 15. SPARQL • SPARQL is an RDF Query Language. • It is a recursive acronym and stands for SPARQL Protocol And RDF Query Language. • Informa)on from linked Datasets can be accessed via SPARQL queries. • Most linked data sources provide SPARQL ENDPOINTS to enable access. • A SPARQL endpoint -‐ provides access to its data via supported SPARQL protocol
- 16. To cut a loooong story short: We go from: a web of documents or hyperlinks, to: a web of data or seman)c links with: linked data and linked datasets. We use RDF to represent the data on the web and we use SPARQL to query the data And RDFa is simply RDF in aZributes.
- 17. Core Concepts: • Not that we have forgoZen about: – RDFS (RDF Schema) – OWL (Web Ontology Language) • & then in summary – RDF (central to all) – Linked Data – SPARQL • RDFa (simply stated as it is html markup)
- 18. So at this point either your head is spinning or You are bored to death because you already know about the seman)c web
- 19. SO … -‐ How is this being used? -‐ What is the extent of adop)on -‐ Who is using it? -‐ How can it be leveraged?
- 20. LOD Cloud Evolu)on The rate of growth has been remarkable Source maintained by: Richard Cygniak and Anja Jentsch. hZp://lod-‐cloud.net
- 21. Oct 2007
- 22. Nov 2007 (1)
- 23. Nov 2007 (2)
- 24. Feb 2008
- 25. Mar 2008
- 26. Sept 2008
- 27. Mar 2009 (1)
- 28. Mar 2009 (2)
- 29. March 5 -‐ 2009 Sem- Wiki- Surge Web- company Radio LIBRIS Central RDF ohloh Doap- Music- space Semantic Resex brainz Audio- Eurécom Flickr Web.org MySpace Scrobbler QDOS SW exporter Wrapper Conference IRIT Corpus Toulouse RAE BBC BBC Crunch 2001 FOAF SIOC ACM BBC Later + John Base Revyu Jamendo Peel profiles Sites Playcount TOTP Open- Buda- Data Guides pest DBLP BME flickr RKB Project Pub Geo- Euro- wrappr Explorer Guten- Virtuoso Guide names stat berg Pisa BBC Sponger eprints Programm Open es Calais New- riese World Linked ECS castle Fact- MDB South- IEEE book ampton Magna- Gov- tune RDF Book Track Mashup DBpedia lingvoj Freebase IBM US CiteSeer LAAS- Census W3C DBLP CNRS Data WordNet Hannover UniRef GEO UMBEL Species DBLP Berlin Reactome LinkedCT UniParc Open Taxonomy Cyc Yago Drug PROSITE Daily Bank Med Pub GeneID Homolo Chem Gene KEGG UniProt Pfam ProDom Disea- CAS Gene some ChEBI Ontology Symbol OMIM Inter Pro UniSTS PDB HGNC MGI PubMed As of March 2009
- 30. March 27 -‐ 2009 ECS South- Sem- Wiki- Surge ampton LIBRIS Web- company Radio Central RDF ohloh Resex Doap- Buda- Music- space Semantic ReSIST brainz Audio- pest Eurécom Project Flickr Web.org MySpace Scrobbler QDOS SW BME Wiki exporter Wrapper Conference IRIT Corpus Toulouse RAE National BBC BBC Crunch 2001 Science FOAF SIOC ACM BBC Later + John Base Revyu Foundation Jamendo Peel profiles Sites Playcount TOTP Open- Data Guides DBLP flickr RKB Project Pub Geo- Euro- wrappr Explorer Guten- Virtuoso Guide names stat Pisa CORDIS berg Sponger eprints BBC Programm Open es Calais RKB riese World Linked ECS Fact- MDB IEEE New- South- Magna- book ampton castle Gov- tune RDF Book Track Mashup DBpedia lingvoj Freebase LAAS- US CiteSeer CNRS Census W3C DBLP IBM Data WordNet Hannover UniRef GEO UMBEL Species DBLP Berlin Reactome LinkedCT UniParc Open Taxonomy Cyc Yago Drug PROSITE Daily Bank Med Pub GeneID Homolo Chem Gene KEGG UniProt Pfam ProDom Disea- CAS Gene some ChEBI Ontology Symbol OMIM Inter Pro UniSTS PDB HGNC MGI PubMed As of March 2009
- 31. July 14 -‐ 2009
