Semantic Technology -Notes From a Beginner

Nils Jacob Berland - PhDX2X Maritime AS

Theano AS

njberland@gmail.com

About NJ Berland

● PhD in informatics○ Stochastic optimization and parallel computations

● Previous work experience○ Telecom - Security and Intelligent buildings○ Oil & Gas logistics - tracking ○ Norwegian University of Science and Technology ○ Molde University College - Oil & Gas logistics

NJ Berland at present

X2X Maritime AS - CTO

● Visualization of oil and gas logistics

Theano AS - CTO

● Stakeholder analysis

Warning!

● I am NOT an expert in Semantic Technology

● I try to build systems that simply work

● And we need existing and good building blocks to help our job

About the presentation

● Talk about how we got started with ST

● Show some examples

● Stimulate your curiosity

Two demos

● Oil & Gas logistics

● Decision makers

Both were created to explore how ST work and how the technology can be used for our products

O&G Logistics

● Containers

○ Are owned by one company

○ Are rented by another company for a period

○ Are handled by other companies for a period

○ Have certificates managed by maybe several companies

○ And are inspected by other companies

O&G Logistics

● Events○ Can be generated by almost anyone○ Events are basically owned by the renter○ The renter can in principle decide who to share

events with○ Events are added continuously

● Rentals○ A rental has a start and finally an end

O&G Logistics

● What is difficult about this?

○ Manage temporal permissions

○ Collect data from various systems

○ View temporal relationships

○ Explore relationships

○ Queries like "who rented a unit at dd:mm:yyyy"?

O&G Logistics

● A demo implementation○ A simulator in Python to generate events○ A basic ontology○ Jena for triples○ Node.js to route data from Jena to web clients○ Some Python "middleware" for SPARQL

● Demo of "LogisticsHub light"

Code to insert events

...

data = {

'id': 'event_' + str(uuid.uuid4()),

'timestamp': timestamp,

'type': type,

'ccu': ccu,

'location': location

}

sparql_wrapper.setQuery("""

PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>

PREFIX : <http://ontology.org/>

INSERT DATA { :%(id)s rdf:type :%(type)s;

:timeStamp "%(timestamp)s";

:hasCCU :%(ccu)s;

:atLocation :%(location)s;

} """ % data)

Code to view active rentals

PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>

PREFIX : <http://ontology.org/>

select * where

{

?rental rdf:type :Rental;

:hasRenter ?renter;

:hasStart ?startdate;

:hasCCU ?ccu.

FILTER NOT EXISTS {?rental :hasEnd ?enddate}.

}

ORDER BY ?startdate

O&G Logistics

● Evaluation○ Fun to make○ A working demo required some weeks work with a

few good people○ Some of the queries are in practice hard problems

for SQL○ For graph databases it is quite easy○ Extremely simple to expand and add new systems○ Jena has proved very robust○ Easy to port to e.g. AllegroGraph or other "big triple

stores"○ Gave us a lot of insights into LogisticsHub

Decision Makers

● Show how the parliament of Norway and bureaucrats are connected by gender, place, topics, etc.

● Combine data from public sources (http://data.stortinget.no/eksport) and our own data

Decision Makers

● A demo implementation○ A basic ontology - Based on FOAF○ Jena triple store○ Python pull from public sources and push to Jena○ Python pull our own data and push to Jena○ Node.js to route data from Jena to web clients○ Some Python "middleware" for SPARQL○ D3JS.org for visualization○ Data is pulled from Jena when new

configurations are chosen

● Demo

Decision Makers

● Evaluation

○ Fun to make○ Less work than the Logistics demo - with the

right people!○ Easy to expand

■ With other data sources■ Other data types

○ Jena works nice

What is cool about ST?

● Get started fast - really!● SPARQL - once you understand it!● Due to the graph structure - some queries are

simple and fast

● Easy to add new data and expand● An instance can be a member of many classes

(I can be a programmer and dancer at the same time)!

Always consider hybrids

● SQL or NoSQL for storage○ e.g. MongoDB for event logs

● RDF for interesting queries● JSON for API's● SPARQL "construct" to extract data for in-

memory analysis

So where do you start?

● Forget the buzzwords● Read "Programming the semantic web" by

Toby Segaran, Colin Evans and Jamie Taylor - preferably do the examples yourself

● Make some working systems that use triple stores

● You are never alone - there are many free tools available!

The big conclusions

● Google Trends○ "Semantic Web" is not so interesting

anymore○ "Linked Data" is a stable term○ SPARQL is rising○ Neo4j is growing faster

● ST is however○ Fun○ Surprisingly simple to use○ Very efficient in some situations○ Over-hyped

The big conclusions (cont)

● ST enable○ Less monolithic systems○ Faster prototyping○ Inferencing and create "data that is not there"○ Linking data!

● Test out alternatives and hybrid solutions○ Pure graph databases○ Schema-less NoSQL - e.g. MongoDB

Thank you!