The document discusses how the Knowledge Media Institute at the Open University in the UK has developed a linked data platform, called data.open.ac.uk, to provide open access to various types of data from across the university, including course information, research publications, podcasts, videos, and more. It describes some of the technical and organizational challenges in developing the platform, and highlights how it has enabled new uses of the university's data and inspired innovation both within the university and more broadly in open education.

1. Linked Data at The Open University:
From Technical Challenges to
Organizational Innovation
Mathieu d’Aquin (@mdaquin)
Knowledge Media Institute
Stuart Brown (@stuartbrown)
Communication Services
The Open University

2. What are we doing in the industry
track?
Knowledge Media Institute:
leading research center on
semantic web technologies:
– Ontology
engineering, ontology
discovery
– Knowledge
representation, reasoning, pr
oblem solving
– Interoperability, services, onto
logy matching, data linking
– 80 researchers/research
assistants/PhD Students/
Academic-related staff
– 100s of publications

3. And So?
KMi is a department of the Open
University
The Open University:
– The largest university in the UK:
250K students per year, 8000
associate lecturers, a big campus
in Milton Keynes
– Created in 1969
– Almost entirely open and distance
learning
– 13 regional center, more national
centers, courses available in a
large number of countries
 Big organization = crazy
information infrastructure

4. data.open.ac.uk
The first linked data platform providing
open information from a across a whole
university

5. Lots a (types) of data
Course information:
580 modules/ description of the course, information about the levels and number of
credits associated with it, topics, and conditions of enrolment.
Research publications:
16,000 academic articles / information about authors, dates, abstract and venue of the
publication.
Podcasts:
2220 video podcasts and 1500 audio podcats / short description, topics, link to a
representative image and to a transscript if available, information about the course the
podcast might relate to and license information regarding the content of the podcast.
Open Educational Resources:
640 OpenLearn Units / short description, topics, tags used to annotate the
resource, its language, the course it might relate to, and the license that applies to the
content.
Youtube videos:
900 videos / short description of the video, tags that were used to annotate the
video, collection it might be part of and link to the related course if relevant.
University buildings:
100 buildings / address, a picture of the building and the sub-divisions of the building
into floors and spaces.
Library catalogue:
12,000 books/ topics, authors, publisher and ISBN, as well as the course related.
Others…

6. Collect Extract Link Store Expose
Scheduler Ontologies
Cleaning RDF file (add)
rules URL redirection
RDF file
RSS Delete (1) rules
(delete)
Extractor RDF Add (2)
ORO, podcast Cleaner
Web
RSS feed
RDF file (add) Server
RDF file (delete)
RSS Updater
RDF
New items Extractor SPARQL
Obsolete items Each datasets
endpoint
Entity
XML Name
Updater System
Lib, courses, loc URI creation
rules
Planning + Logging
Generic process Dataset specific process

7. First Issue: Convincing People
Not the technical bit… that’s easy
data.open.ac.uk is now a core infrastructure
element of the Open University. But it took a lot of
talking…
- Identify data Where most of
LD Team - Get sample data
Initial
- Identify Copyright Issues the work is
Meeting with
Data
Data Owner
- Identify possible links done
Owner - Identify users and usage
- Find reusable ontologies
LD Team Data Data LD Team
- Map onto the data
Modeling Modeling
- Identify uncovered parts Data
LD Team sessions Validation
- Define URI Scheme Owner
URI Creation
Development Deployment
LD Team Rules
of Extractor
Definition

8. What works
Not changing the way people work:
– Pull data from feed exported by
the original system. Not changing
them, or introducing any additional
difficulty.
– Data taken “as is”, with an effort
on understanding its original
modeling.
Bring the user along, add value
– Data re-modeling as linked data
creates positive side effects on
the original data
– Talk about possible links and
usages first
– Improve the usability of the data
produce by the institution = make
the work of people more visible
and useful

9. So, what it is that we can do?
Oh no! We can’t find a killer app!
“Small things” that either were impossible before, or
are now trivial to do
Ben, in the corridor:
Hey! Your linked data thing, can it tell me what are the
podcasts attached to courses that we no longer offer?
Time difference in answering this question:
x weeks  5 minutes
not really feasible  easy

10. Simple works… A lot of “simple” works!
Social
Resource
Discovery
Research
Exploration

11. Example: map of buildings
Interactive map of
Open University
Buildings in the UK
Built in 1 hour
Connected to
Ordnance Survey for
location based on
post-codes
Allowed us to find
out about issues in
the data.