- 32. Sept 22 -‐ 2010 Sussex St. Reading Andrews NDL Audio- Lists Resource subjects t4gm MySpace scrobbler Lists Moseley (DBTune) (DBTune) RAMEAU Folk NTU SH lobid GTAA Plymouth Resource Lists Organi- Reading Lists sations Music The Open ECS Magna- Brainz Music DB tune Library LCSH South- (Data Brainz LIBRIS ampton Tropes lobid Ulm Incubator) (zitgist) Man- EPrints Resources chester Surge Reading biz. Music RISKS Radio Lists The Open ECS data. John Brainz Discogs Library PSH Gem. UB South- gov.uk Peel (DBTune) FanHubz (Data In- (Talis) Norm- Mann- ampton (DB cubator) Jamendo datei heim RESEX Tune) Popula- Poké- DEPLOY Last.fm tion (En- pédia Artists Last.FM Linked RDF AKTing) research EUTC (DBTune) (rdfize) LCCN VIAF Book Wiki data.gov Produc- Pisa Eurécom P20 Mashup semantic NHS .uk tions classical web.org (EnAKTing) Pokedex (DB Mortality Tune) PBAC ECS (En- AKTing) BBC MARC (RKB Budapest Program Codes Explorer) Energy education OpenEI BBC List Semantic Lotico Revyu OAI (En- CO2 data.gov mes Music Crunch SW AKTing) (En- .uk Chronic- Linked Dog NSZL Base AKTing) ling Event- MDB RDF Food IRIT America Media Catalog ohloh BBC DBLP ACM IBM Good- BibBase Ord- Wildlife (RKB Openly Recht- win nance Finder Explorer) Local spraak. Family DBLP legislation Survey Tele- New VIVO UF .gov.uk nl graphis York flickr (L3S) New- VIVO castle Times URI wrappr OpenCal Indiana RAE2001 UK Post- Burner ais DBLP codes statistics (FU VIVO CiteSeer Roma data.gov LOIUS Taxon iServe Berlin) IEEE .uk Cornell Concept Geo World data ESD Fact- OS dcs Names book dotAC stan- reference Project Linked Data NASA (FUB) Freebase dards data.gov Guten- .uk for Intervals (Data GESIS Course- transport DBpedia berg STW ePrints CORDIS Incu- ware data.gov bator) (FUB) Fishes ERA UN/ .uk of Texas Geo LOCODE Uberblic Euro- Species The stat dbpedia TCM SIDER Pub KISTI (FUB) lite Gene STITCH Chem JISC London Geo KEGG DIT LAAS Gazette TWC LOGD Linked Daily OBO Drug Eurostat Data UMBEL lingvoj Med (es) Disea- YAGO Medi some Care ChEBI KEGG NSF Linked KEGG KEGG Linked Drug Cpd GovTrack rdfabout Glycan Sensor Data CT Bank Pathway US SEC Open Reactome (Kno.e.sis) riese Uni Cyc Lexvo Path- totl.net way Pfam PDB Semantic HGNC XBRL WordNet KEGG KEGG Linked Taxo- CAS Reaction Twarql (VUA) UniProt Enzyme rdfabout EUNIS Open nomy US Census Numbers PRO- ProDom SITE Chem2 UniRef Bio2RDF Climbing WordNet SGD Homolo Linked (W3C) Affy- Gene Cornetto GeoData metrix PubMed Gene UniParc Ontology GeneID Airports Product DB UniSTS MGI Gen Bank OMIM InterPro As of September 2010
- 33. LOD cloud – Sept 22 2010 Sussex St. Reading Andrews NDL Audio- Lists Resource subjects t4gm MySpace scrobbler Lists Moseley (DBTune) (DBTune) RAMEAU Folk NTU SH lobid GTAA Plymouth Resource Lists Organi- Reading Lists sations Music The Open ECS Magna- Brainz Music DB tune Library LCSH South- (Data Brainz LIBRIS ampton Tropes lobid Ulm Incubator) (zitgist) Man- EPrints Resources chester Surge Reading biz. Music RISKS Radio Lists The Open ECS data. John Brainz Discogs Library PSH Gem. UB South- gov.uk Peel (DBTune) FanHubz (Data In- (Talis) Norm- Mann- ampton (DB cubator) Jamendo datei heim RESEX Tune) Popula- Poké- DEPLOY Last.fm tion (En- pédia Artists Last.FM Linked RDF AKTing) research EUTC (DBTune) (rdfize) LCCN VIAF Book Wiki data.gov Produc- Pisa Eurécom P20 Mashup semantic NHS .uk tions classical web.org (EnAKTing) Pokedex (DB Mortality Tune) PBAC ECS (En- AKTing) BBC MARC (RKB Budapest Program Codes Explorer) Energy education OpenEI BBC List Semantic Lotico Revyu OAI (En- CO2 data.gov mes Music Crunch SW AKTing) (En- .uk Chronic- Linked Dog NSZL Base AKTing) ling Event- MDB RDF Food IRIT America Media Catalog ohloh BBC DBLP ACM IBM Good- BibBase Ord- Wildlife (RKB Openly Recht- win nance Finder