SlideShare une entreprise Scribd logo
1  sur  46
18 years of engagement for metadata and semantics in
Agriculture: was it worth the effort
Dr. rer. nat. Johannes Keizer, Goettingen, 2016-11-24
What we achieved really
• No one denies the importants of semantics
anymore, Ontologies everywhere
• Agroportal and GACS .. community not FAO alone
• The VocBench (a nice piece of open Source
software)
• The AGRIS LOD application is a powerful
demonstrator, what LOD can deliver
• Other important experiements: A prototype of a
dataset registry (CIARD RING), Agriprofiles
• Conceptual framework
• and most important!
http://aims.fao.org
Community
SEMANTICS ON THE
WEB
Looking around
The semantic web
The 2001 Scientific American article by Berners-Lee, Hendler,
and Lassila described an expected evolution of the existing
Web to a Semantic Web.[5] In 2006, Berners-Lee and
colleagues stated that: "This simple idea…remains largely
unrealized".[6] In 2013, more than four million Web domains
contained Semantic Web markup.[7]
According to the Verisign Domain Name Industry Brief the total
number of registered domain names is 284 million, an
increase over the January 2014 figure of 265 million
BUT WHAT DOES IT
MEAN IN PRACTICE?
The cloud gets bigger
What application do you mostly use?
• Evernote
• Google Suite
• Dropbox
• Economist
• Amazon
• Drupal
• Facebook
Semantics in Evernote
Existent! But Kind of ridiculous
• Simple tagging system
• No polyhierarachy allowed
(poly hierarchy is one of the
most real events )
• No relations between tags
• Useless inheritance features
Google Suite
• The same charme as normal google
search
• Have you created and used categories
in Gmail?
• Why not even auto categorization?
• «Add recipients» most useful feature
• Google Drive still uses mostly the
concept of physical folders
• Most effort into displaying adds
Amazon
The most intelligent app
They mostly get it
• Artificial Intelligence behind
• Analyzing reading habits
• But the possibilities would
be enormous
– Think about
autocategorization and
linking of your notes
• But: closed shop
Dropbox
Drupal
Drupal has modules that allow
to
:
• expose internal data as RDF;
• expose internal data through a SPARQL
engine;
• dynamically query remote RDF stores through
a SPARQL client;
• execute dynamic SPARQL queries and store
resulting triples as nodes according to a pre-
defined mapping
 Linked Data
Economist
Facebook
EXCEPT IN THE CASE OF DRUPAL
THE SEMANTIC WEB COMMUNITY
HAS NOT REALLY INFLUENCED
MAIN STREAM APPLICATIONS
Conclusions
BUSINESS CASE NOT
STRONG ENOUGH?
Why?
“… research suggests that seven sectors alone could
generate more than $3 trillion a year in additional value
as a result of open data, which is already giving rise to
hundreds of entrepreneurial businesses and helping
established companies to segment markets …”
Source: McKinsey Global Institute
"Making these data public will allow people to
make their own assessments of the progress of
our Good Growth Plan. It is also blurring the
traditional roles of business, government and
NGOs by highlighting our collective
responsibility to address acute global
challenges. Above all, the data will be of value
to farmers, enabling them to increase
productivity sustainably and to enhance their
livelihoods."
"Open data has the power to solve our most
challenging sustainability problems. … Agri-
tech businesses have a big role to play in
finding novel solutions to these problems. …
Syngenta is taking a step that puts them at
the forefront of the open data movement in
their sector. We look forward to working with
them to unlock benefits for farmers and
consumers worldwide."
Mike Mack, CEO of Syngenta
(2015, for 1st GGP data release)
Jeni Tennison, Deputy CEO and CTO of
the Open Data Institute
Now there is big data Hype
Paradigm Shift for research
• In the past
– 80% data production, 20% data
evaluatio
• In the future
– 20% data production, 80% data
evaluation
We have GODAN
• Advocacy
• Think Tank
• Knowledge Network
Aggregation States of Knowledge
Data and Information in Agricultural Research and Extension
Dataset
Registries
Data
processingSemantics
LOD Generator
triplifier,
concept and entity
identifier
Data Services
Webservices + APIs to
data stores
Data Storage
Infrastructure elements for FAIR data
THE FAIR PRINCIPLE
resources need to be
Findable
Accessible
Interoperable
Reusable
= FAIR
FAIR principle by Barend Mons, EC, EOSC
Data Issues
http://www.nature.com/ng/journal/v43/n4/full/ng0411-281.html
Going on!
• Semantics are needed
• Community Building is Prime necessity-
Chania Group
• Pragmatism in approach, avoiding over
commitment
• Developing plans for a data infrastructure
• Riding the big data tiger
• Influencing mainstream productivity tools
eRosa
Keynote at the MTSR conference

