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OpenDataMonitor
Horizon 2020
Coordination and Support Action
GARRI-3-2014 Scientific Information in the Digital Age: Text and Data Mining (TDM)
Project number: 665940
Roadmap to promoting greater uptake of data analytics in Europe
FutureTDM
Reducing Barriers and Increasing Uptake of Text and Data Mining for Research Environments
using a Collaborative Knowledge and Open Information Approach
Kiera McNeice
FutureTDM Symposium, Salzburg
June 13th, 2017
FutureTDM project aims
“The FutureTDM project seeks to improve uptake of text
and data mining (TDM) in the EU”
▪ Involve stakeholders
▪ Assess barriers
▪ Analyse best practices and applications
▪ Elaborate framework, priorities, roadmaps
▪ Empower through open knowledge base
▪ Disseminate results
2FutureTDM
Roadmap and policy priorities
Task 5.4:
Aggregate the established research activities of
the project to generate an EU-level roadmap for
stimulating TDM opportunities
▪ Develop agendas and roadmaps for sustainable uptake of TDM
▪ Highlight and address the future roles of libraries
▪ Consider content availability, end-user training, technical
infrastructure, data preservation
3FutureTDM
Addressing barriers: What have we done so far?
Expert reports
▪ Detailed overview of current situation and barriers to be addressed
▪ Evaluating potential economic benefits
▪ Best practices and policy recommendations
Engaging with stakeholders
▪ Communicating and raising awareness across fields, sectors, and countries
Awareness sheets
▪ Easy-to-read sheets highlighting key case studies
Stakeholder guidelines
▪ Practical advice to help with legal, licensing, data management, and
university policy
4FutureTDM
Policy priorities: FutureTDM recommendations
Key principles from FutureTDM Policy Framework:
▪ Uncertainty
▪ Fragmentation
▪ Restrictiveness
5FutureTDM
Policy priorities: FutureTDM recommendations
Key principles from FutureTDM Policy Framework:
▪ Uncertainty Awareness and Clarity
▪ Fragmentation TDM Without Boundaries
▪ Restrictiveness Equitable Access
6FutureTDM
Policy priorities: Legal Policies
TDM Without Boundaries
▪ Introduce harmonised, mandatory exceptions to copyright and database rights
▪ Harmonise definitions of key Data Protection concepts and terms
Equitable Access
▪ Support copyright and database rights exceptions for all TDM activities that do not trade on the
creative expression of content analysed (so long as content is accessed legally)
▪ Allow retention of copied content for the purpose of reproducibility of TDM research
▪ Provide guidelines on “reasonable and proportionate” technical measures that restrict TDM to
protect content holders’ infrastructure
Awareness and Clarity
▪ Clearly define any terms and concepts (e.g. “text and data mining”, or “severely affecting” privacy)
in laws relevant to TDM, or provide explanatory documentation where this is not possible
▪ Provide guidelines to help TDM practitioners comply with Data Protection regulations, including
best practice codes of conduct for self-regulation
7
Policy priorities: Skills and Education
Awareness and Clarity
▪ Establish computational thinking and basic principles of data science as fundamental aspects of
data literacy, to be introduced as early as possible in education systems
▪ Establish central, accessible information resource networks about TDM, connected on a national
and international level
TDM Without Boundaries
▪ Establish multi-stakeholder communication channels and platforms for sharing skills and best
practices across disciplines, sectors, and borders
Equitable Access
▪ Support public-private collaborations to ensure skills transfers and knowledge exchange
8
Policy priorities: Economy and Incentives
TDM Without Boundaries
▪ Ensure research funding can cover all aspects of the TDM value chain, including integration of
data silos, building infrastructure, storage costs, and scaling costs
Equitable Access
▪ Dedicate funding to platforms that help industry, academia and capital investors collaborate, and
understand and articulate the potential value of TDM
▪ Introduce incentives to reward researchers using TDM techniques in research projects
Awareness and Clarity
▪ Disseminate and promote “success stories” demonstrating the value of TDM and how it can
benefit different sectors
9
Policy priorities: Technical and Infrastructure
TDM Without Boundaries
▪ Support projects building common infrastructures where researchers can share, store, and access
research outputs and data for TDM purposes
▪ Promote and incentivise support for more European languages to broaden the usefulness of TDM
tools and technologies
Equitable Access
▪ Ensure TDM tools and technologies developed through publicly-funded research are shared under
open source licences
Awareness and Clarity
▪ Encourage and promote consistency in the use of open standards for data formats,
communications protocols, middleware, and other aspects of data infrastructure
▪ Support sharing of knowledge and best practices around existing TDM tools and their uses
10
Policy priorities: Summary
To stimulate TDM opportunities in the EU:
 Broaden, harmonise, and clarify legal scope for TDM activities
 Recognise data literacy as a fundamental skill for all members of society
 Dedicate funding to bridging gaps in the TDM value chain
 Fund and support knowledge-sharing initiatives and networks
 Promote and incentivise open and interoperable data infrastructures
11
Policy priorities: Summary
To stimulate TDM opportunities in the EU:
 Broaden, harmonise, and clarify legal scope for TDM activities
 Recognise data literacy as a fundamental skill for all members of society
 Dedicate funding to bridging gaps in the TDM value chain
 Fund and support knowledge-sharing initiatives and networks
 Promote and incentivise open and interoperable data infrastructures
12
(content availability)
(end-user training)
(technical infrastructure)
(data preservation)
(role of libraries)

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FutureTDM Roadmap

