Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Frank van Harmelen
All the questions
we couldn’t ask
10 years ago
Creative Commons License:
allowed to share & remix,
but ...
The bad news:
you’re going to get 3 talks
1. Where are we now?
– The Semantic Web in 4 principles & a movie
– Did we get a...
Semantic Web:
What is it?
“The Semantic Web” a.k.a. “The Web of Data”
http://www.youtube.com/watch?v=tBSdYi4EY3s
P1. Give all things a name
P2. Relations form a graph
between things
P3. The names are addresses on the Web
x T
[<x> IsOfType <T>]
different
owners & locations
<analgesic>
P1+P2+P3 = Giant Global Graph
P4. explicit & formal semantics
• assign types to things
• assign types to relations
• organise types in a hierarchy
• imp...
Examples of “semantics”
married-to
• is male
• married-to relates
males to females
• married-to relates
1 male to 1 female...
Semantic Web:
Where are we now?
Did we get anywhere?
• Google = meaningful search
• NXP = data integration
• BBC = content re-use
• Wallmart= SEO (RDF-a)
...
NXP: data integration
about 26.000 products
Triple store
Triple store
Departments
Customers
Notice the 3-layer architecture
BBC
Notice the 3-layer architecture
Did we get anywhere?
• Google = meaningful search
• NXP = data integration
• BBC = content re-use
• BestBuy = SEO (RDF-a)
...
Size Matters: 25-45 billion facts
The questions
that we couldn’t ask
10 years ago
• Heterogeneity
• Self-organisation, long tails
• Distribution
• Provenance & trust
• Dynamics
• Errors & Noise
• Scale
heterogeneity
is unavoidable
•Linguistic,
•Structural,
•Logical,
•Statistical,
....
Socio-
economic
first to
market
market...
Self-organisation
Self-organisation
Self-organisation
Self-organisation
Self-organisation
Bio-medical
ontologies in
Bio-portal > 5 links
Self-organisation
knowledge follows
a long-tail
incidental
or universal?
impact on
mapping?
impact on
reasoning?
impact on
storage?
Distribution
Caching?
Subgraphs?
Payload
priority?
query-
planning?
Provenance
Representation?
From provenance
to trust?
(Re)construction?
knowledge about
knowledge?
Dynamics
Streams? Incremental
reasoning?
Non-
monotonicity?
versioning?
Errors & noise
Maximally
consistent
subsets?
Fuzzy
Semantics?
Uncertainty
Semantics?
Rough
Semantics?
Modules?
Repair?
Arg...
Maximally
consistent
subsets?
Modules?
Repair?
Argumentation?
Fuzzy
Semantics?
Uncertainty
Semantics?
Rough
Semantics?
Str...
Methodological
Hobby horse
Laws about the physical universe
Laws about the information universe ?
knowledge follows
a long-tail
Law: F = - r
Law: |T|<< |A|
T = terminological knowledge
A = assertional knowledge
Dataset Closure of
T
Closure of
T + A
Ratio
LUBM 8sec 1h15min 562
Linked Life Data 332sec 1h05min 11
FactForge 89sec 2h45m...
Semantic Web questions we couldn't ask 10 years ago
Semantic Web questions we couldn't ask 10 years ago
Semantic Web questions we couldn't ask 10 years ago
Semantic Web questions we couldn't ask 10 years ago
Semantic Web questions we couldn't ask 10 years ago
Semantic Web questions we couldn't ask 10 years ago
Semantic Web questions we couldn't ask 10 years ago
Upcoming SlideShare
Loading in …5
×

