LarKC Tutorial at ISWC 2009 - Introduction

Agenda for today October 2010 @ ISWC Time Presentation Title Presenter 08.30-09.00 Setup 09.00 – 09.30 Introduction to LarKC Frank van Harmelen 09.30 – 10:30 LarKC Architecture Michael Witbrock 10:30 – 11:00 Coffee break 11:00 – 11:30 Hands-on: work with an existing LarKC workflow Florian Fischer 11:30 – 12:00 LarKC Data Layer Florian Fischer 12:00 – 13.00 Builder a LarKC DECIDEr & create a workflow from existing plugins Luka Bradesko, Blaz Fortuna 13.00 – 14:00 Lunch 14:00 – 14:30 Distributed Processing in LarKC Michael Witbrock 14:30 – 15:30 Hands-on: Building a LarKC Plugin and integrating it in a worflow Florian Fischer 15.30 – 16:00 Coffee break Eyal Oren 16:00 – 17:00 Hands-on: the Urban computing workflow Emanuele della Valle 17.00 – 18:00 Wrap up - Discussion and feedback Frank van Harmelen

Welcome to the 2nd LarKC Early Adopters Workshop Frank van Harmelen Vrije Universiteit Amsterdam

Health Warning
Today is a WORK shop
we first tell you some stuff,
then you do stuff
(repeat)
Goal of today:
ours: show LarKC to outsiders < who are we >,
yours: <tell us now>

Goals of today
At the end of today you will
understand the goals of LarKC
understand the architecture of LarKC
have hands on experience with platform and plugins
At the end of the day, you will be able to:
roll your own LarKC plugin
roll your own LarKC application

Goals of LarKC LarKC = a platform for large scale reasoning “ LarKC's value is as an experimental platform . LarKC is as an environment where people can go to replicate (or extend) their results in an environment where all the infrastructural heavy lifting has already been taken care of ” Quote from EU Project Officer:

Goals of LarKC LarKC = a platform for large scale reasoning Semantic web research is stifled by the complexity of writing a large scale engine, with services for data access, storage, aggregation, inference, transport, transformation, etc, Physics research has dealt with a similar problem by providing large scale infrastructure into which experiments can be plugged. The idea behind LarKC, which I found so compelling, is that people who wanted to build small scale plugins, for example, plugins for some non-standard deduction, or transformation of text to triples, or estimating the weights for relational models, could do so, taking advantage of the EU's investment in a platform with significant capabilities .“ Quote from US high-tech CTO:

Goals of LarKC LarKC = a platform for large scale reasoning “ Significant progress is sometimes made not by making something possible that was impossible before, but by substantially lowering the costs of something that was only possible before at high cost” Quote from EU Reviewer:

What do we mean by:
reusable components
reconfigurable workflows
provide infrastructure needed by all users:
storage & retrieval
registration of plugins
communication (plugin2datalayer, plugin2plugins)
synchronisation (anytime behaviour)
remote execution (abstracts from local/remote storage)
remote data-access (abstracts from local/remote invation)
(will) provide instrumentation & measuring
(will) provide caching & data-locality
integration of very heterogeneous components
heterogeneous data: unstructured text, (semi)structured data
heterogeneous code: Java, scripts, remote services ("wrap & integrate")
LarKC = a platform for large scale reasoning

What do we mean by: LarKC = a platform for large scale reasoning
raw large numbers
from performant data-layer
from parallel deployment of plugins
from load-balancing strategies
…
interaction of multiple components
e.g. avoid reasoning through selection: SELECT + REASON
allowing for incompletenes and anytime behaviour
but also from not only from

What do we mean by:
not only: deductive inference over given axioms
but also:
LarKC = a platform for large scale reasoning LarKC = a platform for large scale reasoning LarKC = a platform for large scale reasoning LarKC = a platform for large scale reasoning where do the axioms come from? ( IDENTIFY ) which part of knowledge & data is required ( SELECT ion) when is an answer "good enough" or "best possible" ( DECIDE r) non-deductive inference (inductive, statistical) ( REASON er) “ ReaSearch: integrating reasoning and search "

