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Thomson Reuters, The Answer Company
ODI SUMMIT
3 NOVEMBER 2015
@DrDanielASmith
DR. DANIEL A. SMITH, SENIOR DEVELOPER, CORPORATE TECHNOLOGY
CREATING THE THOMSON REUTERS
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ABOUT THOMSON REUTERS
2
FINANCIAL & RISK
INTELLECTUAL PROPERTY & SCIENCE
LEGAL
Comprehensive IP & scientific information,
decision support tools & services to enable
governments, academia, publishers,
corporations & law firms.
Critical information, decision support tools,
software & services to legal, investigation,
business and government professionals.
Critical news, information & analytics,
enables transactions, and connects
trading, investing, financial and corporate
professionals.
TAX & ACCOUNTING
Integrated tax compliance and accounting
information, software & services for
professionals in accounting firms,
corporations, law firms and government.
REUTERS NEWS
Powered by more than 2,800 journalists reporting in 20
languages from bureaux around the world, Reuters is
the world’s largest international news organisation.
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ABOUT THOMSON REUTERS
•
Due to growth by acqusition, we
are working with siloed data
•
Segregation of content by
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ABOUT THOMSON REUTERS
•
Benefits: Designed, content
controlled, edited and published
by each business
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KNOWLEDGE GRAPH
Company
name
Thomson Reuters
TRI.TO
primaryQuote
Quote
RIC
1977-12-28
incorporated
http://tr.com
website
TRI
ticker
TOR
exchange
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KNOWLEDGE GRAPH
Thomson Reuters
name
granted
name
Eikon
US20140173400A1
application
2013-10-23
filed
2014-06-19
published
uses
Patent
makes
Product
Company
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KNOWLEDGE GRAPH
Thomson Reuters
name
granted
name
Eikon
US20140173400A1
application
2013-10-23
filed
2014-06-19
published
uses
Patent
makes
Product
Company
Company
name
Thomson Reuters
TRI.TO
primaryQuote
Quote
RIC
1977-12-28
incorporated
http://tr.com
website
TRI
ticker
TOR
exchange
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IDENTITY CHALLENGES
•
Entities can have multiple identifiers
•
e.g. Organisations have IDs all areas:
•
Finance and Risk
•
Tax and Accounting
•
Legal
•
IP and Science
•
News
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ORGANISATION IDENTIFIERS IN FINANCE AND RISK
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MXID
•
NDGSymbol
•
DBSTicker
•
SDCCusip
•
SDCID
•
SEDARIssuer
•
EdCoID
•
VEFirmID
•
VentureEconomicsID
•
TMTCompanyID
•
CIK
•
DisclosureID
•
EedbID
•
GemAlphaNumericID
15
•
RegistrationNumber
•
DunsNumber
•
SinotrustNumber
•
DatastreamFiId
•
RegulatoryId
•
Cusip6
•
TaxId
•
RcpId
•
EfxId
•
EjvExchangeCode
•
Lei
•
DataStreamId
•
AllCode
•
InvestextId
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CONTENT MARKETPLACE
•
Thomson Reuters addressed the problem by introducing an information
governance framework, which:
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Created authorities to maintain common reference points of identity for major objects
(organisations, people, instruments, quotes etc...)
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Used PermIDs as a common method for identity
•
Our customers have the same problems, as does the open data community
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Introducing rules is not practical. Instead, offer a compelling solution that each group or
organisation can make use of independently: Open PermID
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Grow a network effect – an ecosystem – around this de-facto standard
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PERMID AS A USEFUL COMMON REFERENCE POINT
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Specifically maintained for identity reference & not as a side-effect
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Use / context independent – focus is on getting community support & network mass
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Unambiguous, consistent interface, doesn’t need interpretation
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Well-described & maintained relative to the real world
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Stable meaning, persistent, temporal
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Coverage & granularity reflect community needs
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Dependable support over time
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Everyone knows that everyone else can freely access and use it
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Open licensed
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Known quantity to plan against
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Creates a network effect
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TECHNOLOGY STACK
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Content Marketplace
•
Data Item Registry (i.e., ISO/IEC 11179)
•
XML
•
Knowledge Graph
•
Semantic Web
•
RDF, OWL, SPARQL, SPIN, Jena, Sesame
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Big Data
•
Apache Big Data Ecosystem - Hadoop, Spark, Kafka, Oozie, Cassandra, Elastic Search
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BUILDING THE KNOWLEDGE GRAPH
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The Content Marketplace work gave us the linkage through PermIDs
•
Semantic Web and Big Data technologies give a strong starting point to building a
knowledge graph
•
Take those technologies and scale them to:
•
Query or manipulate at scale
•
Provide lots of data and lots of perspectives on data
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BUILDING THE KNOWLEDGE GRAPH
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Build a minimal set of tools to put and get data into the graph
•
Determine the minimum viable set of data to bootstrap the graph
•
Retain federation of data internally
•
Data authorities keep editorial and publishing control as before
•
If we can prove out a knowledge graph of federated data internally, we can use the
same approach to link to customers data and open data
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THOMSON REUTERS KNOWLEDGE GRAPH STATS
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Knowledge Graph: 2.35B triples
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Metadata, Organisations, People: 2.27B triples
-
Inferred Data, generated with SPIN rules [reverse predicates etc.]: 78.3M triples
•
Compared to other large open data sets:
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Wikidata: 367M triples
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DBPedia: 474M triples
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Freebase: 2B triples
-
UniProt: 17B triples
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KNOWLEDGE GRAPHS PROVIDE
MANY VIEWS TO ANSWER MANY QUESTIONS
•
Gives us the ability to provide many lenses over the graph
•
Query for absolute facts
•
Patents issued by a company, litigation history, market capitalisation history
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Also make inferred and abstract connections
•
Sort by litigation history within an industry sector weighted by market capitalisation
•
Combine absolute facts with inferred/abstract connections
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KNOWLEDGE GRAPHS PROVIDE
MANY VIEWS TO ANSWER MANY QUESTIONS
•
Iterate and build layers of queries of increasing sophisticated/complexity to infer
new facts
•
Handle relative truth of facts and data - according to their source
•
Ability to utilise the facts relevant to your product or question
•
Adding additional perspectives as relevant
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KNOWLEDGE GRAPH USE CASE
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KNOWLEDGE GRAPH USE CASE
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