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FAIR discovery - Open Knowledge Maps - Kraker Peter

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FAIR discovery with Open Knowledge Maps -presented by Peter Kraker during the OpenAIRE workshop Services to support FAIR data, Vienna: https://www.openaire.eu/openaire-workshop-making-services-fair-vienna-april-24th-2019 .

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FAIR discovery - Open Knowledge Maps - Kraker Peter

  1. 1. @OK_Maps
  2. 2. Uncitedness (publications): 12% - 82% (Larivière & Gingras 2009) Uncitedness (data): 85% (Peters et al. 2016) Transfer to practice (medicine): 14%, taking 17 years (Balas 1998)
  3. 3. Who we are Open Knowledge Maps is a charitable non-profit organization dedicated to dramatically improving the visibility of scientific knowledge for science and society alike
  4. 4. Overview of heart diseases
  5. 5. https://openknowledgemaps.org
  6. 6. Advantages
  7. 7. Open science, all the way open sourceopen content open data open roadmap
  8. 8. Largest visual search engine for research First 2.5 years: ½ million visits on the site 100,000+ maps created 1000+ participants in workshops
  9. 9. https://openknowledgemaps.eventbrite.com
  10. 10. Core Team
  11. 11. Advisors
  12. 12. Enthusiasts
  13. 13. Partners
  14. 14. Networks
  15. 15. Findability vs. discoverability Findability = attribute of the (meta-)data Discoverability = attribute of the infrastructure FAIR is a precondition to discoverability
  16. 16. The open discovery infrastructure Libraries, Archives, Repositories, Aggregators Meta aggregators Institutions, Researchers, Publishers Value added services A cycle of continuous innovation
  17. 17. DISCOVERY
  18. 18. Discovery IN – Rationale Discoverability is a key challenge: up to 85% of research data is not reused Lack of adequate user interfaces for data discovery Many market entrants following a closed/proprietary model o Prevents reuse o Takes away control and governance from the researchers and research institutions
  19. 19. Discovery IN – Purpose & Objective Provide user interfaces and other user-facing services for data discovery across disciplines Explore new and innovative ways of enabling discovery Apply user involvement and participatory design, going beyond academia Create FAIR and open infrastructures
  20. 20. Discovery IN – Workplan Stocktaking of relevant use cases as well as indices, interfaces and services Structuring: Defining the standards and structure of an open ecosystem for discovery that fulfils the use cases Implementation: Working towards implementation of the ecosystem

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