Overall approach of LarKC
Very lightweight platform
communication, synchronisation, registration
LarKC = “SPARQL endpoint on steroids”
The real work happens in the plugins
LarKC gives you:
very scalable datalayer
standardised interfaces for combining components
utilities & infrastructure
Three types of LarKC users:
people building plugins
people configuring workflows
people using workflows

How to deploy LarKC
All local:
platform local, plugins local
Example: workstation
Calling remote plugins:
platform local, (some) plugins remote
Example: laptop
Fully remote
platform remote (eg. as a web-service)
plugins remote
Example: cluster

Why would people (like you) want to use LarKC
workflow builders:
easier to get some application scenario running
Plugin builders:
easier integration with components by others,
wider take up of your own component by others

What does a workflow look like? Identifier Info Set Transformer Reasoner Decider Selector Query Transformer Data Layer

What does a workflow look like? Identifier Info Set Transformer Reasoner Decider Selector Query Transformer Data Layer Data Layer Data Layer Data Layer Data Layer

What does a workflow look like? Identifier Info Set Transformer Reasoner Decider Selector Query Transformer

What does a workflow look like? Identifier Reasoner Decider Selector

What does a workflow look like? Reasoner Decider Selector

What does a workflow look like? Identifier Info Set Transformer Reasoner Decider Selector Query Transformer Identifier Identifier Info Set Transformer ETCETERA

What does a DECIDEr look like?
Can be a hardcoded sequence of plugins
Can be a self-configuring selection of plugins
Can make run-time decisions on progress and resource consumption
Coded as:
Java
a Cyc knowledge base
...
as long as it complies with the DECIDE r API

Already any plugins available?
5x IDENTIFY
3x TRANSFORM
10x SELECT
4x REASON
4x DECIDE
Sometimes sophisticated, sometimes simple
Sometimes novel, sometimes wrapped
existing web-services (e.g. Sindice, Swoogle)
another RDF store (geo-queries in Allegrograph)
a very large (workflow-based) system (GATE)
existing reasoners (Jena, Pellet, Cyc, IRIS)
XSLT scripts (XML-2-RDF)
spreading activitation (new)
RDF-2-weightedRDF (new)

Goals of LarKC, and where we are
Scalable: > 10 9 triples, lazy pipes
Reconfigurable: plugins with standard API’s
Open: Apache license
heterogenous: TRANSFORM, wrappers
experimentation: wrap & integrate
allow incompleteness: IDENTIFY, SELECT
enable distribution: plugin containers
anytime behaviour: streaming APIs
web-enabled: remote plugins & data

What we will not show today
Available but not demo’d:
lot’s of plugins
C-SPARQL: extension of SPARQL to enable stream-querying
cognition-based heuristics (e.g. selection rules, stopping rules)
very cool data-sets
Linked Life Data (1.4B explicit, 2.3B closure, 1.3M links)
Milan traffic grid (2M explicit +2Tb sensor-data (to come))
Interest-enhanced DBLP (615k authors + interests)
LDSR (358M explit + 512 inferred, 100m URIs)
very large/fast inference engines: MarVIN, Reasoning-Hadoop
Not yet available (but will be):
plugin-farming on remote CPU’s (cloud, cluster)
instrumentation & measuring
smart data caching

Agenda for today October 2010 @ ISWC Time Presentation Title Presenter 08.30-09.00 Setup 09.00 – 09.30 Introduction to LarKC Frank van Harmelen 09.30 – 10:30 LarKC Architecture Michael Witbrock 10:30 – 11:00 Coffee break 11:00 – 11:30 Hands-on: work with an existing LarKC workflow Florian Fischer 11:30 – 12:00 LarKC Data Layer Florian Fischer 12:00 – 13.00 Builder a LarKC DECIDEr & create a workflow from existing plugins Luka Bradesko, Blaz Fortuna 13.00 – 14:00 Lunch 14:00 – 14:30 Distributed Processing in LarKC Michael Witbrock 14:30 – 15:30 Hands-on: Building a LarKC Plugin and integrating it in a worflow Florian Fischer 15.30 – 16:00 Coffee break Eyal Oren 16:00 – 17:00 Hands-on: the Urban computing workflow Emanuele della Valle 17.00 – 18:00 Wrap up - Discussion and feedback Frank van Harmelen

LarKC Tutorial at ISWC 2009 - Introduction

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