John Breslin - NUI Galway - @johnbreslin linkd.in/johnbreslin

Data Analytics and Industry-Academic Partnerships:

An Irish Perspective

First: Ireland and Chile! •  John/Juan Garland, governor of Valdivia; Ambrosio O’Higgins (from

Sligo), Chile governor and founder of first transcontinental postal service; his son Bernardo O’Higgins, first president of independent Chile; John/Juan McKenna and Thomond O’Brien, Chilean-Irish independence fighters; grandson Benjamin McKenna, writer and liberal politician; George O’Brien, founder of the Chilean navy; Patricio Lynch, Chilean-Irish naval hero (grandfather from Galway) and ancestor of Che Guevara; drill head used in rescue of Atacama miners was made in Ireland (County Clare)

•  http://brenspeedie.blogspot.com/2010/11/what-did-irish-ever-do-for-chile.html (a colleague of mine from NUI Galway wrote this)

•  http://www.irlandeses.org/0610griffin1.htm

•  http://en.wikipedia.org/wiki/Irish_Chilean

1. Menlo Castle (origin of Menlo Park in Silicon Valley, California)2. Computer Museum of Ireland (at DERI)3. NUI Galway (where Stoney, namer of the “electron”, was a prof.)4. Java’s (Zachary Quinto, AKA Spock, waited on tables here)

OnePageCRM

Insight

Ex Ordo

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G A L W A YT E C H M A P

European Microcity of the Future

5. Claddagh (birthplace of the Claddagh Ring, and Angel from Buffy!)6. Ignite TTO Business Innovation Centre7. Galway Technology Centre8. Innovation in Business Centre (at GMIT)9. Marine Institute

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@johnbreslin@technologyvoice@startupgalway#upgalway#gaillimhabuv1.201405271500bit.ly/galwaytech

NUI Galway introduction

NUI Galway in brief •  Established in 1845:

•  One of Ireland’s seven universities

•  105 hectare campus (260 acres)

•  120 links with universities around the world

•  17,300 students:

•  12,500 undergraduates, 3,600 postgraduates, 1,200 other

•  2,541 staff:

•  1,078 academics, 1,015 admin and support, 448 research

•  90,000 alumni in over a hundred countries

Famous alumni •  Alice Perry, first female graduate engineer in the

world, 1849

•  Michael O’Shaughnessy, a Civil Engineering graduate from the University in the 1880’s, was San Francisco Chief Engineer, and commissioned the Golden Gate Bridge

•  Honorary degrees to Nelson Mandela, Hillary Clinton

•  TV and movie star Martin Sheen (The West Wing’s President Bartlet) studied here in 2006/2007

•  Includes the largest School of Engineering in Ireland (finished 2011, 14,000 square metres, €43 million)

•  Information Technology, Electrical and Electronic Engineering, Biomedical Engineering, Mechanical Engineering, Civil Engineering, DERI (now Insight)

The College of Engineering and

Informatics

Insight Centre for Data Analytics

Incorporating DERI (Digital Enterprise Research Institute) at NUI Galway

200RESEARCHERS 8INSTITUTIONS 30PARTNERS €88MFUNDING

1 = 10

bytes 18

exabyte

1000,000,000,000,000,000

1 = 10

bytes 18

exabyte

20,000 x all of the printed material in the

US Library of Congress. Or all of the words spoken by humans. Ever!

1 = 10

bytes 18

exabyte

6 !

hours

But, we now create this much information every

1 = 10

bytes 18

exabyte

Volume. Velocity. Variation. +Veracity.

A PARADIGMSHIFT

algorithm!!

data

algorithm !!

data

Politics

Epidemiology

Sport

FROM PATTERNS TO PREDICTIONS

From simple inertial sensing…

… to longitudinal gait analysis.

Detecting gait-cycledeviations ⇒ falls prediction

Predicting functional decline.

PARTICIPATORY SENSING

TURNING DATA INTO DECISIONS

Using sensor data to optimise forestry resources during harvesting.

Stem volume prediction, yield management etc.

Remote sensing + autonomous cutter control.

TURNING DATA INTO KNOWLEDGE

Creating a network of knowledge.

Data ⇒ Semantics

Semantics ⇒ Discovery

e.g. discovering links between drugs, genes, and diseases.

MINING PATTERNS FROM REAL-TIME SOURCES

Physical shockwaves travel at 4.8km/sec but knowledge of the earthquake traveled at 70km/

sec to Galway.

14:42 Earthquake strikes.""14:43 First tweet from @Bacanalnica in nearby Managua.""14:44 120 secs later the first tweets are posted.

Insight Centre

Future Projects Legacy Projects

28

Peracton (DERI spin out)

SindiceTech (spin out)

Case studies: finding insights in business data

1.  Finding expertise and content

2.  Holistic energy management

3.  AYLIEN text analytics

4.  Social analytics for recommendation and communities

•  Saffron (saffron.deri.ie) extracts knowledge from text, with business applications in expert finding, community detection, recommender systems, and enterprise search, e.g.:

1.  Ecommerce system with Kennys Bookshop to analyse book descriptions and reviews to extract a fine-grained book topic categorisation for use in book recommendation to customers

2.  EnRG entity relatedness for applications in semantic search (EnRG is built over a large matrix on Wikipedia and using the DBpedia ontology)

1. Expertise and content

Kennys Bookshop

2. Holistic energy management

Managing energy related to:

•  Office IT

•  Data centres

•  Facilities

•  Business travel

•  Daily commutes

Keep in mind business context:

•  Energy expended

•  Finances required

•  Resource allocation

•  Human resources

•  Asset management

Making smart buildings smarter (have air conditioning at CO2 peaks)

Energy management software can be unintuitive/difficult to use

We can do better!