Contenu connexe

Tendances

What is big data ? | Big Data Applications
What is big data ? | Big Data ApplicationsWhat is big data ? | Big Data Applications
What is big data ? | Big Data ApplicationsShilpaKrishna6
 
Jeff Kelly, Wikibon Slides; Big Data Summit 2015
Jeff Kelly, Wikibon Slides; Big Data Summit 2015Jeff Kelly, Wikibon Slides; Big Data Summit 2015
Jeff Kelly, Wikibon Slides; Big Data Summit 2015MassTLC
 
Trends in Big Data & Business Challenges
Trends in Big Data & Business Challenges   Trends in Big Data & Business Challenges
Trends in Big Data & Business Challenges Experian_US
 
Big Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation SlidesBig Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation SlidesSlideTeam
 
Big data and Internet
Big data and InternetBig data and Internet
Big data and InternetSanoj Kumar
 
Big Data Trends - WorldFuture 2015 Conference
Big Data Trends - WorldFuture 2015 ConferenceBig Data Trends - WorldFuture 2015 Conference
Big Data Trends - WorldFuture 2015 ConferenceDavid Feinleib
 
BIG DATA & DATA ANALYTICS
BIG  DATA & DATA  ANALYTICSBIG  DATA & DATA  ANALYTICS
BIG DATA & DATA ANALYTICSNAGARAJAGIDDE
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data ScienceSrishti44
 
Towards a big data roadmap for europe
Towards a big data roadmap for europeTowards a big data roadmap for europe
Towards a big data roadmap for europeBIG Project
 
Data Con LA 2020 Keynote - Bryan Kirschner
Data Con LA 2020 Keynote - Bryan KirschnerData Con LA 2020 Keynote - Bryan Kirschner
Data Con LA 2020 Keynote - Bryan KirschnerData Con LA
 
Introduction to Big Data for LABDUG
Introduction to Big Data for LABDUGIntroduction to Big Data for LABDUG
Introduction to Big Data for LABDUGamuletc
 
Guest Lecture on Big Data in Business,
Guest Lecture on Big Data in Business, Guest Lecture on Big Data in Business,
Guest Lecture on Big Data in Business, saravana krishnamurthy
 
Austrade Presentation - Big Data the New Oil (Microsoft draft)
Austrade Presentation - Big Data the New Oil   (Microsoft draft)Austrade Presentation - Big Data the New Oil   (Microsoft draft)
Austrade Presentation - Big Data the New Oil (Microsoft draft)Dr Andrew Seit
 
BIG Data and Methodology-A review
BIG Data and Methodology-A reviewBIG Data and Methodology-A review
BIG Data and Methodology-A reviewShilpa Soi
 
Big Data, Big Deal: For Future Big Data Scientists
Big Data, Big Deal: For Future Big Data ScientistsBig Data, Big Deal: For Future Big Data Scientists
Big Data, Big Deal: For Future Big Data ScientistsWay-Yen Lin
 
OPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLS
OPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLSOPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLS
OPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLSAmin Chowdhury
 

Tendances (19)

What is big data ? | Big Data Applications
What is big data ? | Big Data ApplicationsWhat is big data ? | Big Data Applications
What is big data ? | Big Data Applications
 
Bigdata
Bigdata Bigdata
Bigdata
 
Jeff Kelly, Wikibon Slides; Big Data Summit 2015
Jeff Kelly, Wikibon Slides; Big Data Summit 2015Jeff Kelly, Wikibon Slides; Big Data Summit 2015
Jeff Kelly, Wikibon Slides; Big Data Summit 2015
 
Trends in Big Data & Business Challenges
Trends in Big Data & Business Challenges   Trends in Big Data & Business Challenges
Trends in Big Data & Business Challenges
 
Big Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation SlidesBig Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation Slides
 
Big data and Internet
Big data and InternetBig data and Internet
Big data and Internet
 
