Ontology2 PlatformPaul Houle, Founder Ontology2

Bill Freeman, President KMSolutions

(774) 301-1301

O2

kms

OUR PLATFORM

For organizations handling complex, heterogeneous, and big data from a large number of sources, structured, unstructured and semistructured.We rapidly (in terms of computer time and configuration time) combine, curate, and index your data, both in batch and in real-time.Based on our experience with Freebase (the basis for the Google Knowledge Graph), we combine Hadoop technology with SQL and NoSQL databases on a next generation cloud technology;Focus: quality, usability, cross-domain integration and inference, standards-driven interoperability, open-source components

Current State as we understand it

Technical: Need for extreme agility

• High-quality, curated data is important• Limited by MySQL speed/scalability (and slow schema changes because of row store)• Difficulty of handling taxonomy/ontology/schema changes• Dealing with data loss and broken inter-concept links caused by changes• Difficulty of linking entity between silos; inability to infer accurate, high quality relationships

between collections• Need for clean, normalized data for input to machine learning algorithms• Need ability to manage spatial and temporal data• To keep up with competition: It must be easy has to make changes, fast to implement changes• Need for data typing beyond SQL (currency, length, time interval, etc.) to support inference and

user interfaces• Infrastructure built ad-hoc is difficult to document, maintain, expand

Business Challenges• To be discussed

Benefits from cloud-native Infovore™ platform

Index construction does not interfere with user-facing real-time services

Development, Test and Staging do not interfere with production

Batch Jobs Don’t Interfere with Interactive Services

Next Generation Cloud

• Near Bare Metal PerformanceHardware Virtualization

• Incredible Speed• Predictable Response TimeSSD Drives

• Take advantage of competition between cloud provider

• Use existing on premise capacity; control physical security, flexible options

Hybrid cloud

FilesDatabases

Hadoop Mappers

Hadoop Reducers

Hadoop Powered Index Construction

We deliver the exact data required by your index

builders, partitioned, sorted and filtered for maximum

efficiency.

Index Construction in Hybrid CloudNew Index Construction Never Conflicts With Production

time

Old index (multiple copies for throughput & availability)

Source data

Test

Clone

New Index

Terminate andrecover

resources

Batch Index plus Real-Time IndexEffortless and efficient scalability

Message Queue

Bulk Data time stamped master data

small real-time index

large bulk index

merger

RESULTS

New approach to data managementA FRAMEWORK FOR DATA QUALITY

Multiple sources of instance data

Factsclassifications

Reference data…

ExamplesTest Data

Training DataRequirements

Quality metrics

WE DELIVER FAST CYCLE TIME

HYBRID CLOUD: No waiting for hardware

PARALLEL DATA PROCESSING: Handle large data sets quickly

DEVOPS AUTOMATION: Little system administration overhead

EFFICIENT DATA REPRESENTATION: Rapid turnaround, low hardware cost

COMPETITIVEADVANTAGE

MINIMIZE WASTED CYCLESautomation eliminates errors

MINIMIZE TIME AROUND CYCLE

Ontology2 Spatial HierarchyFreebase data enriched for Language+Contextual Performance

Global coverage30+ languages

250 countries

36,000 regions1.5M names

400,000 cites & towns8M names

Large alternative name bank + hierarchical constraint =• Resolution of jurisdictions in international business listings• Resolution of place names in free text

Extensive Graph-Based SchemaMETA-MODEL SYSTEMATICAL DESCRIBES PROCESSES AND THINGS

RDFStypes + properties

XML SCHEMAData types

EXTENDEDData types

DECLARATIVE MAPPINGS

CSV RDBMS XML …

DECLARATIVEHINTS

formatting

editing

…

LINGUISTIC +CONTEXTUAL

KnowledgeRepresentation

SOLVES ISSUES, SEE SLIDE 3 !

Compiledrepresentation

databases

COMMON TEXT FORMATS

CSV, XML, JSON, RDF

FAST BINARY FORMATS

THRIFT, AVROPROTOCOL BUFFERS

RAW DATAEvent-driven real-time pipeline

applications

MERGEDPRODUCTION

INDEX

batch pipeline

MODEL-DRIVEN ARCHITECTUREHANDLING CONTENT AND DATA WITH CONTEXTUAL UNDERSTANDING

SUMMARY

For organizations handling complex, heterogeneous, and big data from a large number of sources, structured, unstructured and semistructured.We rapidly (in terms of computer time and configuration time) combine, curate, and index your data, both in batch and in real-time.Based on our experience with Freebase (the basis for the Google Knowledge Graph), we combine Hadoop technology with SQL and NoSQL databases on a next generation cloud technology;Focus: quality, usability, cross-domain integration and inference, standards-driven interoperability, open-source components

Bill Freeman, President KMSolutionswilliam.freeman3@outlook.com (774) 301-1301