Get your organization’s feet wet with Semantic Web Technologies

Tutorial by André Torkveen (Aker Solutions), Magnus Stuhr and Jens Kilde Mjelva (both Computas).

Prepared for 8th Semantic Days Conference, held in Stavanger, Norway on May 28th, 2013.

Tutorial «rig»

3 x 50 minutes slots : Basically too little time (even after being cut down)

André Torkveen : Business track (Advisor, Aker Solutions)

Magnus Stuhr : Tech. track I (Knowledge Engineer, Computas)

Jens Kilde Mjelva : Tech. track II (Knowledge Engineer, Computas)

TopBraid Composer : The modeling (and querying) tool that we use

Apache Jena (stack) : The Semantic Web tooling platform that we use

Ubuntu Linux : The underlying operating system (set up on VMware)

Why at all bother to use such techie snake oil (called SWTs)?

1) It mimics human knowledge capture/expression

2) Based on mature, scalable open standards that are increasingly adopted

3) Explicit handling of meaning does away with semantic conflicts (that otherwise lurk behind the corner)

4) Easy to combine pieces of info from across different datasources & -sorts

5) Linked data establishes «self-documentation»; real-world subjects can be referred directly into the information graph

6) Enables learning (by letting humans & machines inspect the graph)

7) Simple to extend (compared with competing technologies)

Purpose

Provide key footing/a starting point to continue a ‘skills journey’ after you’ve returned home

Present an approach that helps gather different parties to contribute into a joint workflow effort

Potential to begin UNLOCKING diverse data residing in different systems in your organization

NOT: «Everything»

Introductory remarks

1) How many here have yet to be introduced to …Traditional data modeling using E-R or UML?

…Metadata, ‘plain’ data and code …inside of XML?

…Semantic Web Technologies? (hereafter abbreviated ‘SWT’)

…Integration of server systems? (…using file imp/exp. or middleware)

…multi-layered/‘n’-tiered Web applications?

2) Some word of advice: Soon (after today): Fill in your competency blanks

Always #1: Start off by representing reality!

Always #2: Exercise pragmatism!

What we’re going to do workflows for Business

track

Technical

track

: rig your environment

: make data extracts

: «dress up» (RDF’ify)

: make front-ends (GUI)

: document everything

: query interfaces (SPARQL)

pick a case

make a simple model

play around

present it all!

Business : Pick a case

The business representative needs to understand the nature of his/her business well!

In order to be of any use, the case that you choose must reflect your business needs well!

Don’t «stretch it» —better to extend it later

Business : A side-step

Before we can continue with this, we’ll actually have to visit another topic …to get everyone introduced to same foundation. First it’ll get worse, then better :-)

(right now)

(new situation)

(having to learn even more ’stuff’)

(you’ve actually ‘gotten it’)

adopting prerequisites

gaining understanding PAIN

< a b u i l d i n g >

Side-track: Some say tomato…

Side-track: What do authoritative sources say?

«The Nexus of Forces is Driving the Adoption of Semantic Technologies, but What Does That Mean?» Source: Gartner, May 16th 2013

Let’s take a look at the SWT building blocks

Side-track: Understanding the foundation

Triplets: The foundation of the Semantic Web

(resource) (property) (value)

Graphs: When triplets go to work.

parent

child

child

child

grand-parent

attribute

attribute

Side-track: Build a model that REPRESENTS REALITY (here: the many ISO standards covering the Oil & Gas industry)

Slide 14

Side-track: Real-life structures may be very complex

– we must search for relevant simplifications

Business (now back on track): Modeling exercise

Exercise objectives Know difference between abstract Classes and specific Instances

Get a notion of how to use Relations/Associations

LATER: Try working according to a methodical approach

Capture

Concepts

Define

Structure

Implement

Manage

: common model

: individual projects

: te

rmin

olo

gy

: platform governance

: fields & attributes

: data material/ learning

Model for our chosen case: Staffing

project

period

person

availability

skill

(type)

proficiency

(level)

contribution

(amount)

mustFitWith

hasA

characterizes needsA

enables

Overall workflow Business

track

Technical

track

: rig your environment

: make data extracts

: «dress up» (RDF’ify)

: make front-ends (GUI)

: document everything

: query interfaces (SPARQL)

pick a case

make a simple model

play around

present it all!

Tech : Rig your environment

A2A

(design & build time) (run time)

E X T E R N A L L Y

I N T E R N A L L Y

B2B B2C

B2E

Portal Server

Partner Gateway

Portal server

some kind of «common carrier» (…an ESB or something)

Ad

apter

Ad

apter

Ad

apter

LoB

LoB

LoB

Web srv.

catalogue

catalogue

Web srv.

IDE

Modeler

Tech : Rig your environment

Tech : Rig your environment

Tech : Rig your environment

Tech : Rig your environment

Borrowed with permission from Martin Ringel,

© IBM Corporation 2007

The Model : Understanding of a domain is captured

The Content/dataset : Human readable (…but often partial)

Content modification : Intermediary step to apply Turtle format

Modified Content : Machine interpretable (…but ‘scattered’ graph)

prefix: reference to another vocabulary that we borrow concepts from

component separator ➝ triplet separator ➝ .

predicate list separator ➝ ; object list separator ➝ ,

Important changes that happen during in the process

Overall workflow Business

track

Technical

track

: rig your environment

: make data extracts

: «dress up» (RDF’ify)

: make front-ends (GUI)

: document everything

: query interfaces (SPARQL)

pick a case

make a simple model

play around

present it all!

Business : Play around

Use the application’s provided Graphical User Interface (GUI) to RUN QUERIES. This is how you familiarize yourself with the datasets: The more you learn, the more qualified you become to point out more relevant aspects of/angles into the content.

Utilize your new-earned knowledge and TALK MORE with your data scientists. Together you have established an excellent foundation for understanding your business.

SHARE with others! Next out, you can gain momentum by extending the solution! The discussion about which improvement suggestions to prioritize is valuable in itself.

Business : Present it all!

Show what you have, explain only essentials

Prepare calculations that illustrate payback potential of integrating via linked data

– Empathize EXTENDIBILITY; reuse across business cases

Prepare suggestions on how to proceed

Manage the expectations and the exercise

Tell us how things go! (…e.g. via Twitter to @quiet_listening, @MagnusStuhr and @JensKM)