Big data
Big dataBig data
Big data
 
Big Data Trends - WorldFuture 2015 Conference
Big Data Trends - WorldFuture 2015 ConferenceBig Data Trends - WorldFuture 2015 Conference
Big Data Trends - WorldFuture 2015 Conference
 
BIG DATA & DATA ANALYTICS
BIG  DATA & DATA  ANALYTICSBIG  DATA & DATA  ANALYTICS
BIG DATA & DATA ANALYTICS
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 
Towards a big data roadmap for europe
Towards a big data roadmap for europeTowards a big data roadmap for europe
Towards a big data roadmap for europe
 
Data Con LA 2020 Keynote - Bryan Kirschner
Data Con LA 2020 Keynote - Bryan KirschnerData Con LA 2020 Keynote - Bryan Kirschner
Data Con LA 2020 Keynote - Bryan Kirschner
 
Introduction to Big Data for LABDUG
Introduction to Big Data for LABDUGIntroduction to Big Data for LABDUG
Introduction to Big Data for LABDUG
 
Guest Lecture on Big Data in Business,
Guest Lecture on Big Data in Business, Guest Lecture on Big Data in Business,
Guest Lecture on Big Data in Business,
 
Managing service business
Managing service businessManaging service business
Managing service business
 
Austrade Presentation - Big Data the New Oil (Microsoft draft)
Austrade Presentation - Big Data the New Oil   (Microsoft draft)Austrade Presentation - Big Data the New Oil   (Microsoft draft)
Austrade Presentation - Big Data the New Oil (Microsoft draft)
 
BIG Data and Methodology-A review
BIG Data and Methodology-A reviewBIG Data and Methodology-A review
BIG Data and Methodology-A review
 
Big Data, Big Deal: For Future Big Data Scientists
Big Data, Big Deal: For Future Big Data ScientistsBig Data, Big Deal: For Future Big Data Scientists
Big Data, Big Deal: For Future Big Data Scientists
 
OPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLS
OPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLSOPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLS
OPPORTUNITIES FOR THE USE OF DIGITAL TECHNOLOGY TOOLS
 

Similaire à Keynote at the MTSR conference

Similaire à Keynote at the MTSR conference (20)

Geospatial Intelligence Middle East 2013_Big Data_Steven Ramage
Geospatial Intelligence Middle East 2013_Big Data_Steven RamageGeospatial Intelligence Middle East 2013_Big Data_Steven Ramage
Geospatial Intelligence Middle East 2013_Big Data_Steven Ramage
 
What is the future of data strategy?
What is the future of data strategy?What is the future of data strategy?
What is the future of data strategy?
 
Big data and analytics
Big data and analyticsBig data and analytics
Big data and analytics
 
Presentation on Big Data
Presentation on Big DataPresentation on Big Data
Presentation on Big Data
 
BigData.pptx
BigData.pptxBigData.pptx
BigData.pptx
 
Big data and data mining
Big data and data miningBig data and data mining
Big data and data mining
 
Kartikey tripathi
Kartikey tripathiKartikey tripathi
Kartikey tripathi
 
Our big data
Our big dataOur big data
Our big data
 
Big data ppt
Big data pptBig data ppt
Big data ppt
 
final oracle presentation
final oracle presentationfinal oracle presentation
final oracle presentation
 
Big data analytics
Big data analyticsBig data analytics
Big data analytics
 
Special issues on big data
Special issues on big dataSpecial issues on big data
Special issues on big data
 
ppt final.pptx
ppt final.pptxppt final.pptx
ppt final.pptx
 
Big-Data-Seminar-6-Aug-2014-Koenig
Big-Data-Seminar-6-Aug-2014-KoenigBig-Data-Seminar-6-Aug-2014-Koenig
Big-Data-Seminar-6-Aug-2014-Koenig
 
Data mining with big data
Data mining with big dataData mining with big data
Data mining with big data
 
Data mining with big data
Data mining with big dataData mining with big data
Data mining with big data
 
Future of Data Strategy (ASEAN)
Future of Data Strategy (ASEAN)Future of Data Strategy (ASEAN)
Future of Data Strategy (ASEAN)
 
Big data ppt
Big data pptBig data ppt
Big data ppt
 
Bigdata " new level"
Bigdata " new level"Bigdata " new level"
Bigdata " new level"
 
