Research Data Management in São Paulo

Fabio Kon - FAPESP

LEARN Workshop United Nations CEPAL – Chile

27/10/2016

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State of São Paulo, Brasil

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41 Million people

34% of Brazil’s GDP

50% of Brazilian science

13% of State budget to HE

and R&D

1.64% GDP for R&D

3 State Universities

3 Federal Universities

52 State Tech Faculties

45% of the PhDs graduated in

Brazil (4,937 in 2010)

22 Research Institutes (19

state/3 federal)

1 Research Foundation

62% of R&D public support

comes from State sources

The State of São Paulo funding policy

• Funding for the state universities is a fixed percentage (9.57%) of state fiscal revenues

• Funding for FAPESP is 1% of total state fiscal revenues

• Effects – 25% of the country’s scientists create 48% of the

scientific articles and supervise 40% of the doctoral theses concluded each year

– Significant university-industry research interaction in a few areas

20150428 3 s+t-brazil-20150428.pptx

FAPESP - Overview

• Mission – support research in all fields

• Annual budget in 2015 ~~R$ 1.189 billion (approximately $PPP 629 million)

40% - fundamental research;

7.4% - research infrastructure;

52% - application-oriented research

Stability and Autonomy

• All proposals are peer reviewed (26,000 annually)

Average time for decision ~ 65 days

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Some of FAPESP’s main programs

• 9,000 ongoing Fellowships (SI, MSc, Dr, PostDoc)

• Research grants (ongoing) – 17 Centers for Research, Innovation and Diffusion (CEPID) - 11 years funding

– 276 Young Investigator Awards – 4 years funding

– 389 Thematic Research Projects – 5 years funding

– 2625 Regular Research Grants – 2 years funding

• Special Programs Biota, Bioen, Climate Change, eScience, Cinapce, ZIKA

• Application oriented research

– Joint University – Industry (PITE)

– Small business research (PIPE)

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Scielo – Open Access Scientific Electronic Library Online (supported by FAPESP)

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© C.H. Brito Cruz e Fapesp 7 11/11/2016

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Challenge

• Several large scale projects

• Generating a lot of data

• Data sharing performed in ad hoc ways

• Data provenance not properly recorded

• Long-term availability not guaranteed

• Many times data not publicly available

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Data Management Plan

• Required for eScience projects since 2015

• Currently designing policy to be required for all large projects within a couple of years and, later, for all projects.

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eScience call for proposals include:

• Data management plan: A major characteristic of eScience projects is its dependency on data management practices, and the need of making results public, to allow reuse and collaboration with other groups. Therefore, all projects should provide indication of how they intend to manage the data produced during the project (where the term “data” is taken on the large, and includes files, algorithms, software, samples, models, curriculum material and others).

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eScience – open source

• Proposals must explicit which efforts will be made for the results of selected projects to be largely available.

• The results should be accessible under an open source license approved by the OSI (www.opensource.org), in the case of software, or under a Creative Commons license (www.creativecommons.org), in the case of documentation, technical reports, and associated documents.

• These considerations also apply to databases, datasets, workflows, etc. generated by the project.

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Ongoing work: new DMP

• DMP answers 2 questions: – Which data will be produced?

– How will they be managed?

• Addressing, in 2 pages: – Description of data and metadata

– Sharing policy

– Mechanisms, formats, and standards for storage

– Legal and ethical restrictions

– Provenance and reproducibility

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Administrative/cultural issues

• Who will manage and curate repositories? – University?

– Recognized centers?

• How to train researchers in – Designing plan

– Maintaining and preserving data

How to breach cultural barriers against open science?

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Questions / Discussion

Prof. Fabio Kon

kon@ime.usp.br

Special Advisor to the Scientific Director

FAPESP – São Paulo Research Agency

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