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DNV GL © 2015 SAFER, SMARTER, GREENER DNV GL © 2015
Matchmaking A proof of concept for The Climate Technology Centre and Network
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Eelco Kruizinga
DNV GL
DNV GL © 2015
Standards, testing, inspection, certification and technical advice
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OIL & GAS
MARITIME
ENERGY
BUSINESS
ASSURANCE
SOFTWARE
RESEARCH & INNOVATION
CYBERNETICS
DNV GL © 2015
Safeguarding life, property and the environment, since 1864
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dnvgl.com
DNV GL © 2015
Strategic research and innovation programmes
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OIL & GAS AND
ENERGY SYSTEMS
ARCTIC TECHNOLOGY
POWER SYSTEMS ELECTRIFICATION
MATERIALS
CLIMATE CHANGE
MARITIME TRANSPORT
INFORMATION TECHNOLOGY
HEALTHCARE
• Adaptation
• Mitigation
• Super grid
• Smart grid
• Storage
• Materials in energy storage
• Risk management of
corrodible systems
• Advanced materials and
sensors
• Autonomous systems
• Big data analytics of sensor
data
LOW CARBON FUTURE
• Renewable energy
• Green economy
• Transformation process
• Offshore safety
• Safety and reliability of the
subsea factory
• Energy foresight
• Arctic offshore structures
• Arctic ship structures
• Arctic oil spill preparedness
• Safer shipping
• Greener shipping
• Smarter shipping
• Patient safety
DNV GL © 2015
Increased focus on drawing intelligence from data
“Other major developments we have just seen the start of,
and which provide great opportunities for most of our
business areas, are digitalization, connectivity and the
‘Internet of Things’. These will be crucial to ensure that the
components of wider integrated energy and transportation
systems work together as a whole. Digitalization is also
about cyber security and using data in smarter ways to gain
insight for better decisions.
So, we will use the strategy period to become a data
smart company, using digital solutions to innovate
and offer better services to our customers as well as
to increase our own efficiency”
August 2015.
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Group President
and CEO of DNV GL
DNV GL © 2015
DNV GL strategic partnership with CTCN
What is CTCN?
– UN operational body under UNFCCC
for combating climate change
– Focus on developing countries around the world
– Requests for assistance from developing countries
are screened and routed to the best partner
to provide the assistance
– Focus is on climate technologies: org/hard/software
Areas of collaboration:
– Knowledge management
– Private sector engagement in climate smart solutions
– Monitoring and evaluation
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c tc -n.org
DNV GL © 2015 SAFER, SMARTER, GREENER DNV GL © 2015
CTCN Matchmaking Assistant Proof of Concept Demonstrator
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DNV GL © 2015
Introduction
CTCN provides a pyramid of services including response plans to requests
for technical assistance from so-called National Designated Entities (NDEs)
Matching of requests for technical assistance with available consortium and
network partners, solutions and technology types is currently a manual
process
Amount of requests is expected to increase substantially in the future, as is
the volume of network partners
To cope with anticipated volumes, a web-based system can help recommend
partners, solutions and technology types with technical assistance requests
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DNV GL © 2015
Matchmaking at the heart of CTCN service provision
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Help to find the right solutions to
developing countries’ needs
DNV GL © 2015
Key question
Is it possible to automatically match incoming requests for assistance with
available expertise throughout the CTCN expertise pool, represented by a growing
number of network member organisations?
If so, this would then allow CTCN to provide solutions to developing countries’
needs, in a scalable, yet high-quality way.
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DNV GL © 2015
Partners in PoC undertaking
CTCN
DNV GL
Semantic Web Company
REEEP
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DNV GL © 2015
Looking to create further impacts and efficiencies
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• Introduction of search
to KMS • Climate technology
taxonomy and library • Matchmaking
Assistant
DNV GL © 2015
Demonstrator matchmaking assistant available in-line
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CTCN Climate Technology Manager can access the
Matchmaking Assistant from within their web-based administration system.
