ST&I National Information System Platform: the Brazilian case of Lattes

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In this presentation we address the issue of why innovation funding data are generally poor to support strategic studies. Generally they come from information systems designed to help only part of the processes of a national (or regional) innovation system. We present the main lessons learned from the Brazilian ST&I system projects, particularly Lattes and Portal Inovação.

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NATIONAL INFORMATION SYSTEM PLATFORMS (NISP) TO SUPPORT DECISION MAKING IN ST&I

POLICIES: Brazilian NISP analysis and perspectives

Roberto C. S. Pacheco; Vinícius Medina Kern; José Salm Jr; Denilson Sell.

Second WorkshopBuenos Aires, May 31, 2011

3rd Background Paper – Regional and international practices for disclosing information related to innovation and social environment impact of business.

Project “OPENING UP NATURAL RESOURCE-BASED INDUSTRIES FOR INNOVATION: EXPLORING NEW PATHWAYS FOR DEVELOPMENT IN LATIN AMERICA”

2

AGENDA

• Where were we in 2010?• Why innovation data is bad and what can we do

about it?1. How innovation data are created?2. What are the lessons learned from Brazilian ST&I

information projects?• Conclusions

3

Where were we in 2010?

How to use innovation funding data to study alternative pathways for Natural

Resources (NR) use?

In our first meeting the issue was:

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The first studies showed that we could not use the data…

“We need to put more emphasis on case studies, because the data is really bad”

But we concluded that:

Why innovation funding data is bad and what can we do about it?

In our paper we tried to answer the following question:

How innovation data are created in a national ST&I system?

What are the lessons learned from Brazilian ST&I information projects?

1 2

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Why the sponsor agency view about ST&I matters?

1.1

Where and how innovation data come from?

1.2

How ST&I information systems are developed?

2.1

How were Brazilian ST&I information systems developed?

2.2

One of our paper´s goal

1. How innovation data are created?

Why innovation funding data is bad and what can we do about it?

How innovation data are created in a national ST&I system?

1

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Why the sponsor agency view about ST&I matters?

1.1

Where and how innovation data come from?

1.2

1.1 How sponsor agency sees information matters…

Why innovation funding data is bad and what can we do about it?

How innovation data are created in a national ST&I system?

1

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Why the sponsor agency view about ST&I matters?

1.1

Where and how innovation data come from?

1.2

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1.1a Innovation data is designed to attend the sponsors…

Innovation data format is impacted by the way the sponsor agency understands the role of information in the national (regional) ST&I system.

An information system developed to help a funding agency depends on how this organization conceives the national (regional) innovation system being funded…

http://www.sussex.ac.uk/study/pg/2010/images/subjects/Science,%20technology%20and%20innovation.jpg

1.1b How to know the sponsor agency view of the NIS?

NIS conceptual (nonlinear) models

Indu

stry

Government

Companies S&T infraesrtructure

Sabato´s triangle

UniversityGovernment

Jorge de Sábato

Henry Etzkowitz

Triple Helix OECD Systemic Model

LoeLeydesdorff

Pacheco, et. al. 2010

• We need to know the public sponsor view of NIS (is it linear or nonlinear?).• Is the sponsor agency willing to treat information systems in the same way?

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10

CGEE

Dep

ts Labs

InvestorsPDP, PIB

RNP, Portal Inovação, Plataforma Lattes

Education andTraining System

Culture

NIS components

Environment

Innovation Law

Product and factorMarket conditions(ex. demand for engineers)

STI

STI researchers

STI R&D Groups

FINEP

Firms

S&T

Government

Petrobras

CNPq

MCT

MDIC

CENPES

ABIPTI

BNDESANPROTEC

ABDI

SINAESMEC

R&D groups at CENPES

ANVISA ANEEL

Communication infrastructure

1.1c How to design a national ST&I system model?

This was the view we adopted in the Portal Inovação project in Brazil: it is a platform because it considers all innovation players

1.2 Where and how innovation data come from?

Why innovation funding data is bad and what can we do about it?

How innovation data are created in a national ST&I system?

1

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Why the sponsor agency view about ST&I matters?

1.1

Where and how innovation data come from?