Explorer) Local spraak. Family DBLP legislation Survey Tele- New VIVO UF .gov.uk nl graphis York flickr (L3S) New- VIVO castle Times URI wrappr Open Indiana RAE2001 UK Post- Burner Calais DBLP codes statistics (FU VIVO CiteSeer Roma data.gov LOIUS Taxon iServe Berlin) IEEE .uk Cornell Concept Geo World data ESD Fact- OS dcs Names book dotAC stan- reference Project Linked Data NASA (FUB) Freebase dards data.gov Guten- .uk for Intervals (Data GESIS Course- transport DBpedia berg STW ePrints CORDIS Incu- ware data.gov bator) (FUB) Fishes ERA UN/ .uk of Texas Geo LOCODE Uberblic Euro- Species The stat dbpedia TCM SIDER Pub KISTI (FUB) lite Gene STITCH Chem JISC London Geo KEGG DIT LAAS Gazette TWC LOGD Linked Daily OBO Drug Eurostat Data UMBEL lingvoj Med (es) Disea- YAGO Medi some Care ChEBI KEGG NSF Linked KEGG KEGG Linked Drug Cpd GovTrack rdfabout Glycan Sensor Data CT Bank Pathway US SEC Open Reactome (Kno.e.sis) riese Uni Cyc Lexvo Path- way PDB Media Semantic totl.net Pfam HGNC XBRL WordNet KEGG KEGG Geographic Linked Taxo- CAS Reaction Twarql (VUA) UniProt Enzyme rdfabout EUNIS Open nomy US Census Publications Numbers PRO- ProDom SITE Chem2 UniRef Bio2RDF User-generated content Climbing WordNet SGD Homolo Linked (W3C) Affy- Gene GeoData Cornetto metrix Government PubMed Gene UniParc Ontology GeneID Cross-domain Airports Product DB UniSTS MGI Gen Life sciences Bank OMIM InterPro As of September 2010 latest LOD cloud
- 34. Adopters? • UK Government • US Government • BBC (FIFA world cup site dynamically generated using linked data) • Thomson Reuters • Freebase • NY Times • Best Buy • Tesco • Google (More to follow hZp://rdf.data-‐vocabulary.org/#) • Yahoo • Facebook • Oracle • Tons more – Just look at the diversity in the LOD data cloud • …….
- 35. Seman)c Web to Date Seman)c Search
- 36. What is Seman)c Search • Semantic Search is basically the notion of improving search by using metadata or searching on that metadata. • There are several ways that the Search engines on the web may use this to enhance search results. – FIND, rather than SEARCH. • Searching directly on the metadata directly can yield specific answers or results as demonstrated in the following example: Query “Barack Obama Birthday” Results on
- 37. Defini)ve Answer on Top
- 38. Bing Definitive Answer Note: Freebase part of Metaweb acquisition by Google
- 40. Bing leveraged this for quite some )me Definitive answer & enhanced display
- 41. What is Seman)c Search (cont) • Semantic Search is basically the notion of improving search by using metadata or searching on that metadata. • There are several ways that the Search engines on the web may use this to enhance search results. – FIND, rather than SEARCH. • Searching directly on the metadata directly can yield specific answers or results as demonstrated in the following example: • Ran the query “Barack Obama Birthday” on both google, and bing. Obtained the following: – Answer engines rather than Search Engines? • At this point really, a defini)ve answer followed with the standard search result set for that query
- 42. What is Seman)c Search (Cont) • Semantic Search is basically the notion of improving search by using metadata or searching on that metadata. • There are several ways that the Search engines on the web may use this to enhance search results. – FIND, rather than SEARCH. – Another aspect of using metadata such as embedding metadata or semantic markup in web pages could be demonstrated by enhanced displays in search results (e.g. rich snippets in google). Both Google and Yahoo support enhanced displays for RDFa markup.