12. Example: Connecting our resources
Show the courses and podcasts that connect to a piece of open
educational resources.
Trivial with data.open.ac.uk
Impossible to do before (!)

13. Simple things as examples: Inspire
The simple apps above are
not demonstrating particularly
impressive technical
achievements: They are here
to show what can be done
(easily)

14. Study at the OU mobile application
(Communication and student services)

15. Supporting Research Evaluation
(Research School)

16. Discovery of open educational resources
(Open Media Unit and KMi)

17. So the technology is mature enough after
all?
No!
Providing an open SPARQL endpoint is a very bad
idea:
1 query can kill everything (and it does… often)
Our approach: leave things open, fix when it breaks
Example: Mirror triple-stores updated in parallel
Example: Simple cache based on serving static files
for most popular URIs/query. The cache is updated
with the data.
Keep the standard/open/application independent
interface: Free and easy reuse helps innovation, an
API is an obstacle.

18. Conclusion
Starting point:
Showing off our
technology, information integration
issues, access to open information
Where we got:
(Open) innovation, competitive
advantage, Linked Data as part of
the backbone of the University’s
information infrastructure, new
systems built doing linked data by
design
BTW, anybody has a better word
than backbone for linked data based
information infrastructure?

19. Going further…
We are not the only University (anymore):
data.southampton.ac.uk, data.ox.ac.uk, data.aalto.fi, data.uni-
muenster.de…
Ultimately, the University does not count: moving to
“education à la carte”
mEducator
Orgs., Buid Research
The Open outputs
ings, Locati
University
ons Data.gov.uk
education
Learning
resources
OrganicEduNet University of
Muenster, DE
University of University of
Bristol Southampton

20. What we need: Community effort
LinkedUniversities.org

21. What we need: A reusable toolset
Marimba4lib.com

22. What we need: Compelling, global use
cases
LinedUp-Project.eu

23. Thanks!
More info:
http://data.open.ac.uk
http://lucero-project.org
http://linkeduniversities.org
http://linkedup-project.eu
http://mdaquin.net
mathieu.daquin@open.ac.uk

24. What it provides
• Linked Data: URIs resolve with
redirects to RDF and HTML, content
negotiation
• CC-By license on everything
• SPARQL endpoint (SPARQL 1.1)
• That’s all…

25. Integration
• Big organization = crazy
information infrastructure
• Special focus on open/public
information:
– Course information
– Open educational resources
(OpenLearn)
– Multimedia material: Podcast
repository, iTunes U, openly
licensed Youtube videos
– Open access repository of
research publications

26. Example: Charting our offering
Showing
basic charts
generated
from the
answers to
SPARQL
queries
The only
effort
required is
coming up
with the

27. Lean-back OU podcast channel on Google
TV
(IT services)

28. More on using the users…
Obviously: Won’t be convinced by technological
blabla
Show examples of what it can do! (BTW we have a
problem here…)
More importantly: ask them what they would like to
do. We asked: communication services, library
people, student services, marketing
services, faculties… (they are very creative)
A typical email of my inbox (inspired by a true story):
Hi Mathieu,
Stuart told me that your linked data thing might
help with the problem Laura had with Guy’s
system.
Can we have a chat?
Tx, Ben.

29. The OU’s presence in the media
(Media relations)
Academics in “Arts and Topics most commonly
Humanities” most often involved mentioned by news outlets
with the media (in number of news own by the BBC (in number
items) of news items)