Welcome to LD4KD 2015#LD4KD2015

Ilaria Tiddi - @IlaTiddiMathieu d’Aquin - @mdaquinClaudia d’Amato - @cldamat

Yes, this is a small workshop...

2 paper presentations out of 4 papers submitted

but

A lot of interest from both communities (KD/ML and Linked Data).LD4KD is more than a set of paper presentations.

Working on existing opportunities and challenges and the way they can be better supported/addressed.

Program10:00 – 10:15 Welcome10:15 – 10:45 Linked Data for Knowledge Discovery: the story so far

10:45 – 11:15 Mehwish Alam and Amedeo Napoli, Navigating and Exploring RDF Data using Formal Concept Analysis

11:15 – 11:30 Coffee Break

11:30 – 12:00 Denis Krompaß and Volker Tresp, Ensemble Solutions for Link-Prediction in Knowledge Graphs

12:00 – 12:45 Demo session12:45 – 13:00 Wrap-up and conclusions

Linked Data for Knowledge Discovery: the story so far

LD for KD - KD with LD

LD for KD - KD with LD

A set of te

chniques and methods to

extract m

eaningful inform

ation

patterns fro

m raw data

LD for KD - KD with LD

A set of te

chniques and methods to

extract m

eaningful inform

ation

patterns fro

m raw data

A set of p

rinciples and te

chnologies

for sharin

g and integratin

g data

through the archite

cture of the W

eb

LD for KD - KD with LD

LD for KD - KD with LD

A complex,

information-in

tensive

process

LD for KD - KD with LD

A complex,

information-in

tensive

process A global, distrib

uted

and collaborative

informatio

n source

LD for KD - KD with LD

LD for KD - KD with LD

LD for KD - KD with LD

LD for KD - KD with LD

LD for KD - KD with LD

LD for KD - KD with LD

LD for KD - KD with LD

Needs a more systematic understanding...Of the way the properties of the process of KD and of the information source of LD create new opportunities and challenges for both communities.

Knowledge Discovery Linked Data

Talking about communities: ?

Started in LD4KD 2014http://events.kmi.open.ac.uk/ld4kd2014/

http://goo.gl/NEu1d7

A collaborative document to share information about issues, challenges, tools and methods at the intersection of Linked Data and Knowledge Discovery

Opportunities Linked Data as Input

Large, global, accessible, convenient, multilingual - Separation of data and process - Easily extended, integrated, enriched.

Link Discovery Using DM/ML techniques to find connections across disparate datasetsExploiting links across dataset for richer data, and richer patternsCan this be done “on the fly”, i.e. within DM/ML process?

Background knowledge to enrich the KDD processCan Linked Data be part of the bottom arrow in the KDD diagram? A global, universally accessible knowledge base of almost everything?

Is it too hard?

“RDF and SPARQL - are they really complicated?”

“Not really, but SPARQL is not what ML researchers want to worry about. Most of us don't even like SQL. Just a CSV file is the easiest format. It's messy, but we really don't care.”

ChallengesLinked data is a graph

but is this really an issue?

Linked data is a distributed, collaborative graph accessibility issues, link explosion, terminationneed to build the graph on the fly, not all data is known at the start

Linked data is incomplete and biasedAnd we don’t know the bias - how to evaluate KDD that uses Linked Data?

Linked data is redundant, unbalanced and unreliablenoisy, bad formating (no control), lack of documentation, which ID/source to choose and what is the impact?

And we haven’t even started talking about...

Mr. Slow

and

Mr. Nosey

Continuing this year...Start with the practical aspects: What tools and applications exist, through which we can explore the use of linked

data in KD, and from which we can learn how to solve some of the challenges

Discuss, Contribute, Questionand of course

Enjoy the workshop!#LD4KD2015