DNV GL © 2015
Results – CTCN Matchmaking Assistant – Home Page
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Note: examples provided are for illustration purposes only and do not represent actual decisions by CTCN
DNV GL © 2015
PoC Use Case 1 - Recommender
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On-line Matchmaking Assistant takes TA Request as input
And suggests organisations that have the expertise to help
On the basis of an extracted ‘fingerprint’ of the TA Request Note: examples provided are for illustration purposes only and do not represent actual decisions by CTCN
DNV GL © 2015
PoC Use Case 1 – Recommender Content Highlights = Fingerprint
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Note: examples provided are for illustration purposes only and do not represent actual decisions by CTCN
DNV GL © 2015
PoC Use Case 1 – Background information on Consortium Partners Recommended
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DNV GL © 2015
PoC Use Case 1 – Background information on Network Partners Recommended
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PoC Use Case 1 – Background information on relevant initiatives from Case Studies and existing projects
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DNV GL © 2015
PoC Use Case 2 – Faceted Search
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The user can filter through different areas of the expert vetted concepts to display documents in the pool of content with those extracted concepts
Note: examples provided are for illustration purposes only and do not represent actual decisions by CTCN
DNV GL © 2015
PoC Use Case 2 – Faceted Search
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The user can input key concepts into the open search field and the system recommends concepts from the thesaurus
Note: examples provided are for illustration purposes only and do not represent actual decisions by CTCN
DNV GL © 2015
CTCN specific adaptations to wider climate tagger thesaurus
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DNV GL © 2015
CTCN specific adaptations to the expert-vetted climate tagger thesaurus
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CTCN Consortium Partner Depth of info example 1
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CTCN Consortium Partner Depth of info example 2
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DNV GL © 2015
User Acceptance Testing
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The agreed benchmark for success was the positive feedback from the
Climate Technology Managers (CTMs)
• Will the Matchmaking Assistant help facilitate your work?
• Do you support this development based on your user testing?
• Can you see the potential in the system based on a live demonstration,
hands on testing, being able to provide feedback and seeing the speed at
which the developers can facilitate requested changes?
• The answer across the board was YES
DNV GL © 2015
PoC Limitations Important to Keep in Mind
The CTCN Matchmaking Assistant is a Proof of Concept
It demonstrates the potential of technology and approach
The documentation used on Consortium Partners and Network Members
varies in depth:
Information regarding skills, expertise, regional focus and capacity is limited
Currently a lot of this information is not on record but in the memory and
experience of CTCN CTMs
Any next phase will focus on integration of CTCN technology types
• From the expert-vetted process consulting with experts across the globe for
consensus, this has not been developed yet and will include approximately 500
new concepts
The scope of documents available for inclusion and analysis was limited
based on access to CTCN documentation thus far
• Solution would be to curate CTCN specific content in a next phase
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DNV GL © 2015
Lessons Learned
Use semi-structured information about organizations (DB & documents)
More information about organisations will benefit robustness of results
Enrich assistant by data & info from 3rd party sources (e.g. country Info,
solutions, on-line info about skills and expertise)
Additional information of experts to enhance the robustness of results
Record decision rationale
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DNV GL © 2015
Key Future Development and Opportunities
A public facing user interface to provide recommendations for technology
types and solutions to end users who may find what they need and not
submit a request for TA
Actively crawl pre-determined sources to proactively gather on-line
information for knowledge base and contextual case studies,
solutions, the scope to be finalized in coming discussions
Use the power of the system as framework to develop new protocols for
on-boarding new network partners in future
Further development of functionality – ranking, geographic expertise,
balancing selection
Further customization of search facets and user interface for CTCN
CTMs – i.e. order of displayed sectors, information about partners
Development and integration of technology types and solutions into
existing Climate Tagger Thesaurus
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Development of a ‘climate problem-language’ and inference via thesaurus relations
DNV GL © 2015
Future use cases?
• Front end user interface to search for known solutions and technology types
before submitting a request to CTCN open to the public
• Advanced Semantic Search
• CTCN Technology Pages
• News Aggregation and / or Media Monitoring Services
• CTCN Glossary Service
• Use Recommender Services for Climate Technology from Climate Tagger
• Enable Personalization Services
• Expand the use of Relations in the Climate Tagger Thesaurus relating
partners to specific regions, technologies, expertise utilizing existing
technology
• Multiple languages such as French, Spanish, Portuguese and German – can
develop further languages in the thesaurus in future
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DNV GL © 2015 SAFER, SMARTER, GREENER DNV GL © 2015 32
Eelco Kruizinga, [email protected]
Knowledge Management Group, DNV GL
Thank you.