More challenges •  Technology and data

interoperability: data scattered among different systems, multiple incompatible technologies make it difficult to use

•  Interpreting dynamic and static data: sensors, ERP, BMS, assets databases

•  Need to proactively identify efficiency opportunities

•  Empowering actions and including users in the loop

•  Understanding of direct and indirect impacts of activities

•  Embedding impacts within business processes

•  Engaging users

Applica

tions

Energy Analysis Model

Complex Events

Situation Awareness Apps

Energy and Sustainability Dashboards

Decision Support Systems

Linked

Dat

a

Support

Se

rvic

es

Entity Management

Service

Data Catalog

Complex Event Processing

Engine

Provenance Search & Query

Sourc

es

Adapter Adapter Adapter Adapter Adapter

Energy saving applications

Energy awareness

Semantic event processing

Collaborative data management

Cloud of energy data

Linked sensor middleware

Resource Description Framework (RDF)

Semantic sensor networks

Constrained application protocol (CoAP)

Linked energy intelligence

You…

…are part of a team…

…sharing a ‘shell’

3. AYLIEN text analytics •  AYLIEN is based in Dublin, backed by SOS Ventures

•  7 employees, started as B2C, switched to B2B in 2014

•  Vision to “extract reality from data” (information retrieval domain)

•  Research collaboration with NUI Galway through John (sentiment analysis on large-scale social media)

•  http://bresl.in/aylientechcrunch

Text Analysis API (TAA) ●  A package of easy-to-use

tools for extracting information and insights from any text

●  Language detection

●  Supported Languages (EN, DE, PT, ES, IT, FR)

●  168 customers

●  Academic, ad intelligence and brand protection, sentiment analysis/opinion mining, PR and media, CRMs, education, psychology/interest graph

●  Endpoints:

o  Extraction

o  Classification

o  Summarisation

o  Concept/entity extraction

o  Hashtag suggestion

o  Sentiment analysis

How is TAA used? o  Three major methods for deploying text analytics

services: API (via the “cloud”), on-premises deployments, other integrations

o  TAA is mainly provided using an API/subscription model (monthly) via Mashape or 3scale

o  Additional integrations with Google Spreadsheets and other platforms (Telerik, Azuqua)

o  In future: on-premises deployment, subscription (yearly), custom solutions (bespoke)

Under the TAA hood… •  Based on Machine Learning (ML)

techniques (supervised, unsupervised and semi-supervised)

•  Extraction: useful for scraping text, media and metadata from web pages

•  Annotate text, media and metadata in a training set

•  Extract a set of heuristic rules and use them to extract text, media and metadata

•  Summarisation: Extracting n-best key sentences from a document, based on heuristics and a sentence similarity matrix (initially), learning over time

•  Classification and document-level sentiment analysis: assigning a label to any piece of text (“sports”, “technology”, “positive”, “negative”)

•  Create word vectors from an annotated dataset

•  Train a classifier, use it to predict future classes for a new instance

•  Similar to a spam filter

•  Concept extraction: Find what is mentioned in a document and disambiguate them based on contextual clues e.g. Apple is mentioned, how do we find out if it’s the fruit or the company?

TAA market (SMEs) Segments: SMEs, enterprises

Size: “many times the $2bn forecast”

US, UK, Germany, Spain, India

See “Text Analytics 2014: User Perspectives on Solutions and Providers”

Market: natural language processing [related markets: machine learning, text mining]

SME segment: AlchemyAPI, Semantria (Lexalytics), Textalytics,

Fluxifi

Enterprise segment: SAS, IBM, Lexalytics

Main target: SMEs

Differentiators: feature-richness, quality, price, progression

http://www.programmableweb.com/news/how-5-natural-language-processing-apis-

stack/analysis/2014/07/28

4. Social analytics •  Some applications include cross-domain

recommendations, community detection and evolution monitoring

•  SemStim (Cisco)

•  Whassapi (Volvo Ocean Race)

•  SociaLens (ROBUST)

SemStim A spreading activation based algorithm tuned for RDF-based social semantic networks

How does it work?

Travel destinations:

Movies:

User profile with DBpedia URIsfrom multiple source domains

Cross-domain recommendation algorithm using DBpedia as

background knowledgeRecommendations

from target domains

Input Background knowledge Cross-domain output

http://advansse.deri.ie/

Advansse

Whassappi: real-time event and topic detection

GraphDB

NetworksSlices

Ranked  Communities,  Users  and  Labels

Feedback:Users  to  Follow

Raw  Tweets

RelationalDB

Relevant  Tweets

Signal:Updated  Communities  Data

Tweets,  Topics  &Communities

Relationships

Initial  Tweets  &  Communities  Data

TweetsClassifierTwitter Stream

Filter

Entities  Extraction

AnalyticsStreaming  Flow

On-­‐demand  Flow

System  Triggered  Flow

Data  Flow  Types

Mobile  App

SociaLens: insights into enterprise communities

Thanks! Any questions?