of

Semantic Web questions we couldn't ask 10 years ago Slide 1 Semantic Web questions we couldn't ask 10 years ago Slide 2 Semantic Web questions we couldn't ask 10 years ago Slide 3 Semantic Web questions we couldn't ask 10 years ago Slide 4 Semantic Web questions we couldn't ask 10 years ago Slide 5 Semantic Web questions we couldn't ask 10 years ago Slide 6 Semantic Web questions we couldn't ask 10 years ago Slide 7 Semantic Web questions we couldn't ask 10 years ago Slide 8 Semantic Web questions we couldn't ask 10 years ago Slide 9 Semantic Web questions we couldn't ask 10 years ago Slide 10 Semantic Web questions we couldn't ask 10 years ago Slide 11 Semantic Web questions we couldn't ask 10 years ago Slide 12 Semantic Web questions we couldn't ask 10 years ago Slide 13 Semantic Web questions we couldn't ask 10 years ago Slide 14 Semantic Web questions we couldn't ask 10 years ago Slide 15 Semantic Web questions we couldn't ask 10 years ago Slide 16 Semantic Web questions we couldn't ask 10 years ago Slide 17 Semantic Web questions we couldn't ask 10 years ago Slide 18 Semantic Web questions we couldn't ask 10 years ago Slide 19 Semantic Web questions we couldn't ask 10 years ago Slide 20 Semantic Web questions we couldn't ask 10 years ago Slide 21 Semantic Web questions we couldn't ask 10 years ago Slide 22 Semantic Web questions we couldn't ask 10 years ago Slide 23 Semantic Web questions we couldn't ask 10 years ago Slide 24 Semantic Web questions we couldn't ask 10 years ago Slide 25 Semantic Web questions we couldn't ask 10 years ago Slide 26 Semantic Web questions we couldn't ask 10 years ago Slide 27 Semantic Web questions we couldn't ask 10 years ago Slide 28 Semantic Web questions we couldn't ask 10 years ago Slide 29 Semantic Web questions we couldn't ask 10 years ago Slide 30 Semantic Web questions we couldn't ask 10 years ago Slide 31 Semantic Web questions we couldn't ask 10 years ago Slide 32 Semantic Web questions we couldn't ask 10 years ago Slide 33 Semantic Web questions we couldn't ask 10 years ago Slide 34 Semantic Web questions we couldn't ask 10 years ago Slide 35 Semantic Web questions we couldn't ask 10 years ago Slide 36 Semantic Web questions we couldn't ask 10 years ago Slide 37 Semantic Web questions we couldn't ask 10 years ago Slide 38 Semantic Web questions we couldn't ask 10 years ago Slide 39 Semantic Web questions we couldn't ask 10 years ago Slide 40 Semantic Web questions we couldn't ask 10 years ago Slide 41 Semantic Web questions we couldn't ask 10 years ago Slide 42 Semantic Web questions we couldn't ask 10 years ago Slide 43 Semantic Web questions we couldn't ask 10 years ago Slide 44 Semantic Web questions we couldn't ask 10 years ago Slide 45
Upcoming SlideShare
OWL briefing
Next
Download to read offline and view in fullscreen.

13 Likes

Share

Download to read offline

Semantic Web questions we couldn't ask 10 years ago

Download to read offline

Talk given at the SSSW 2013 Semantic Web Summerschool.
Part 1: What is "Semantic Web" (in 4 principles and 1 movie)
Part 2: What question can we ask now that we couldn't ask 10 years ago
Part 3: Treat Computer Science as a *science*, not just as engineering!
(this part a short version of http://slidesha.re/SaUhS4 )