1.2

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1.2a Innovation data come from ST&I processes…

Innovation data come from information systems that help to deal with ST&I processes

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PlanningPublic call

for proposals

Evaluation Contract Mgmt.Results

and Impacts

GoalsPrioritiesFunding Programs

Term of referenceProposal creationDemand receptionDocument analysis

Peer reviewProject evaluationTeam evaluationClassification

Budget analysisBudget adjustmentInst. AgreementsPayment

Research progressTrainingST&I developmentProject reports

ConferencesMediaFinal reportAssessment

• ST&I Plans•Budget Plan•Reports

processes

Tasks

Data

• Proponent profile(Cvs, firm portfolio)• Project proposals• Institutional data•Documents

• Curriculum evaluation• Proposal evaluation• Budget analysis

•Contract•Work plan

approval• Payments

ST&I PlayersFunding agency

Funding agency Funding

candidatesociety

Funding agency Evaluators

Funding agency

Funding Beneficiary

ST&IInstitution

Funding agency

Funding Beneficiary

Funding agency

society

Funding Beneficiary

• Project reports• Publications• Patents•Dissertations/theses• Event presentations

• Job creation• Infrastructure

1.2b How ST&I processes and data are related?

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1.2c What are the ST&I data?

15

1.2c What are the ST&I data?

16Individual Collective Organizational

Stru

ctur

edU

nstr

uctu

red

Project proposal documentPublication

Social networksindividual profile

Web personal

profile

Project proposal description

Research group profile

Project proposal

document

Project proposal description

R&D network profile Project

team

ISTIprofile

CV

Course

Public agency

Firmprofile

Other organization

Project web data

ISTIweb data

Firmweb data

Public agencyweb data

Innovation demand/offering

Innovation demand/offering

Explicit relationship

Implicitrelationship

1.2d How ST&I data are connected?

Why innovation funding data is bad and what can we do about it?

What are the lessons learned from Brazilian ST&I information projects?

2

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How ST&I information systems are developed?

2.1

How were Brazilian ST&I information systems developed?

2.2

2.1 How ST&I information systems are developed?

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2.1a ST&I Systems are called CRIS

Current Research Information Systems (CRIS)

“Any information tool dedicated to provide access to and disseminate research information.

It covers projects, people (expertise), organisational structure, R&D outputs (products, patents, publications), R&D events and R&D facilities and equipment.”

[Eurocris organisation, 2006]

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2.1b A ST&I NISP = i CRISi

National Information Systems Platform (NISP)

“´A coherent array’ of information subsystems with the capacity to intercommunicate” (Aines, 1968).

By “coherent array”, NISP implies in CRIS diversity: NISP is not a centralized computerized information system.

Why a platform? NISP is a Platform when its set of CRIS form a coordinated view of information systems that interoperate, exchange services and identifies the user univocally.

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2.1c NISP include e-Gov systemsE-Government

Application of information and communication technologies to support government activities

The use of technologies to improve how citizens, employees, partners and government interact and conduct business. [Koh et al. 2005]

NISP is not only a matter of e-Gov, but public CRIS play a central role, because government is the player in best position to establish official systems.

Why innovation funding data is bad and what can we do about it?

What are the lessons learned from Brazilian ST&I information projects?

2

http://www.net-detective.co.uk/net-detective-finds-out-the-truth-about-anyone.jpg

How ST&I information systems are developed?

2.1

How were Brazilian ST&I information systems developed?

2.2

2.2 How were Brazilian ST&I CRIS developed?

22

2.2a Lattes Platform (since 1999)

Lattes curricula2.135 million

R&D Groups22,797 groups in 422 institutions

Institutions14,404 institutions (agencies, universities, companies, scientific organizations, institutes)

Integrated data architecture

Information Systems

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2.2a Strategic Developments in Lattes Project

• Lattes Institutional PlatformMore than 100 IST use it as anorganizational information asset

• International viewScienTI network: an initiative ahead of its time.

• TransparencyST&I investments under business intelligence applications

25

CurriculaKnowledge, experiences and

other related data

VISA experience or educational background

Portal

DCVISA

Curriculum LattesProfessional and researchers

Who is working with health surveillance? Who are the experts in

pharmacosurveillance? Which subjects are being investigated in HS? Who works in networks in HS ? How is the HS profile in certain region?

Sample of issues

Indicators CoP

Network Analysis

2.2b National directory of Health Surveillance Competences - DCVISA

VISA TechniciansResearchers

Other Professionals

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SINIMA

PedagogicalDocuments

EE Personal Profile

Lattes CVs in Environment

Institutional Data

Educator Space

Institutional Space SIBEA data infrastructure

SIBEA Public Portal

Environmental education indicators

Search for EE profiles

EE networking

2.2c National Portal in Environmental Education - SIBEA

27

BiotechnologyPortal DB

FINEP PRIME

Portal CoP

SAPI databases

Lattes R&D groups

Lattes CVs and R&D groups

IntellectualProperty

Innovation Portal data infrastructure

Portal Inovação public space

LattesCurricula

Portal Content

CompetencesDemands

Offerings

Intellectual property database

ExpertSpace

Firm Space

R&D groupSpace

STISpace

Innovationagent Space

• Innovation news, agenda, etc.• Search engine• Business Intelligence•Networking and topic map• CoP• Information tips

BiotechnologyPortal

PRIMEPortal

SAPIPortal

National Portal in Environmental Education - SIBEA2.2d National space for technical cooperation - Portal Inovação

After all, are they good for ST&I strategic decision making?