  • 1. OpenDataMonitor Horizon 2020 Coordination and Support Action GARRI-3-2014 Scientific Information in the Digital Age: Text and Data Mining (TDM) Project number: 665940 Roadmap to promoting greater uptake of data analytics in Europe FutureTDM Reducing Barriers and Increasing Uptake of Text and Data Mining for Research Environments using a Collaborative Knowledge and Open Information Approach Kiera McNeice FutureTDM Symposium, Salzburg June 13th, 2017
  • 2. FutureTDM project aims “The FutureTDM project seeks to improve uptake of text and data mining (TDM) in the EU” ▪ Involve stakeholders ▪ Assess barriers ▪ Analyse best practices and applications ▪ Elaborate framework, priorities, roadmaps ▪ Empower through open knowledge base ▪ Disseminate results 2FutureTDM
  • 3. Roadmap and policy priorities Task 5.4: Aggregate the established research activities of the project to generate an EU-level roadmap for stimulating TDM opportunities ▪ Develop agendas and roadmaps for sustainable uptake of TDM ▪ Highlight and address the future roles of libraries ▪ Consider content availability, end-user training, technical infrastructure, data preservation 3FutureTDM
  • 4. Addressing barriers: What have we done so far? Expert reports ▪ Detailed overview of current situation and barriers to be addressed ▪ Evaluating potential economic benefits ▪ Best practices and policy recommendations Engaging with stakeholders ▪ Communicating and raising awareness across fields, sectors, and countries Awareness sheets ▪ Easy-to-read sheets highlighting key case studies Stakeholder guidelines ▪ Practical advice to help with legal, licensing, data management, and university policy 4FutureTDM
  • 5. Policy priorities: FutureTDM recommendations Key principles from FutureTDM Policy Framework: ▪ Uncertainty ▪ Fragmentation ▪ Restrictiveness 5FutureTDM
  • 6. Policy priorities: FutureTDM recommendations Key principles from FutureTDM Policy Framework: ▪ Uncertainty Awareness and Clarity ▪ Fragmentation TDM Without Boundaries ▪ Restrictiveness Equitable Access 6FutureTDM
  • 7. Policy priorities: Legal Policies TDM Without Boundaries ▪ Introduce harmonised, mandatory exceptions to copyright and database rights ▪ Harmonise definitions of key Data Protection concepts and terms Equitable Access ▪ Support copyright and database rights exceptions for all TDM activities that do not trade on the creative expression of content analysed (so long as content is accessed legally) ▪ Allow retention of copied content for the purpose of reproducibility of TDM research ▪ Provide guidelines on “reasonable and proportionate” technical measures that restrict TDM to protect content holders’ infrastructure Awareness and Clarity ▪ Clearly define any terms and concepts (e.g. “text and data mining”, or “severely affecting” privacy) in laws relevant to TDM, or provide explanatory documentation where this is not possible ▪ Provide guidelines to help TDM practitioners comply with Data Protection regulations, including best practice codes of conduct for self-regulation 7
  • 8. Policy priorities: Skills and Education Awareness and Clarity ▪ Establish computational thinking and basic principles of data science as fundamental aspects of data literacy, to be introduced as early as possible in education systems ▪ Establish central, accessible information resource networks about TDM, connected on a national and international level TDM Without Boundaries ▪ Establish multi-stakeholder communication channels and platforms for sharing skills and best practices across disciplines, sectors, and borders Equitable Access ▪ Support public-private collaborations to ensure skills transfers and knowledge exchange 8
  • 9. Policy priorities: Economy and Incentives TDM Without Boundaries ▪ Ensure research funding can cover all aspects of the TDM value chain, including integration of data silos, building infrastructure, storage costs, and scaling costs Equitable Access ▪ Dedicate funding to platforms that help industry, academia and capital investors collaborate, and understand and articulate the potential value of TDM ▪ Introduce incentives to reward researchers using TDM techniques in research projects Awareness and Clarity ▪ Disseminate and promote “success stories” demonstrating the value of TDM and how it can benefit different sectors 9
  • 10. Policy priorities: Technical and Infrastructure TDM Without Boundaries ▪ Support projects building common infrastructures where researchers can share, store, and access research outputs and data for TDM purposes ▪ Promote and incentivise support for more European languages to broaden the usefulness of TDM tools and technologies Equitable Access ▪ Ensure TDM tools and technologies developed through publicly-funded research are shared under open source licences Awareness and Clarity ▪ Encourage and promote consistency in the use of open standards for data formats, communications protocols, middleware, and other aspects of data infrastructure ▪ Support sharing of knowledge and best practices around existing TDM tools and their uses 10
  • 11. Policy priorities: Summary To stimulate TDM opportunities in the EU:  Broaden, harmonise, and clarify legal scope for TDM activities  Recognise data literacy as a fundamental skill for all members of society  Dedicate funding to bridging gaps in the TDM value chain  Fund and support knowledge-sharing initiatives and networks  Promote and incentivise open and interoperable data infrastructures 11
  • 12. Policy priorities: Summary To stimulate TDM opportunities in the EU:  Broaden, harmonise, and clarify legal scope for TDM activities  Recognise data literacy as a fundamental skill for all members of society  Dedicate funding to bridging gaps in the TDM value chain  Fund and support knowledge-sharing initiatives and networks  Promote and incentivise open and interoperable data infrastructures 12 (content availability) (end-user training) (technical infrastructure) (data preservation) (role of libraries)