- 43. Rich Snippets • Google now supports Rich snippets for – People – Events – Businesses and organiza)ons – Reviews – Recipes – Products – Breadcrumbs – Local Search – Video – images hZp://rdf.data-‐vocabulary.org/#
- 44. Rich Snippets • Google now supports Rich snippets for – People – Events – Businesses and organiza)ons – Reviews – Recipes – Products – Breadcrumbs – Local Search hZp://rdf.data-‐vocabulary.org/#
- 47. RDFa for videos
- 48. October 26, 2009
- 49. Events Mar 12, 2010
- 50. Recipes April 13, 2010 50
- 51. Facebook Opengraph protocol based on RFDa April 20, 2010 Enables “semantic Profiling” of users
- 52. April 26, 2010
- 53. July 16, 2010
- 54. Sept 2, 2010
- 55. Sept 22, 2010
- 56. The Demise of Searchmonkey
- 57. Nov 2, 2010 Products now “findable” (more to follow) 57
- 58. Google acquires Metaweb (freebase)
- 59. Nov, 2010 Google Refine
- 60. Yahoo fully supported RDFa for enhanced displays
- 61. Social Networks • While search engines can benefit from access to social networks, social networks can benefit from seman)c metadata in web pages – Example is Facebook’s Open Graph Protocol (also supports RDFa) which allows users to share & like objects (such as products) as opposed to web pages. Enables “Seman)c Profiling” of the users by facebook.
- 62. Generic Web Benefits / Uses • Yahoo stated 15% increase in CTR as a result of enhanced displays, rich snippets in Google • Definitive answers enabled by understanding and leveraging how search engines are searching directly on metadata • Embedding semantic markup in web pages and product pages ultimately makes information “findable” by search engines, enabling them to provide improvements such as definitive answers, enhanced displays, etc • Semantic Profiling and adoption by social networks
- 63. Google supports 3 alterna)ves for microformats for products • Google format • Hproduct • Goodrela)ons • Which do we use & why?
- 64. What can we do with RDFa? • Produce RDFa • Consume RDFa • Build smart applica)ons with consumed RDFa as we now have a triple store and all the reasoning and decision making tools such as those provided by allegrograph
- 65. Google Ontology
- 66. Google Ontology
- 68. hZp://www.overstock.com/Clothing-‐Shoes/ Grane-‐Womens-‐Double-‐breasted-‐Military-‐Coat/ 5237784/product.html
- 69. Consumed RDFa
- 71. Jans will demonstrate how to navigate this in allegrograph to ensure rela)onships set correctly re: nested divs, etc
- 74. LOD meets LOC
- 75. LOD meets LOC
- 76. LOD meets LOC
- 77. 1. Op)mized RDFa in all pages that -‐ serves Google Rich Snippets -‐ serves Yahoo SearchMonkey -‐ is GoodRela)ons valid -‐ is accessible to all client-‐side browser extensions (there will be a lot of such services soon, believe me) -‐ is perfect for any seman)cs-‐aware search engines so that overstock.com offers are visible
- 78. 2. Novel recommender systems based on GoodRela)ons I have quite a lot of novel approaches for GoodRela)ons-‐based recommender systems (in-‐site), which would be very useful for consumer electronics and fashion, in par)cular. 3. Precision E-‐Commerce Content Syndica)on Soon, owners of small sites will be able to syndicate very specific e-‐ commerce content based on GoodRela)ons (same as currently supported by eBay and Amazon, but then across the whole WWW). We have a prototype for this already running, it could be a great new direc)on for overstock. (besides the posi)ve buzz about it).
- 79. hZp://www.ny)mes.com/2010/11/25/technology/personaltech/25smart.html?src=busln Myriad of compe))ve shopping apps already out there, but always room for one more?
- 80. How is this poten)ally disrup)ve The hypothesis: Possible New Consumer market. Good for mama & papa Shops and small business. Also for Overstock. Data exposed that may be lost if only consumed by larger users e.g. google Mama & Papa Online Store RDFa Shoppers Seman)c Random GR based Shopper Shopping apps Web of data – Seman)c Seman)c GR GR based LOC cloud Shopping apps -‐ Based apps
- 81. In the mean)me No longer Beta Help sell on google
- 82. Where do we go from here? • Other means of supplying gr markup hZp://www.jarltech.de is exposing its full catalog with ca. 4,000 auto-‐ID products in RDF/XML (updated several )mes a week!) (not as silly as I first thought) hZp://www.jarltech.de/goodrela)ons.rdf
- 83. Other Ver)cals within retail • New Ver)cal Markets – Automa)ve (Large automo)ve manufacturer recently adopted GR : announcement coming soon) – Financial – Fashion – Real Estate – Tickets – Electronics
- 84. Break Barbara Starr Email: bstarr@Ontologica.us Twitter: @BarbaraStarr