1.
Open Science
meets
Data Science:
Some challenges to be faced
Claudia Bauzer Medeiros
Institute of Computing – Unicamp

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.
RDA - https://www.rd-alliance.org

4.
Open Science
• Open to all the access to scientific research
• How ??????
• Why ????
• What ???????

5.
COLLABORATION THROUGH DATA –
OPEN SCIENCE = OPEN DATA

6.
6/10000
Open Science – slide
adapted from Gray
Respost
Perguntas
Data driven-science
Models
Simulations
Papers
Files
Experiments
Instruments
XXXXX

7.
National Academies of Sciences,
Engineering, Medicine
July 2018
Open science =
Open access = papers
Open data
Open methods = open source

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.
OPEN SCIENCE – OPEN METADATA

10.
HOW??? Datacite.org
(Find, share, cite, connect)

11.
Open science requires FAIR Data
• Findable
• Accessible
• Interoperable
• Reusable
• ??? Have you fairicized your data???
11

12.
Open Science – Basic concepts
Curation
Preservation
Data (which?)
Processes: Workflows Reproducibility
Cyberinfrastructure
Reusability
Provenance

13.
WHAT ABOUT DATA SCIENCE?

14.
The “sexiest job of the 21st century”
14
@Altigran Silva, Brasnam’18 keynote

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.
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.
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.
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.
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.
WHAT ABOUT
VISUALIZATION????

21.
Challenges
• Fairicization
• Curation
• Visualization!!!!!!!!!!!!!!
• For xxx science to work, interpretation is
needed (who are the “appropriate” experts?)

22.
www.fapesp.br/gestaodedados

23.
Obrigada!!!!
cmbm@ic.unicamp.br