Understanding big data
Understanding big dataUnderstanding big data
Understanding big data
 

Plus de Johannes Keizer (20)

Presentation CABI Beijing 2019 11-04
Presentation CABI Beijing  2019 11-04Presentation CABI Beijing  2019 11-04
Presentation CABI Beijing 2019 11-04
 
eROSA presentation at CAAS, September 2018
eROSA presentation at CAAS, September 2018eROSA presentation at CAAS, September 2018
eROSA presentation at CAAS, September 2018
 
2018 03 apan
2018 03 apan2018 03 apan
2018 03 apan
 
2017 11-15 macs
2017 11-15 macs2017 11-15 macs
2017 11-15 macs
 
2016 10 caas-ats
2016 10 caas-ats2016 10 caas-ats
2016 10 caas-ats
 
2016 08 gxaas
2016 08 gxaas2016 08 gxaas
2016 08 gxaas
 
2016 06 chengdu
2016 06 chengdu2016 06 chengdu
2016 06 chengdu
 
2017 08 apan
2017 08 apan2017 08 apan
2017 08 apan
 
2017 09 caas
2017 09 caas2017 09 caas
2017 09 caas
 
2017 11 wageningen-keizer
2017 11 wageningen-keizer2017 11 wageningen-keizer
2017 11 wageningen-keizer
 
2017 11 eosc-keizer
2017 11 eosc-keizer2017 11 eosc-keizer
2017 11 eosc-keizer
 
2017 11 cascd
2017 11 cascd2017 11 cascd
2017 11 cascd
 
2017 04 igad-jk
2017 04 igad-jk2017 04 igad-jk
2017 04 igad-jk
 
2017 02 apan
2017 02 apan2017 02 apan
2017 02 apan
 
2017 06 itpgrfa
2017 06 itpgrfa2017 06 itpgrfa
2017 06 itpgrfa
 
2017 03 brussels
2017 03 brussels2017 03 brussels
2017 03 brussels
 
2017 076 efita-sponsor-godan
2017 076 efita-sponsor-godan2017 076 efita-sponsor-godan
2017 076 efita-sponsor-godan
 
2017 07 montpellier-keizer
2017 07 montpellier-keizer2017 07 montpellier-keizer
2017 07 montpellier-keizer
 
2017 04 embl
2017 04 embl2017 04 embl
2017 04 embl
 
The FAIR principle in the Big Data World
The FAIR principle in the Big Data WorldThe FAIR principle in the Big Data World
The FAIR principle in the Big Data World
 

Dernier

Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girlsRussian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girlsMonica Sydney
 
Real Men Wear Diapers T Shirts sweatshirt
Real Men Wear Diapers T Shirts sweatshirtReal Men Wear Diapers T Shirts sweatshirt
Real Men Wear Diapers T Shirts sweatshirtrahman018755
 
在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查ydyuyu
 
原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查
原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查
原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查ydyuyu
 
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...gajnagarg
 
2nd Solid Symposium: Solid Pods vs Personal Knowledge Graphs
2nd Solid Symposium: Solid Pods vs Personal Knowledge Graphs2nd Solid Symposium: Solid Pods vs Personal Knowledge Graphs
2nd Solid Symposium: Solid Pods vs Personal Knowledge GraphsEleniIlkou
 
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdfMatthew Sinclair
 
Microsoft Azure Arc Customer Deck Microsoft
Microsoft Azure Arc Customer Deck MicrosoftMicrosoft Azure Arc Customer Deck Microsoft
Microsoft Azure Arc Customer Deck MicrosoftAanSulistiyo
 
Russian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi EscortsRussian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi EscortsMonica Sydney
 
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac RoomVip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Roommeghakumariji156
 
Indian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi EscortsIndian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi EscortsMonica Sydney
 
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...kajalverma014
 
20240510 QFM016 Irresponsible AI Reading List April 2024.pdf
20240510 QFM016 Irresponsible AI Reading List April 2024.pdf20240510 QFM016 Irresponsible AI Reading List April 2024.pdf
20240510 QFM016 Irresponsible AI Reading List April 2024.pdfMatthew Sinclair
 
