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Presentation’s Subtitle
#openminted_eu, #or2016, #tdm
Repositories in the
centre of new scientific
knowledge
Text Mining: the next data
frontier
Natalia Manola
Athena Research & Innovation Centre
Some facts About scientific literature
OR2016 - 13 June, 2016 - Dublin,
IRELAND
The global research community generates over 1.5 million new
scholarly articles per annum.
The STM report (2009)
… some 90% of papers … are never cited.
… 50% of papers are never read by anyone other than their
authors, referees and journal editors
Lokman I. Meho, The rise and rise of citation analysis, 2007
… one paper published every 30 seconds
… 70,000 papers published on a single protein, the tumor
suppressor p53
Spangler et al, Automated Hypothesis Generation based on
Mining Scientific Literature, 2014
2
Emerging solution(S)
Machine reading
process textual sources, organise and classify in various
dimensions, extract main (indexical) information items,
… and “understanding”
identify and extract entities and relations between entities, facilitate
the transformation of unstructured textual sources into structured
data
… and predicting
enable the multidimensional analysis of structured data to extract
meaningful insights and improve the ability to predict
OR2016 - 13 June, 2016 - Dublin,
IRELAND
3
What
OpenMinted is
About
MAIN Objectives
Establish an open and sustainable Text and
Data Mining (TDM) platform and
infrastructure where researchers can
discover, collaboratively create, share and re-
use knowledge from a wide range of text based
scientific and scholarly related sources.
OR2016 - 13 June, 2016 - Dublin,
IRELAND
5
A next step from Open Access to
Open Science
A complex Landscape
egi conference - lisbon, 18-22 may
2015
Text Mining Researchers
Computing Infrastructures
Content Providers
End Users
6
HIGH LEVEL
ARCHITECTURE
OR2016 - 13 June, 2016 - Dublin,
IRELAND
7
Policies &
guidelines
service oriented – discovery, re-use of
content and tools
build on existing TDM tools - no focus on
new algorithms
infrastructure – focus on interoperability
community driven - user centric
requirements
open science - openness at all levels
Key Characteristics
8
OR2016 - 13 June, 2016 - Dublin,
IRELAND
Challenges
Discoverable & accessible content &
services
• Document literature content, language/knowledge resources, data
categories taxonomies, provenance information
• Document language processing/text mining services and workflows
• Generic and domain-specific metadata descriptions
Interoperable services
• Combine services into workflows
• Combine content and language resources with services and workflows
• Combine automatic and manual/crowdsourcing annotation services
IPR and licensing
• Study IPR restrictions for reuse of sources as well as possible exceptions
• Promote clarity and standardisation of legal rights and obligations
• Translate the legal & policy aspects into specifications for lawful user-to-
service and service-to-service interactionsOR2016 - 13 June, 2016 - Dublin,
IRELAND
9
Building on existing language resources repositories
and infras (meta-share, clarin)
Starting with repositories and OA
publishers
via OpenAIRE and CORE
Promoting existing standards and best practices
AND technologies
In close collaboration with the FUTURETDM project
http://project.futuretdm.eu/
OR2016 - 13 June, 2016 - Dublin,
IRELAND
Scholarly
Comm.
Feature extraction
Data citation
Research
analytics
Life
Sciences
Curation of
databases and
lexica in
Chembolomics &
neuroinformatics
Agriculture
Extracting
information from
tables for food
safety alerts
Social
Sciences
Data citation
Community Driven
10
From the very beginning…
Requirements, content, barriers, expected outcomes.
… to the very end
Create applications, validate and evaluate the results.
twitter.com/openminted_eu
facebook.com/openminted
bit.do/openmintedlinkedin
vimeo.com/openminted
bit.do/openmintedplus
THANK YOU!
Natalia Manola
natalia@di.uoa.gr
twitter.com/openminted_eu
facebook.com/openminted
bit.do/openmintedlinkedin
vimeo.com/openminted
bit.do/openmintedplus

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OpenMinTeD - Repositories in the centre of new scientific knowledge

  • 1. Presentation’s Subtitle #openminted_eu, #or2016, #tdm Repositories in the centre of new scientific knowledge Text Mining: the next data frontier Natalia Manola Athena Research & Innovation Centre
  • 2. Some facts About scientific literature OR2016 - 13 June, 2016 - Dublin, IRELAND The global research community generates over 1.5 million new scholarly articles per annum. The STM report (2009) … some 90% of papers … are never cited. … 50% of papers are never read by anyone other than their authors, referees and journal editors Lokman I. Meho, The rise and rise of citation analysis, 2007 … one paper published every 30 seconds … 70,000 papers published on a single protein, the tumor suppressor p53 Spangler et al, Automated Hypothesis Generation based on Mining Scientific Literature, 2014 2
  • 3. Emerging solution(S) Machine reading process textual sources, organise and classify in various dimensions, extract main (indexical) information items, … and “understanding” identify and extract entities and relations between entities, facilitate the transformation of unstructured textual sources into structured data … and predicting enable the multidimensional analysis of structured data to extract meaningful insights and improve the ability to predict OR2016 - 13 June, 2016 - Dublin, IRELAND 3
  • 5. MAIN Objectives Establish an open and sustainable Text and Data Mining (TDM) platform and infrastructure where researchers can discover, collaboratively create, share and re- use knowledge from a wide range of text based scientific and scholarly related sources. OR2016 - 13 June, 2016 - Dublin, IRELAND 5 A next step from Open Access to Open Science
  • 6. A complex Landscape egi conference - lisbon, 18-22 may 2015 Text Mining Researchers Computing Infrastructures Content Providers End Users 6
  • 7. HIGH LEVEL ARCHITECTURE OR2016 - 13 June, 2016 - Dublin, IRELAND 7 Policies & guidelines
  • 8. service oriented – discovery, re-use of content and tools build on existing TDM tools - no focus on new algorithms infrastructure – focus on interoperability community driven - user centric requirements open science - openness at all levels Key Characteristics 8 OR2016 - 13 June, 2016 - Dublin, IRELAND
  • 9. Challenges Discoverable & accessible content & services • Document literature content, language/knowledge resources, data categories taxonomies, provenance information • Document language processing/text mining services and workflows • Generic and domain-specific metadata descriptions Interoperable services • Combine services into workflows • Combine content and language resources with services and workflows • Combine automatic and manual/crowdsourcing annotation services IPR and licensing • Study IPR restrictions for reuse of sources as well as possible exceptions • Promote clarity and standardisation of legal rights and obligations • Translate the legal & policy aspects into specifications for lawful user-to- service and service-to-service interactionsOR2016 - 13 June, 2016 - Dublin, IRELAND 9 Building on existing language resources repositories and infras (meta-share, clarin) Starting with repositories and OA publishers via OpenAIRE and CORE Promoting existing standards and best practices AND technologies In close collaboration with the FUTURETDM project http://project.futuretdm.eu/
  • 10. OR2016 - 13 June, 2016 - Dublin, IRELAND Scholarly Comm. Feature extraction Data citation Research analytics Life Sciences Curation of databases and lexica in Chembolomics & neuroinformatics Agriculture Extracting information from tables for food safety alerts Social Sciences Data citation Community Driven 10 From the very beginning… Requirements, content, barriers, expected outcomes. … to the very end Create applications, validate and evaluate the results.