A Keynote at the Web Science Conference, 2018, held at the VU Amsterdam [1]. This describes in the main the output of the Semantic Technology Institute International (STI2) Summit (for senior researchers in the Semantic Web field) held in Crete in September, 2017 [2].
1. https://websci18.webscience.org/
2. https://www.sti2.org/events/2017-sti2-semantic-summit
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The Future of Semantics on the Web
1. The Future of Semantics
on the Web
Web Science Conference
Prof. John Domingue (@johndmk)
Director, Knowledge Media Institute,
the Open University, UK
President STI International
On behalf of STI 2017 Summit Attendees
http://kmi.open.ac.uk/
https://www.sti2.org/events/2017-sti2-semantic-summit
4. STI2 Summit 2017
• Invitation only – mainly for seniors
• Run every 2 years
• Individually submitted papers
• Aggregation into 3 topics
• Sub-groups tackle topics in turn
5. STI Summit Attendees
Dieter FenselClaudia d’Amato John Domingue Sung-Kook HanStefan Decker JuanMiguelGómezBerbis
Andreas Harth Sabrine KirraneXatanas KiryakovMartin Hepp Axel NgongaMaria MaleshkovaJens Lehmann
York SureElena SimperlAdrian Paschke Ioan TomaJuan SequedaOleksandraPanasiuk Raphaël Troncy
5
6. Caveats
• Only a portion of the event
• Personal likes and prejudices remain
• All the mistakes are mine
• Happy to forward requests to authors of
ideas/research
6
8. Seman&c Web History Important
“Those who cannot remember the past are
condemned to repeat it.” George Santayana 1905/06
https://en.wikiquote.org/wiki/George_Santayana
https://en.wikiquote.org/wiki/Edmund_Burke
Edmund Burke 1790
“People will not look forward to posterity, who
never look backward to their ancestors.”
8
13. Cyc Common Sense Knowledge
h"p://www.cyc.com/kb/ 13
500K terms
17K types of relations
7M assertions based on terms
14. Agents in Original Semantic Web
“The real power of the Semantic Web will
be realized when people create many
programs that collect Web content from
diverse sources, process the
information and exchange the results
with other programs. The effectiveness of
such software agents will increase
exponentially as more machine-readable
Web content and automated services
(including other agents) become available.
The Semantic Web promotes this synergy:
even agents that were not expressly
designed to work together can transfer
data among themselves when the data
come with semantics.”
Tim Berners-Lee, James Hendler and Ora Lassila 14
15. Linked Open Data
Use1. URIs to name (identify) things.
Use2. HTTP URIs so that these things can be
looked up (interpreted, “dereferenced”).
Provide useful information about what a3.
name identifies when it’s looked up, using
open standards such as RDF, SPARQL, etc.
Refer to other things using their HTTP URI4. -
based names when publishing data on the
Web.
15
36. Cyc -> Knowledge Graph?
Jamie Taylor Manager of Schema Team at Google
Keynote at ISWC 2017
http://videolectures.net/iswc2017_taylor_applied_semantics/ 36
53. Data Consumption
• Is still problematic
• No good paradigm and best practices for
making data good for a purpose
53
54. Ontology engineering and data
mapping
• Ontology engineering and data mapping, as
done today, are complex and do not scale
• Matching/linking entities is still too complex
• Keeping mappings up to date as data
changes at source
• This makes it hard to come up with reliable
“data architecture” that uses LOD for
enterprise applications
54
69. Benchmarking the Knowledge Graph
Lifecycle
• Goals not fully known
• Not always clear what to measure
• Solution
– Semantic definitions
– Open benchmarks
– Open Toolset
– Queryable results
– Apply sFAIR
– Benchmarking body
69
80. Embedding Knowledge Graphs
Knowledge Graph Embedding: A Survey of Approaches and Applica<ons
Quan Wang , Zhendong Mao , Bin Wang, and Li Guo
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 29, NO. 12, DECEMBER 2017 80
89. Protocols
• HTTP(S)
• The Constrained Application Protocol (CoAP)
web transfer protocol for IoT from IETF
– Compatible with XML and JSON
• oneM2M - Standards for M2M and IoT
– Has a base ontology in OWL
• Discoverability, security,
scalability and minimal resource
use
http://www.onem2m.org/http://coap.technology/
89
90. Challenge 1: Actions on entities
What modelling language do we need?
Actions–
Context–
Constraints (devices, environment, user,–
etc.)
Interactions–
Compositions–
90
103. Background Tourism and Tyrol
• Tourism 40% GDP
• 40 Million night
stays per year
• Tyrol, Salzburg,
Vienna ->
40% Austria’s GDP.
• Tourism sector
3rd largest in EU 10% GDP/employees
• Especially important for Southern Europe
http://www.alpine-space.eu/projects/alpes/en/test-regions/regions/south-tyrol-italy 103
109. Approach
• Ontologies based on schema.org
• Static content and dynamic data
– Bookings and booking engines
– JSON-LD
• Publish guidelines for accommodation providers
• Pilots and partnerships
– Local agencies for hotels and ski resorts, Tyrol
tourism state agency, Austrian Ministry
• New approach for dealing with multiple
channels
109
110. Other Regions
• 3cixty.com
– French Riviera, Singapore, London, Milan,
Amsterdam, St Barthelemy…
– data from official tourist offices feeds & web
harvesting (Google, Facebook, Foursquare, Yelp)
– partnerships with booking/ticketing retailers
(booking.com, airbnb, ticketmaster)
• pas-time.org - personalize the package to
individuals based on past trips and activities
(using Amadeus data lake)
110
111. Challenges and Issues
GDPR vs security (terrorism)•
Telecom data (+ IoT wearables) track location & increase–
personalization
Heterogeneity of data sources•
Bias in data sources•
Data quality•
live data, updates, outdated data–
Licensing•
Multilinguality•
google translate can help–
semantics helps with controlled vocabularies (e.g. events)–
111
115. “It’s a small world ……
…but I wouldn’t want to have to paint it.”
Steven Wright
https://morristowngreen.com/2012/12/02/comedian-steven-wright-at-the-mayo-in-
morristown-we-could-have-used-him-during-the-gas-lines/
115
120. Conclusions 1/3
Main role benefit of semantics is its ability to sit•
between the machine and humans:
Raising the level of discourse–
Supporting interoperability–
Enabling automation–
What has changed•
Scale–
Industrial take– -up
Future•
Adapting to ever changing context–
Hitting the sweet spot between reasoning power and–
simplicity
120
121. Conclusions 2/3
• Context is very different to pre and early web
days
– Ubiquity of devices
– Volume of data
• Societal Concerns
– Over centralization
– Data exacerbating inequality – need for ‘data
justice’
– Privacy
– Security
121
122. Conclusions 3/3
• Scalable Data
– Need for incentivized, benchmarked full life-cycle
– Benefits from a more open publishing process
– Decentralised platforms
• Dynamics
– Unclear how to support decentralized semantic
applications in M2M context
• Real world applications
– Development of comprehensive framework to
support creation of sector specific KGs
122