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样ayvbos
 
"Boost Your Digital Presence: Partner with a Leading SEO Agency"
"Boost Your Digital Presence: Partner with a Leading SEO Agency""Boost Your Digital Presence: Partner with a Leading SEO Agency"
"Boost Your Digital Presence: Partner with a Leading SEO Agency"growthgrids
 
Best SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency DallasBest SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency DallasDigicorns Technologies
 
75539-Cyber Security Challenges PPT.pptx
75539-Cyber Security Challenges PPT.pptx75539-Cyber Security Challenges PPT.pptx
75539-Cyber Security Challenges PPT.pptxAsmae Rabhi
 
Power point inglese - educazione civica di Nuria Iuzzolino
Power point inglese - educazione civica di Nuria IuzzolinoPower point inglese - educazione civica di Nuria Iuzzolino
Power point inglese - educazione civica di Nuria Iuzzolinonuriaiuzzolino1
 
APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...
APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...
APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...APNIC
 
Nagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime Nagercoil
Nagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime NagercoilNagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime Nagercoil
Nagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime Nagercoilmeghakumariji156
 

Dernier (20)

Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girlsRussian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
 
Real Men Wear Diapers T Shirts sweatshirt
Real Men Wear Diapers T Shirts sweatshirtReal Men Wear Diapers T Shirts sweatshirt
Real Men Wear Diapers T Shirts sweatshirt
 
在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查
 
原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查
原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查
原版制作美国爱荷华大学毕业证(iowa毕业证书)学位证网上存档可查
 
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
 
2nd Solid Symposium: Solid Pods vs Personal Knowledge Graphs
2nd Solid Symposium: Solid Pods vs Personal Knowledge Graphs2nd Solid Symposium: Solid Pods vs Personal Knowledge Graphs
2nd Solid Symposium: Solid Pods vs Personal Knowledge Graphs
 
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
 
Microsoft Azure Arc Customer Deck Microsoft
Microsoft Azure Arc Customer Deck MicrosoftMicrosoft Azure Arc Customer Deck Microsoft
Microsoft Azure Arc Customer Deck Microsoft
 
Russian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi EscortsRussian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
 
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac RoomVip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
 
Indian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi EscortsIndian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
 
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
 
20240510 QFM016 Irresponsible AI Reading List April 2024.pdf
20240510 QFM016 Irresponsible AI Reading List April 2024.pdf20240510 QFM016 Irresponsible AI Reading List April 2024.pdf
20240510 QFM016 Irresponsible AI Reading List April 2024.pdf
 
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
 
"Boost Your Digital Presence: Partner with a Leading SEO Agency"
"Boost Your Digital Presence: Partner with a Leading SEO Agency""Boost Your Digital Presence: Partner with a Leading SEO Agency"
"Boost Your Digital Presence: Partner with a Leading SEO Agency"
 
Best SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency DallasBest SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency Dallas
 
75539-Cyber Security Challenges PPT.pptx
75539-Cyber Security Challenges PPT.pptx75539-Cyber Security Challenges PPT.pptx
75539-Cyber Security Challenges PPT.pptx
 
Power point inglese - educazione civica di Nuria Iuzzolino
Power point inglese - educazione civica di Nuria IuzzolinoPower point inglese - educazione civica di Nuria Iuzzolino
Power point inglese - educazione civica di Nuria Iuzzolino
 
APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...
APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...
APNIC Policy Roundup, presented by Sunny Chendi at the 5th ICANN APAC-TWNIC E...
 
Nagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime Nagercoil
Nagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime NagercoilNagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime Nagercoil
Nagercoil Escorts Service Girl ^ 9332606886, WhatsApp Anytime Nagercoil
 

