data science

1. The fourth paradigm: a research perspective
Data Science Symposium
Arnold Bregt

2. Outline presentation
The fourth paradigm
Your opinion
The roles of science
●Data producer role
●Data user role
●Data governance/management role
Conclusions/refection

3. A short introduction to.....me (Arnold)
Geo-information Science - Wageningen University
MSc Geo-information science
Research topics our group:
●Sensing and measuring
●Modelling and visualization
●Integrated land monitoring
●Human-space interaction
●Empowering communities

4. My field: Geo-information science

5. Paradigms in Science: a classification

6. Your opinion
Who has made new discoveries by only analysing data?
Who think we collect too much data?
Who beliefs that the fourth paradigm is a new paradigm?

7. The fourth paradigm
Data-intensive scientific discovery
(almost) all disciplines are more data intensive
It is a hype (“Big data”)

8. Papers in Scopus “fourth paradigm”

9. Papers in Scopus “big data”

10. A lot of conferences

11. Universities and IBM

12. eScience in Scopus

13. Marie Tharp (Oceanography)
1920- 2006
Seafloor mapping (1957)
Envisioning processes from 2D observations

14. Is it really new?
Data is always used by science for discovery
What is new:
●Volume
●Type of data (more spatial/temporal resolution)
●Data by “accident” or “surprice”

15. More for less

16. Data by surprise

17. The role of Science
Data producer role
●Past
●Present
●Future
Data user role
●...
Data governance/management role
●....

18. Data producer role: Past
Collect own data key part of research
Contextual knowledge of data
Owned by researcher (at least not claimed by university)

19. Data producer role: Present
Own data collection additionally to existing data (data for validation)
Data collection in communities (consortia)
Researcher compile collections (data selection) (example)

20. Data producer role: Future
More producer of aggregated data based on existing data (meta- analysis on data)
Role of scientist as data producer will be reduced
Validation data from small experiments
Data production as an own activity (specialist)
....

21. Data user role: Past
Analyse own data
Direct knowledge of data context
(even) own software for data analysis (example)

22. Data user role: Present
Strong increase of reuse of existing data (example)
More statistical relations (statistically different)
Less understanding of causal relations

23. Example

24. Data user role: Future
Quest for processing and visualisation algorithms
Strong increase of re-use
More “data-based” science
..

25. Data governance/management role: Past
Researcher manages own data
Stored in paper archives
Collections are important
Role of libraries and museum's

26. Data governance/management role: Present
Increased attention and institutions
Data as part of publications
DANS, 3TU.datacentrum Research data Netherlands
Data management plan (PhD’s)

27. Data management plan
All PhD’s must formulate DMP.
Chair groups are responsible
Critical issue from plan to implementation

28. Data governance/Management
The Availability of Research Data Declines Rapidly with Article Age
Timothy H. et al. 2014, Current Biology
We examined the availability of data from 516 studies between 2 and 22 years old
The odds of a data set being reported as extant fell by 17% per year
Broken e-mails and obsolete storage devices were the main obstacles to data sharing
Policies mandating data archiving at publication are clearly needed

29. Data governance/management role: Future
Selection of data to be preserved
Specialist task (in close interaction with the library) “from book to data library”
Key-role for meta-data

30. Extent description
Target groups Functions Manage Search Exchange Use Personal + + - - Own organisation/researchers ++ ++ ++ ++ Other organisation/researchers - +++ +++ +++

31. Conclusions/Refection
Data has always played a key-role in science
The fourth paradigm is not new, but “scale is new”
The role of the scientist is changing from primary data collection to re-use of existing data
Which means that the “data knowledge” is decreasing

32. The fourth paradigm
For scientists an
evolution
(not a revolution)