2.3

Why innovation funding data is bad and what can we do about it?

What are the lessons learned from Brazilian ST&I information projects?

2

http://www.net-detective.co.uk/net-detective-finds-out-the-truth-about-anyone.jpg

How ST&I information systems are developed?

2.1

How were Brazilian ST&I information systems developed?

2.2

2.2 How were Brazilian ST&I CRIS developed?

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2.3a Spatial data analysis

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Engenharia de Produto

Mecânica da Fratura, Fadiga e

IntegridadeEstrutural

Refrigeração, Ar Condicionado, Aquecimento e

Ventilação

Ciências Térmicas

Bioengenharia

Mecânica dosSólidos

CiênciasTérmicas

CiênciasTérmicas

Dinâmica

Engenharia de Fabricação

Fenômenos Não-lineares

Mecânicados Fluidos

Mecatrônica

MecânicaComputacional

2.3b For National Knowledge Profile Analysis

31

2.3c MERCK LabsWhat are the Brazilian competences in Health R&D?

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2.3c Searching for competences – Portal Inovação

33

2.3c Searching for competences – Portal Inovação

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2.3c Searching for competences – Portal Inovação

35

2.3c Health Research competences in Brazil

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2.3c Antibacterial National research knowledge map

Why innovation funding data is bad and what can we do about it?

What are the lessons learned from Brazilian ST&I information projects?

2

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How ST&I information systems are developed?

2.1

How were Brazilian ST&I information systems developed?

2.2

2. What did we learn from Brazilian ST&I systems?

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Leadership and commitment Integration

VISION/POLITICAL WILL

COMMON FRAMEWORKS/CO-OPERATION

Inter-agency collaboration Financing

CUSTOMER FOCUS

Access ChoiceCitizen

engagement

Privacy

RESPONSIBILITY

Accountabily Monitoring and Evaluation

2.2a International guidelines for e-Gov

OECD, 2003.

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•Gather data to fulfill government needs

OR

•Promote Information Society

•Operational (transactional to support public processes)

OR

•Strategic to create national spaces of information

•Exclusively dedicated to the government needs

OR

•Systemic, designed to fulfill the needs of diverse ST&I players

•Operational (transactional to support public processes)

OR

•Strategic to create national spaces of information

•Dedicated to a particular government demand

OR

•Systemic, built to attend all ST&I players

•Isolated and connected only to sponsor agency information needs

OR

•Strategic to create national spaces of information

•Ordinary Software Engineering methods

OR

•e-government software methodology based on R&D and knowledge engineering

WORLD VIEW

SYSTEM MISSION

DATA REQUIREMENT

SYSTEM OWNERSHIP

SYSTEM LIFE

CYCLECONNECTIVITY

METHODOLOGY

2.2b The e-Gov principles of NISP based on the Lattes e-Gov methodology.

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CONCLUSIONS

What can we conclude in terms of using innovation funding data in strategic

studies such as NR pathway analysis?

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How to create better data?

1) Apply e-Gov methodology in CRIS projects2) Include strategic issues from the beginning3) Apply knowledge systems to deal with CRIS and

related data (ex. web documents)4) Involve experts in data analysis

Hence, if we want useful (rich, correct, easily updated) data to analyze ST&I, we need to:

IMPORTANT: (1) and (2) are applicable only in new (or renewed) information system projects, but (3) and (4) can be useful even when the data is unstructured, and available in nonofficial sources. The problem with applying (3) and (4) without (1) and (2) is the cost-benefit relation of such studies.

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What can we do in our project?

Knowledge-based ST&I systems combined with experts´ analysis can help us to study innovation

data and check for evidences of new NR pathways…

Finally, we hope that we can say now:

MUITO OBRIGADO!

Roberto C. S. Pacheco; Vinícius Medina Kern; José Salm Jr; Denilson Sell.

Second WorkshopBuenos Aires, May 31, 2011

3rd Background Paper – Regional and international practices for disclosing information related to innovation and social environment impact of business. Project “OPENING UP NATURAL RESOURCE-BASED INDUSTRIES FOR INNOVATION: EXPLORING NEW PATHWAYS FOR DEVELOPMENT IN LATIN AMERICA”

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