Related Audiobooks

Free with a 30 day trial from Scribd

See all

Semantic Web questions we couldn't ask 10 years ago

  1. 1. Frank van Harmelen All the questions we couldn’t ask 10 years ago Creative Commons License: allowed to share & remix, but must attribute & non-commercial
  2. 2. The bad news: you’re going to get 3 talks 1. Where are we now? – The Semantic Web in 4 principles & a movie – Did we get anywhere? 2. Now what? – Questions we couldn’t ask 10 years ago 3. Methodological hobby horse – Science or engineering?
  3. 3. Semantic Web: What is it?
  4. 4. “The Semantic Web” a.k.a. “The Web of Data”
  5. 5. http://www.youtube.com/watch?v=tBSdYi4EY3s
  6. 6. P1. Give all things a name
  7. 7. P2. Relations form a graph between things
  8. 8. P3. The names are addresses on the Web x T [<x> IsOfType <T>] different owners & locations <analgesic>
  9. 9. P1+P2+P3 = Giant Global Graph
  10. 10. P4. explicit & formal semantics • assign types to things • assign types to relations • organise types in a hierarchy • impose constraints on possible interpretations
  11. 11. Examples of “semantics” married-to • is male • married-to relates males to females • married-to relates 1 male to 1 female • = lowerbound upperbound
  12. 12. Semantic Web: Where are we now?
  13. 13. Did we get anywhere? • Google = meaningful search • NXP = data integration • BBC = content re-use • Wallmart= SEO (RDF-a) • data.gov = data-publishing
  14. 14. NXP: data integration about 26.000 products Triple store Triple store Departments Customers Notice the 3-layer architecture
  15. 15. BBC Notice the 3-layer architecture
  16. 16. Did we get anywhere? • Google = meaningful search • NXP = data integration • BBC = content re-use • BestBuy = SEO (RDF-a) • data.gov = data-publishing Oracle DB, IBM DB2 Reuters, New York Times, Guardian Sears, Kmart, OverStock, Volkswagen, Renault GoodRelations ontology, schema.org
  17. 17. Size Matters: 25-45 billion facts
  18. 18. The questions that we couldn’t ask 10 years ago
  19. 19. • Heterogeneity • Self-organisation, long tails • Distribution • Provenance & trust • Dynamics • Errors & Noise • Scale
  20. 20. heterogeneity is unavoidable •Linguistic, •Structural, •Logical, •Statistical, .... Socio- economic first to market market- share
  21. 21. Self-organisation
  22. 22. Self-organisation
  23. 23. Self-organisation
  24. 24. Self-organisation
  25. 25. Self-organisation
  26. 26. Bio-medical ontologies in Bio-portal > 5 links Self-organisation
  27. 27. knowledge follows a long-tail
  28. 28. incidental or universal? impact on mapping? impact on reasoning? impact on storage?
  29. 29. Distribution Caching? Subgraphs? Payload priority? query- planning?
  30. 30. Provenance Representation? From provenance to trust? (Re)construction? knowledge about knowledge?
  31. 31. Dynamics Streams? Incremental reasoning? Non- monotonicity? versioning?
  32. 32. Errors & noise Maximally consistent subsets? Fuzzy Semantics? Uncertainty Semantics? Rough Semantics? Modules? Repair? Argumentation?
  33. 33. Maximally consistent subsets? Modules? Repair? Argumentation? Fuzzy Semantics? Uncertainty Semantics? Rough Semantics? Streams? Incremental reasoning? Non- monotonicity? versioning? Representation? From provenance to trust? (Re)construction? knowledge about knowledge? Caching? Subgraphs? Payload priority? incidental or universal? impact on mapping? impact on reasoning? impact on storage? Socio- economic first to market market- share
  34. 34. Methodological Hobby horse
  35. 35. Laws about the physical universe Laws about the information universe ?
  36. 36. knowledge follows a long-tail Law: F = - r
  37. 37. Law: |T|<< |A| T = terminological knowledge A = assertional knowledge
  38. 38. Dataset Closure of T Closure of T + A Ratio LUBM 8sec 1h15min 562 Linked Life Data 332sec 1h05min 11 FactForge 89sec 2h45min 111 We don’t have any good laws on complexity
  • semanticweb

    Jan. 11, 2017
  • daniele.napoleone

    Nov. 30, 2014
  • ysauvageon

    Jul. 2, 2014
  • ahmadaassaf

    Aug. 12, 2013
  • keronos

    Jul. 18, 2013
  • OscarPDR

    Jul. 14, 2013
  • troncy

    Jul. 13, 2013
  • zaziki

    Jul. 12, 2013
  • gonewiththeway

    Jul. 12, 2013
  • kemani

    Jul. 11, 2013
  • evanwolf

    Jul. 10, 2013
  • emchateau

    Jul. 10, 2013
  • weblivz

    Jul. 9, 2013

Talk given at the SSSW 2013 Semantic Web Summerschool. Part 1: What is "Semantic Web" (in 4 principles and 1 movie) Part 2: What question can we ask now that we couldn't ask 10 years ago Part 3: Treat Computer Science as a *science*, not just as engineering! (this part a short version of http://slidesha.re/SaUhS4 )

Views

Total views

6,779

On Slideshare

0

From embeds

0

Number of embeds

1,411

Actions

Downloads

44

Shares

0

Comments

0

Likes

13

×