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Claudia Bauzer Medeiros - Open Science meets Data Science: Some challenges to be faced

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Open Science is a movement to make scientific research, its data and dissemination accessible to all levels of society. This movement considers aspects such as Open Access, Open Data, Reproducible Research and Open Software.

Each of these aspects presents discreteness that need to be evaluated and discussed by the scientific community so that guidelines are established that facilitate the dissemination of scientific information.

The great challenge is to establish effective and efficient practices that allow journals to add these demands in their editorial processes, so as not only to allow data, software and methods to be accessible, but also to encourage the community to do so.

Considering these questions, this panel has as a proposal to discuss important aspects about the advancement of research communication. Some of these aspects are placed in the SciELO indexing criteria, as is the case of referencing research materials in favor of transparency and reproducibility.

Syllabus
FAIR criteria, concepts and implementation; challenges for the publication of data and methods; institutional policies for open data; adoption of TOP guidelines (Transparency and Openness Promotion); software repositories; thematic areas data repositories.

Published in: Science
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Claudia Bauzer Medeiros - Open Science meets Data Science: Some challenges to be faced

  1. 1. Open Science meets Data Science: Some challenges to be faced Claudia Bauzer Medeiros Institute of Computing – Unicamp
  2. 2. Open Science – G7 Priority 1. Human Capital Formation – research and innovation 2. Financing – inclusive science, research and innovation 3. Global Research Infrastructures 4. Open Science
  3. 3. RDA - https://www.rd-alliance.org
  4. 4. Open Science • Open to all the access to scientific research • How ?????? • Why ???? • What ???????
  5. 5. COLLABORATION THROUGH DATA – OPEN SCIENCE = OPEN DATA
  6. 6. 6/10000 Open Science – slide adapted from Gray Respost Perguntas Data driven-science Models Simulations Papers Files Experiments Instruments XXXXX
  7. 7. National Academies of Sciences, Engineering, Medicine July 2018 Open science = Open access = papers Open data Open methods = open source
  8. 8. What is Open Data? • “What is OPEN DIGITAL DATA” – Share “everything”? Not necessarily • Everyone can – Discover if data exist – Discover how to obtain them Under constraints – security, confidentiality, ethics, intellectual property 8
  9. 9. OPEN SCIENCE – OPEN METADATA
  10. 10. HOW??? Datacite.org (Find, share, cite, connect)
  11. 11. Open science requires FAIR Data • Findable • Accessible • Interoperable • Reusable • ??? Have you fairicized your data??? 11
  12. 12. Open Science – Basic concepts Curation Preservation Data (which?) Processes: Workflows Reproducibility Cyberinfrastructure Reusability Provenance
  13. 13. WHAT ABOUT DATA SCIENCE?
  14. 14. The “sexiest job of the 21st century” 14 @Altigran Silva, Brasnam’18 keynote
  15. 15. Data Science (CACM) • Processes and systems to extract knowledge or insight from data in various forms and translate it into action. • Interdisciplinary field that integrates approaches from statistics, data mining, predictive analytics • Incorporates advances in scalable computing and data management. Berman et al. CACM 61(4), April 2018 @Altigran Silva, Brasnam’18 keynote 15
  16. 16. Data Science: Reality (FORBES 2016) • 80% of time of data scientists spent on data pre-processing, cleansing, etc. 16 https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says
  17. 17. Open Science meets data science Open science • Fairicized data • Concerns with – Privacy – Accessibility – Quality – Provenance – Reproducibility WHERE, HOW, will be used? Data Science • Mine and correlate data • Concerns with – Pattern extraction – Algorithmic efficiency – Production of knowledge – Ask interesting questions from data Big data and VVVVVVVVVV…
  18. 18. Open Science meets Data Science Open science • Fairicized data • Concerns with – Privacy – Accessibility – Quality – Provenance – Reproducibility WHERE, HOW, will be used? Data Science • Mine and correlate data • Concerns with – Pattern extraction – Algorithmic efficiency – Production of knowledge – Ask interesting questions from data Big data and VVVVVVVVVV…
  19. 19. Open Science meets Data Science Open science • Fairicized data • Concerns with – Privacy – Accessibility – Quality – Provenance – Reproducibility WHERE, HOW, will be used? Data Science • Mine and correlate data • Concerns with – Pattern extraction – Algorithmic efficiency – Production of knowledge – Ask interesting questions from data Big data and VVVVVVVVVV…
  20. 20. WHAT ABOUT VISUALIZATION????
  21. 21. Challenges • Fairicization • Curation • Visualization!!!!!!!!!!!!!! • For xxx science to work, interpretation is needed (who are the “appropriate” experts?)
  22. 22. www.fapesp.br/gestaodedados
  23. 23. Obrigada!!!! cmbm@ic.unicamp.br

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