Keynote at the MTSR conference

  • 1. 18 years of engagement for metadata and semantics in Agriculture: was it worth the effort Dr. rer. nat. Johannes Keizer, Goettingen, 2016-11-24
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15. What we achieved really • No one denies the importants of semantics anymore, Ontologies everywhere • Agroportal and GACS .. community not FAO alone • The VocBench (a nice piece of open Source software) • The AGRIS LOD application is a powerful demonstrator, what LOD can deliver • Other important experiements: A prototype of a dataset registry (CIARD RING), Agriprofiles • Conceptual framework • and most important!
  • 19. The semantic web The 2001 Scientific American article by Berners-Lee, Hendler, and Lassila described an expected evolution of the existing Web to a Semantic Web.[5] In 2006, Berners-Lee and colleagues stated that: "This simple idea…remains largely unrealized".[6] In 2013, more than four million Web domains contained Semantic Web markup.[7] According to the Verisign Domain Name Industry Brief the total number of registered domain names is 284 million, an increase over the January 2014 figure of 265 million
  • 20.
  • 21. BUT WHAT DOES IT MEAN IN PRACTICE? The cloud gets bigger
  • 22. What application do you mostly use? • Evernote • Google Suite • Dropbox • Economist • Amazon • Drupal • Facebook
  • 23. Semantics in Evernote Existent! But Kind of ridiculous • Simple tagging system • No polyhierarachy allowed (poly hierarchy is one of the most real events ) • No relations between tags • Useless inheritance features
  • 24. Google Suite • The same charme as normal google search • Have you created and used categories in Gmail? • Why not even auto categorization? • «Add recipients» most useful feature • Google Drive still uses mostly the concept of physical folders • Most effort into displaying adds
  • 25. Amazon The most intelligent app They mostly get it • Artificial Intelligence behind • Analyzing reading habits • But the possibilities would be enormous – Think about autocategorization and linking of your notes • But: closed shop
  • 27. Drupal Drupal has modules that allow to : • expose internal data as RDF; • expose internal data through a SPARQL engine; • dynamically query remote RDF stores through a SPARQL client; • execute dynamic SPARQL queries and store resulting triples as nodes according to a pre- defined mapping  Linked Data
  • 30. EXCEPT IN THE CASE OF DRUPAL THE SEMANTIC WEB COMMUNITY HAS NOT REALLY INFLUENCED MAIN STREAM APPLICATIONS Conclusions
  • 31. BUSINESS CASE NOT STRONG ENOUGH? Why?
  • 32. “… research suggests that seven sectors alone could generate more than $3 trillion a year in additional value as a result of open data, which is already giving rise to hundreds of entrepreneurial businesses and helping established companies to segment markets …” Source: McKinsey Global Institute "Making these data public will allow people to make their own assessments of the progress of our Good Growth Plan. It is also blurring the traditional roles of business, government and NGOs by highlighting our collective responsibility to address acute global challenges. Above all, the data will be of value to farmers, enabling them to increase productivity sustainably and to enhance their livelihoods." "Open data has the power to solve our most challenging sustainability problems. … Agri- tech businesses have a big role to play in finding novel solutions to these problems. … Syngenta is taking a step that puts them at the forefront of the open data movement in their sector. We look forward to working with them to unlock benefits for farmers and consumers worldwide." Mike Mack, CEO of Syngenta (2015, for 1st GGP data release) Jeni Tennison, Deputy CEO and CTO of the Open Data Institute Now there is big data Hype
  • 33.
  • 34. Paradigm Shift for research • In the past – 80% data production, 20% data evaluatio • In the future – 20% data production, 80% data evaluation
  • 35. We have GODAN • Advocacy • Think Tank • Knowledge Network
  • 36.
  • 37.
  • 39. Data and Information in Agricultural Research and Extension
  • 40. Dataset Registries Data processingSemantics LOD Generator triplifier, concept and entity identifier Data Services Webservices + APIs to data stores Data Storage Infrastructure elements for FAIR data
  • 41. THE FAIR PRINCIPLE resources need to be Findable Accessible Interoperable Reusable = FAIR FAIR principle by Barend Mons, EC, EOSC
  • 43. Going on! • Semantics are needed • Community Building is Prime necessity- Chania Group • Pragmatism in approach, avoiding over commitment • Developing plans for a data infrastructure • Riding the big data tiger • Influencing mainstream productivity tools
  • 44.
  • 45. eRosa

Notes de l'éditeur

  1. This diagram is taken from a Nature article from 2015. It shows the complex relationships between Data Intensive Science, large data sets and narrative articles. GODAN supports the Agricultural Data Interest Group of the Research Data Alliance to improve the many relations that are unsatisfactory at the moment
  2. There are several such examples of collaborative action to deliver serious policy focussed research. These pieces are being catalysed by several partners and perspectives: For example the papers here came out of discussions with Syngenta, CTA and University of Ottawa Law School. In the coming period we hope to work with our partners, especially in private sectors and well funded foundations to help bring some of these vision pieces to fruition.